WorldWideScience

Sample records for vegetation index time

  1. Detecting inter-annual variations in the phenology of evergreen conifers using long-term MODIS vegetation index time series.

    OpenAIRE

    Ulsig, Laura

    2016-01-01

    Long-term observations of vegetation phenology can be used to monitor the response of terrestrial ecosystems to climate change. Satellite remote sensing provides the most efficient means to observe phenological events through time series analysis of vegetation indices such as the Normalised Difference Vegetation Index (NDVI). This study investigates the potential of the Photochemical Reflectance Index (PRI), which has been linked to vegetation light use efficiency, to improve the accuracy of ...

  2. Detecting Inter-Annual Variations in the Phenology of Evergreen Conifers Using Long-Term MODIS Vegetation Index Time Series

    OpenAIRE

    Ulsig, Laura; Nichol, Caroline J.; Huemmrich, Karl F.; Landis, David R.; Middleton, Elizabeth M.; Lyapustin, Alexei I.; Mammarella, Ivan; Levula, Janne; Porcar-Castell, Albert

    2017-01-01

    Long-term observations of vegetation phenology can be used to monitor the response of terrestrial ecosystems to climate change. Satellite remote sensing provides the most efficient means to observe phenological events through time series analysis of vegetation indices such as the Normalized Difference Vegetation Index (NDVI). This study investigates the potential of a Photochemical Reflectance Index (PRI), which has been linked to vegetation light use efficiency, to improve the accuracy of MO...

  3. Canopy Modeling of Aquatic Vegetation: Construction of Submerged Vegetation Index

    Science.gov (United States)

    Ma, Z.; Zhou, G.

    2018-04-01

    The unique spectral characteristics of submerged vegetation in wetlands determine that the conventional terrestrial vegetation index cannot be directly employed to species identification and parameter inversion of submerged vegetation. Based on the Aquatic Vegetation Radiative Transfer model (AVRT), this paper attempts to construct an index suitable for submerged vegetation, the model simulated data and a scene of Sentinel-2A image in Taihu Lake, China are utilized for assessing the performance of the newly constructed indices and the existent vegetation indices. The results show that the angle index composed by 525 nm, 555 nm and 670 nm can resist the effects of water columns and is more sensitive to vegetation parameters such as LAI. Furthermore, it makes a well discrimination between submerged vegetation and water bodies in the satellite data. We hope that the new index will provide a theoretical basis for future research.

  4. On the characterization of vegetation recovery after fire disturbance using Fisher-Shannon analysis and SPOT/VEGETATION Normalized Difference Vegetation Index (NDVI) time series

    Science.gov (United States)

    Lasaponara, Rosa; Lanorte, Antonio; Lovallo, Michele; Telesca, Luciano

    2015-04-01

    Time series can fruitfully support fire monitoring and management from statistical analysis of fire occurrence (Tuia et al. 2008) to danger estimation (lasaponara 2005), damage evaluation (Lanorte et al 2014) and post fire recovery (Lanorte et al. 2014). In this paper, the time dynamics of SPOT-VEGETATION Normalized Difference Vegetation Index (NDVI) time series are analyzed by using the statistical approach of the Fisher-Shannon (FS) information plane to assess and monitor vegetation recovery after fire disturbance. Fisher-Shannon information plane analysis allows us to gain insight into the complex structure of a time series to quantify its degree of organization and order. The analysis was carried out using 10-day Maximum Value Composites of NDVI (MVC-NDVI) with a 1 km × 1 km spatial resolution. The investigation was performed on two test sites located in Galizia (North Spain) and Peloponnese (South Greece), selected for the vast fires which occurred during the summer of 2006 and 2007 and for their different vegetation covers made up mainly of low shrubland in Galizia test site and evergreen forest in Peloponnese. Time series of MVC-NDVI have been analyzed before and after the occurrence of the fire events. Results obtained for both the investigated areas clearly pointed out that the dynamics of the pixel time series before the occurrence of the fire is characterized by a larger degree of disorder and uncertainty; while the pixel time series after the occurrence of the fire are featured by a higher degree of organization and order. In particular, regarding the Peloponneso fire, such discrimination is more evident than in the Galizia fire. This suggests a clear possibility to discriminate the different post-fire behaviors and dynamics exhibited by the different vegetation covers. Reference Lanorte A, R Lasaponara, M Lovallo, L Telesca 2014 Fisher-Shannon information plane analysis of SPOT/VEGETATION Normalized Difference Vegetation Index (NDVI) time series to

  5. Assessments of Drought Impacts on Vegetation in China with the Optimal Time Scales of the Climatic Drought Index

    Directory of Open Access Journals (Sweden)

    Zheng Li

    2015-07-01

    Full Text Available Drought is expected to increase in frequency and severity due to global warming, and its impacts on vegetation are typically extensively evaluated with climatic drought indices, such as multi-scalar Standardized Precipitation Evapotranspiration Index (SPEI. We analyzed the covariation between the SPEIs of various time scales and the anomalies of the normalized difference vegetation index (NDVI, from which the vegetation type-related optimal time scales were retrieved. The results indicated that the optimal time scales of needle-leaved forest, broadleaf forest and shrubland were between 10 and 12 months, which were considerably longer than the grassland, meadow and cultivated vegetation ones (2 to 4 months. When the optimal vegetation type-related time scales were used, the SPEI could better reflect the vegetation’s responses to water conditions, with the correlation coefficients between SPEIs and NDVI anomalies increased by 5.88% to 28.4%. We investigated the spatio-temporal characteristics of drought and quantified the different responses of vegetation growth to drought during the growing season (April–October. The results revealed that the frequency of drought has increased in the 21st century with the drying trend occurring in most of China. These results are useful for ecological assessments and adapting management steps to mitigate the impact of drought on vegetation. They are helpful to employ water resources more efficiently and reduce potential damage to human health caused by water shortages.

  6. Validation of Vegetation Index Time Series from Suomi NPP Visible Infrared Imaging Radiometer Suite Using Tower Radiation Flux Measurements

    Science.gov (United States)

    Miura, T.; Kato, A.; Wang, J.; Vargas, M.; Lindquist, M.

    2015-12-01

    Satellite vegetation index (VI) time series data serve as an important means to monitor and characterize seasonal changes of terrestrial vegetation and their interannual variability. It is, therefore, critical to ensure quality of such VI products and one method of validating VI product quality is cross-comparison with in situ flux tower measurements. In this study, we evaluated the quality of VI time series derived from Visible Infrared Imaging Radiometer Suite (VIIRS) onboard the Suomi National Polar-orbiting Partnership (NPP) spacecraft by cross-comparison with in situ radiation flux measurements at select flux tower sites over North America and Europe. VIIRS is a new polar-orbiting satellite sensor series, slated to replace National Oceanic and Atmospheric Administration's Advanced Very High Resolution Radiometer in the afternoon overpass and to continue the highly-calibrated data streams initiated with Moderate Resolution Imaging Spectrometer of National Aeronautics and Space Administration's Earth Observing System. The selected sites covered a wide range of biomes, including croplands, grasslands, evergreen needle forest, woody savanna, and open shrublands. The two VIIRS indices of the Top-of-Atmosphere (TOA) Normalized Difference Vegetation Index (NDVI) and the atmospherically-corrected, Top-of-Canopy (TOC) Enhanced Vegetation Index (EVI) (daily, 375 m spatial resolution) were compared against the TOC NDVI and a two-band version of EVI (EVI2) calculated from tower radiation flux measurements, respectively. VIIRS and Tower VI time series showed comparable seasonal profiles across biomes with statistically significant correlations (> 0.60; p-value 0.95), with mean differences of 2.3 days and 5.0 days for the NDVI and the EVI, respectively. These results indicate that VIIRS VI time series can capture seasonal evolution of vegetated land surface as good as in situ radiometric measurements. Future studies that address biophysical or physiological interpretations

  7. Detecting Inter-Annual Variations in the Phenology of Evergreen Conifers Using Long-Term MODIS Vegetation Index Time Series

    Directory of Open Access Journals (Sweden)

    Laura Ulsig

    2017-01-01

    Full Text Available Long-term observations of vegetation phenology can be used to monitor the response of terrestrial ecosystems to climate change. Satellite remote sensing provides the most efficient means to observe phenological events through time series analysis of vegetation indices such as the Normalized Difference Vegetation Index (NDVI. This study investigates the potential of a Photochemical Reflectance Index (PRI, which has been linked to vegetation light use efficiency, to improve the accuracy of MODIS-based estimates of phenology in an evergreen conifer forest. Timings of the start and end of the growing season (SGS and EGS were derived from a 13-year-long time series of PRI and NDVI based on a MAIAC (multi-angle implementation of atmospheric correction processed MODIS dataset and standard MODIS NDVI product data. The derived dates were validated with phenology estimates from ground-based flux tower measurements of ecosystem productivity. Significant correlations were found between the MAIAC time series and ground-estimated SGS (R2 = 0.36–0.8, which is remarkable since previous studies have found it difficult to observe inter-annual phenological variations in evergreen vegetation from satellite data. The considerably noisier NDVI product could not accurately predict SGS, and EGS could not be derived successfully from any of the time series. While the strongest relationship overall was found between SGS derived from the ground data and PRI, MAIAC NDVI exhibited high correlations with SGS more consistently (R2 > 0.6 in all cases. The results suggest that PRI can serve as an effective indicator of spring seasonal transitions, however, additional work is necessary to confirm the relationships observed and to further explore the usefulness of MODIS PRI for detecting phenology.

  8. Analysis of vegetation recovery surrounding a restored wetland using the normalized difference infrared index (NDII) and normalized difference vegetation index (NDVI)

    Science.gov (United States)

    Wilson, Natalie R.; Norman, Laura

    2018-01-01

    Watershed restoration efforts seek to rejuvenate vegetation, biological diversity, and land productivity at Cienega San Bernardino, an important wetland in southeastern Arizona and northern Sonora, Mexico. Rock detention and earthen berm structures were built on the Cienega San Bernardino over the course of four decades, beginning in 1984 and continuing to the present. Previous research findings show that restoration supports and even increases vegetation health despite ongoing drought conditions in this arid watershed. However, the extent of restoration impacts is still unknown despite qualitative observations of improvement in surrounding vegetation amount and vigor. We analyzed spatial and temporal trends in vegetation greenness and soil moisture by applying the normalized difference vegetation index (NDVI) and normalized difference infrared index (NDII) to one dry summer season Landsat path/row from 1984 to 2016. The study area was divided into zones and spectral data for each zone was analyzed and compared with precipitation record using statistical measures including linear regression, Mann– Kendall test, and linear correlation. NDVI and NDII performed differently due to the presence of continued grazing and the effects of grazing on canopy cover; NDVI was better able to track changes in vegetation in areas without grazing while NDII was better at tracking changes in areas with continued grazing. Restoration impacts display higher greenness and vegetation water content levels, greater increases in greenness and water content through time, and a decoupling of vegetation greenness and water content from spring precipitation when compared to control sites in nearby tributary and upland areas. Our results confirm the potential of erosion control structures to affect areas up to 5 km downstream of restoration sites over time and to affect 1 km upstream of the sites.

  9. Investigation on the Patterns of Global Vegetation Change Using a Satellite-Sensed Vegetation Index

    Directory of Open Access Journals (Sweden)

    Ainong Li

    2010-06-01

    Full Text Available The pattern of vegetation change in response to global change still remains a controversial issue. A Normalized Difference Vegetation Index (NDVI dataset compiled by the Global Inventory Modeling and Mapping Studies (GIMMS was used for analysis. For the period 1982–2006, GIMMS-NDVI analysis indicated that monthly NDVI changes show homogenous trends in middle and high latitude areas in the northern hemisphere and within, or near, the Tropic of Cancer and Capricorn; with obvious spatio-temporal heterogeneity on a global scale over the past two decades. The former areas featured increasing vegetation activity during growth seasons, and the latter areas experienced an even greater amplitude in places where precipitation is adequate. The discussion suggests that one should be cautious of using the NDVI time-series to analyze local vegetation dynamics because of its coarse resolution and uncertainties.

  10. Relative sensitivity of Normalized Difference Vegetation Index (NDVI) and Microwave Polarization Difference Index (MPDI) for vegetation and desertification monitoring

    Science.gov (United States)

    Becker, Francois; Choudhury, Bhaskar J.

    1988-01-01

    A simple equation relating the Microwave Polarization Difference Index (MPDI) and the Normalized Difference Vegetation Index (NDVI) is proposed which represents well data obtained from Nimbus 7/SMMR at 37 GHz and NOAA/AVHRR Channels 1 and 2. It is found that there is a limit which is characteristic of a particular type of cover for which both indices are equally sensitive to the variation of vegetation, and below which MPDI is more efficient than NDVI. The results provide insight into the relationship between water content and chlorophyll absorption at pixel size scales.

  11. Evaluation of vegetation cover using the normalized difference vegetation index (NDVI

    Directory of Open Access Journals (Sweden)

    Gabriela Camargos Lima

    2013-08-01

    Full Text Available Soil loss by water erosion is the main cause of soil degradation in Brazil. However, erosion can be reduced by the presence of vegetation. The Normalized Difference Vegetation Index (NDVI makes it possible to identify the vegetative vigor of crops or natural vegetation which facilities the identification of areas with vegetation covers. This information is very important in identifying the phenomena which might be occurring in a particular area, especially those related to soil degradation by water erosion. Thus, the aim of this work was to assess the canopy cover by using NDVI, checking the image accuracy using the Coverage Index (CI based on the Stocking method, in the Sub-basin of Posses, which belongs to the Cantareira System, located in the Extrema municipality, Minas Gerais, Brazil. Landsat-5 TM images were used. The sub-basin of Posses was very altered in comparison to the surrounding areas. The NDVI technique proved to be a suitable tool to assess the uses that occur in the sub-basin of Posses, as validated by the Stocking methodology. The map derived from NDVI allowed the geographic distribution of different land uses to be observed and allowed for the identification of critical areas in relation to vegetation cover as well. This finding can be used to optimize efforts to recover and protect soil in areas with bare soil and degraded pasture, in order to reduce environmental degradation. The CI has not exceeded 40% for land use classes that occur in the majority of the sub-basin (91%, except in areas of woody vegetation.

  12. [Correlation analysis on normalized difference vegetation index (NDVI) of different vegetations and climatic factors in Southwest China].

    Science.gov (United States)

    Zhang, Yuan-Dong; Zhang, Xiao-He; Liu, Shi-Rong

    2011-02-01

    Based on the 1982-2006 NDVI remote sensing data and meteorological data of Southwest China, and by using GIS technology, this paper interpolated and extracted the mean annual temperature, annual precipitation, and drought index in the region, and analyzed the correlations of the annual variation of NDVI in different vegetation types (marsh, shrub, bush, grassland, meadow, coniferous forest, broad-leaved forest, alpine vegetation, and cultural vegetation) with corresponding climatic factors. In 1982-2006, the NDVI, mean annual temperature, and annual precipitation had an overall increasing trend, and the drought index decreased. Particularly, the upward trend of mean annual temperature was statistically significant. Among the nine vegetation types, the NDVI of bush and mash decreased, and the downward trend was significant for bush. The NDVI of the other seven vegetation types increased, and the upward trend was significant for coniferous forest, meadow, and alpine vegetation, and extremely significant for shrub. The mean annual temperature in the areas with all the nine vegetation types increased significantly, while the annual precipitation had no significant change. The drought index in the areas with marsh, bush, and cultural vegetation presented an increasing trend, that in the areas with meadow and alpine vegetation decreased significantly, and this index in the areas with other four vegetation types had an unobvious decreasing trend. The NDVI of shrub and coniferous forest had a significantly positive correlation with mean annual temperature, and that of shrub and meadow had significantly negative correlation with drought index. Under the conditions of the other two climatic factors unchanged, the NDVI of coniferous forest, broad-leaved forest, and alpine vegetation showed the strongest correlation with mean annual temperature, that of grass showed the strongest correlation with annual precipitation, and the NDVI of mash, shrub, grass, meadow, and cultural

  13. Solar radiation measurements and Leaf Area Index (LAI) from vegetal covers

    International Nuclear Information System (INIS)

    Wandelli, E.V.; Marques Filho, A. de O.

    1999-01-01

    A method by which a physical model of the solar radiation transfer in a vegetal medium is inverted to estimate the leaf area index (LAI) for different types of vegetation is presented here, as an alternative to the destructive experiments, which are a hard task to implement on the vegetation covers. Radiation data were obtained during the dry season — 1996, at the Embrapa Experimental Station, (BR 174 - km 54, 2° 31' S, 60° 01' W), Manaus, Brazil. The method yielded convergent values for the LAI between different adopted radiation classes with more stable estimates at time when there is a predominant diffuse radiation. The application of the inversion algorithm yields the following values for the leaf area index and respective annual foliage increments: 3.5 (0.35 yr. -1 ) for the intact secondary forest; 2.0 (0.5 yr -1 ) for the palm agroforestry system; and 1.6 (0.4 yr -1 ) for the multi-layer ones [pt

  14. Estimating soil moisture from 6.6 GHz dual polarization, and/or satellite derived vegetation index

    International Nuclear Information System (INIS)

    Ahmed, N.U.

    1995-01-01

    Eight and a half years (January 1979 to August 1987) of Scanning Multichannel Microwave Radiometer (SMMR) data taken at a frequency of 6.6 GHz for both day and night observations at both polarizations were processed, documented and used to study the relationship between brightness temperature (T(B)) and antecedent precipitation index (API) in a wide range of vegetation index (normalized difference vegetation index (NDVI) varies from 0.2 to 0.6) in the mid-west and southern United States. In general, this study validates the model structure for soil wetness developed by Choudhury and Golus. For NDVI greater than 0.45 the resultant microwave signal is substantially affected by the vegetation. The night-time observations by both polarizations gave a better correlation between T(B) and API. The horizontal polarization is more sensitive to vegetation. For the least and greatest vegetated areas, night-time observations by vertical polarization showed less scatter in the T(B) versus API relation. A non-linear model was developed for soil wetness using horizontal and vertical polarization and their difference. The estimate of error for this model is better than previous models, and can be used to obtain six levels of soil moisture. (author)

  15. Pattern Decomposition Method and a New Vegetation Index for Hyper-Multispectral Satellite Data Analysis

    Science.gov (United States)

    Muramatsu, K.; Furumi, S.; Hayashi, A.; Shiono, Y.; Ono, A.; Fujiwara, N.; Daigo, M.; Ochiai, F.

    We have developed the ``pattern decomposition method'' based on linear spectral mixing of ground objects for n-dimensional satellite data. In this method, spectral response patterns for each pixel in an image are decomposed into three components using three standard spectral shape patterns determined from the image data. Applying this method to AMSS (Airborne Multi-Spectral Scanner) data, eighteen-dimensional data are successfully transformed into three-dimensional data. Using the three components, we have developed a new vegetation index in which all the multispectral data are reflected. We consider that the index should be linear to the amount of vegetation and vegetation vigor. To validate the index, its relations to vegetation types, vegetation cover ratio, and chlorophyll contents of a leaf were studied using spectral reflectance data measured in the field with a spectrometer. The index was sensitive to vegetation types and vegetation vigor. This method and index are very useful for assessment of vegetation vigor, classifying land cover types and monitoring vegetation changes

  16. Analysis of agricultural drought using vegetation temperature condition index (VTCI) from Terra/MODIS satellite data.

    Science.gov (United States)

    Patel, N R; Parida, B R; Venus, V; Saha, S K; Dadhwal, V K

    2012-12-01

    The most commonly used normalized difference vegetation index (NDVI) from remote sensing often fall short in real-time drought monitoring due to a lagged vegetation response to drought. Therefore, research recently emphasized on the use of combination of surface temperature and NDVI which provides vegetation and moisture conditions simultaneously. Since drought stress effects on agriculture are closely linked to actual evapotranspiration, we used a vegetation temperature condition index (VTCI) which is more closely related to crop water status and holds a key place in real-time drought monitoring and assessment. In this study, NDVI and land surface temperature (T (s)) from MODIS 8-day composite data during cloud-free period (September-October) were adopted to construct an NDVI-T (s) space, from which the VTCI was computed. The crop moisture index (based on estimates of potential evapotranspiration and soil moisture depletion) was calculated to represent soil moisture stress on weekly basis for 20 weather monitoring stations. Correlation and regression analysis were attempted to relate VTCI with crop moisture status and crop performance. VTCI was found to accurately access the degree and spatial extent of drought stress in all years (2000, 2002, and 2004). The temporal variation of VTCI also provides drought pattern changes over space and time. Results showed significant and positive relations between CMI (crop moisture index) and VTCI observed particularly during prominent drought periods which proved VTCI as an ideal index to monitor terminal drought at regional scale. VTCI had significant positive relationship with yield but weakly related to crop anomalies. Duration of terminal drought stress derived from VTCI has a significant negative relationship with yields of major grain and oilseeds crops, particularly, groundnut.

  17. Wheat Yield Forecasting for Punjab Province from Vegetation Index Time Series and Historic Crop Statistics

    Directory of Open Access Journals (Sweden)

    Jan Dempewolf

    2014-10-01

    Full Text Available Policy makers, government planners and agricultural market participants in Pakistan require accurate and timely information about wheat yield and production. Punjab Province is by far the most important wheat producing region in the country. The manual collection of field data and data processing for crop forecasting by the provincial government requires significant amounts of time before official reports can be released. Several studies have shown that wheat yield can be effectively forecast using satellite remote sensing data. In this study, we developed a methodology for estimating wheat yield and area for Punjab Province from freely available Landsat and MODIS satellite imagery approximately six weeks before harvest. Wheat yield was derived by regressing reported yield values against time series of four different peak-season MODIS-derived vegetation indices. We also tested deriving wheat area from the same MODIS time series using a regression-tree approach. Among the four evaluated indices, WDRVI provided more consistent and accurate yield forecasts compared to NDVI, EVI2 and saturation-adjusted normalized difference vegetation index (SANDVI. The lowest RMSE values at the district level for forecast versus reported yield were found when using six or more years of training data. Forecast yield for the 2007/2008 to 2012/2013 growing seasons were within 0.2% and 11.5% of final reported values. Absolute deviations of wheat area and production forecasts from reported values were slightly greater compared to using the previous year's or the three- or six-year moving average values, implying that 250-m MODIS data does not provide sufficient spatial resolution for providing improved wheat area and production forecasts.

  18. Vegetation Index, Lake Vegetation Index Regions.This layer describes the spatial extent of the North and South Lake Vegetation Index (LVI) biological regions, as described in Fore et al. 2007, Assessing the Biological Condition of Florida Lakes: Development of the Lake Veg, Published in 2008, 1:24000 (1in=2000ft) scale, Florida Department of Environmental Protection (FDEP).

    Data.gov (United States)

    NSGIC State | GIS Inventory — Vegetation Index dataset current as of 2008. Lake Vegetation Index Regions.This layer describes the spatial extent of the North and South Lake Vegetation Index (LVI)...

  19. Estimating foliar nitrogen in Eucalyptus using vegetation indexes

    Directory of Open Access Journals (Sweden)

    Luiz Felipe Ramalho de Oliveira

    Full Text Available ABSTRACT Nitrogen (N has commonly been applied in Eucalyptus stands in Brazil and it has a direct relation with biomass production and chlorophyll content. Foliar N concentrations are used to diagnose soil and plant fertility levels and to develop N fertilizer application rates. Normally, foliar N is obtained using destructive methods, but indirect analyses using Vegetation Indexes (VIs may be possible. The aim of this work was to evaluate VIs to estimate foliar N concentration in three Eucalyptus clones. Lower crown leaves of three clonal Eucalyptus plantations (25 months old were classified into five color patterns using the Munsell Plant Tissue Color Chart. For each color, N concentration was determined by the Kjeldahl method and foliar reflectance was measured using a CI-710 Miniature Leaf Spectrometer. Foliar reflectance data were used to obtain the VIs and the VIs were used to estimate N concentrations. In the visible region, the relationship between N concentration and reflectance percentage was negative. The highest correlations between VIs and N concentrations were obtained by the Inflection Point Position (IPP, r = 0.97, Normalized Difference Red-Edge (reNDVI, r = 0.97 and Modified Red-Edge Normalized Difference Vegetation Index (mNDI, r = 0.97. Vegetation indexes on the red edge region provided the most accurate estimates of foliar N concentration. The reNDVI index provided the best N concentration estimates in leaves of different colors of Eucalyptus urophylla × grandis and Eucalyptus urophylla × urophylla (R2 = 0.97 and RMSE = 0.91 g kg−1.

  20. A method for an accurate in-flight calibration of AVHRR data for vegetation index calculation

    OpenAIRE

    Asmami , Mbarek; Wald , Lucien

    1992-01-01

    International audience; A significant degradation in the Advanced Very High Resolution Radiometer (AVHRR) responsitivity, on the NOAA satellite series, has occurred since the prelaunch calibration and with time since launch. This affects the index vegetation (NDVI), which is an important source of information for monitoring vegetation conditions on regional and global scales. Many studies have been carried out which use the Viewing Earth calibration approach in order to provide accurate calib...

  1. Vegetation index analysis of multi-source remote sensing data in coal mine wasteland

    Energy Technology Data Exchange (ETDEWEB)

    Han, Y.X.; Li, M.Z.; Li, D.L. [China Agricultural University, Beijing (China)

    2007-12-15

    Thirty-six soil samples were collected and their hyperspectral data used to calculate vegetation indices such as a normalised difference vegetation index (NDVI) and a difference vegetation index (DVI). These were evaluated for typical surface object features within the wastelands around Haizhou Opencast Coal Mine in Fuxin city. A principal component analysis to the hyperspectral data was performed, and the result showed that the first and the second principal components satisfactorily accounted for the multi-spectral image information. The panchromatic and multi-spectral images of SPOT5 were then merged. The panchromatic image replaced the first principal component to improve spatial resolution of the image. In addition, the multispectral images and the NDVI image were classified into six types using the unsupervised classification method. The linear quantitative models were built up and the highest correlation coefficients were obtained between the hyperspectral vegetation index and the vegetation index data from the SPOT5 image. The results show that the hyperspectral data and remote sensing images can be used for quantitative estimation of soil nutrients in coal mine wasteland. They can also provide large area surface information for fast and effective decision making regarding revegetation and the monitoring of dynamic change.

  2. Vegetation Index and Phenology (VIP) Vegetation Indices Monthly Global 0.05Deg CMG V004

    Data.gov (United States)

    National Aeronautics and Space Administration — The NASA Making Earth System Data Records for Use in Research Environments (MEaSUREs) Vegetation Index and Phenology (VIP) global datasets were created using...

  3. Multi-index time series monitoring of drought and fire effects on desert grasslands

    Science.gov (United States)

    Villarreal, Miguel; Norman, Laura M.; Buckley, Steven; Wallace, Cynthia S.A.; Coe, Michelle A.

    2016-01-01

    The Western United States is expected to undergo both extended periods of drought and longer wildfire seasons under forecasted global climate change and it is important to understand how these disturbances will interact and affect recovery and composition of plant communities in the future. In this research paper we describe the temporal response of grassland communities to drought and fire in southern Arizona, where land managers are using repeated, prescribed fire as a habitat restoration tool. Using a 25-year atlas of fire locations, we paired sites with multiple fires to unburned control areas and compare satellite and field-based estimates of vegetation cover over time. Two hundred and fifty Landsat TM images, dating from 1985–2011, were used to derive estimates of Total Vegetation Fractional Cover (TVFC) of live and senescent grass using the Soil-Adjusted Total Vegetation Index (SATVI) and post-fire vegetation greenness using the Normalized Difference Vegetation Index (NDVI). We also implemented a Greenness to Cover Index that is the difference of time-standardized SATVI-TVFC and NDVI values at a given time and location to identify post-fire shifts in native, non-native, and annual plant cover. The results highlight anomalous greening and browning during drought periods related to amounts of annual and non-native plant cover present. Results suggest that aggressive application of prescribed fire may encourage spread of non-native perennial grasses and annual plants, particularly during droughts.

  4. A survey of drought and Variation of Vegetation by statistical indexes and remote sensing (Case study: Jahad forest in Bandar Abbas)

    International Nuclear Information System (INIS)

    Tamassoki, E; Soleymani, Z; Bahrami, F; Abbasgharemani, H

    2014-01-01

    The damages of drought as a climatic and creeping phenomenon are very enormous specially in deserts. Necessity of management and conflict with it is clear. In this case vegetation are damaged too, and even are changed faster. This paper describes the process of vegetation changes and surveys it with drought indexes such as statistical and remote sensing indexes and correlation between temperature and relative humidity by Geographical Information System (GIS) and Remote Sensing (RS) in forest park of Bandar Abbas in successive years. At the end the regression and determination-coefficient for showing the importance of droughts survey are computed. Results revealed that the correlation between vegetation and indexes was 0.5. The humidity had maximum correlation and when we close to 2009 the period of droughts increase and time intervals decrease that influence vegetation enormously and cause the more area lost its vegetation

  5. Vegetation Index and Phenology (VIP) Vegetation Indices 7Days Global 0.05Deg CMG V004

    Data.gov (United States)

    National Aeronautics and Space Administration — The NASA Making Earth System Data Records for Use in Research Environments (MEaSUREs) Vegetation Index and Phenology (VIP) global datasets were created using...

  6. Mapping agroecological zones and time lag in vegetation growth by means of Fourier analysis of time series of NDVI images

    Science.gov (United States)

    Menenti, M.; Azzali, S.; Verhoef, W.; Van Swol, R.

    1993-01-01

    Examples are presented of applications of a fast Fourier transform algorithm to analyze time series of images of Normalized Difference Vegetation Index values. The results obtained for a case study on Zambia indicated that differences in vegetation development among map units of an existing agroclimatic map were not significant, while reliable differences were observed among the map units obtained using the Fourier analysis.

  7. The Global Index of Vegetation-Plot Databases 1 (GIVD): a new resource for vegetation science

    NARCIS (Netherlands)

    Dengler, J.; Jansen, F.; Glockler, F.; Schaminee, J.H.J.

    2011-01-01

    Question: How many vegetation plot observations (relevés) are available in electronic databases, how are they geographically distributed, what are their properties and how might they be discovered and located for research and application? Location: Global. Methods: We compiled the Global Index of

  8. A special vegetation index for the weed detection in sensor based precision agriculture.

    Science.gov (United States)

    Langner, Hans-R; Böttger, Hartmut; Schmidt, Helmut

    2006-06-01

    Many technologies in precision agriculture (PA) require image analysis and image- processing with weed and background differentiations. The detection of weeds on mulched cropland is one important image-processing task for sensor based precision herbicide applications. The article introduces a special vegetation index, the Difference Index with Red Threshold (DIRT), for the weed detection on mulched croplands. Experimental investigations in weed detection on mulched areas point out that the DIRT performs better than the Normalized Difference Vegetation Index (NDVI). The result of the evaluation with four different decision criteria indicate, that the new DIRT gives the highest reliability in weed/background differentiation on mulched areas. While using the same spectral bands (infrared and red) as the NDVI, the new DIRT is more suitable for weed detection than the other vegetation indices and requires only a small amount of additional calculation power. The new vegetation index DIRT was tested on mulched areas during automatic ratings with a special weed camera system. The test results compare the new DIRT and three other decision criteria: the difference between infrared and red intensity (Diff), the soil-adjusted quotient between infrared and red intensity (Quotient) and the NDVI. The decision criteria were compared with the definition of a worse case decision quality parameter Q, suitable for mulched croplands. Although this new index DIRT needs further testing, the index seems to be a good decision criterion for the weed detection on mulched areas and should also be useful for other image processing applications in precision agriculture. The weed detection hardware and the PC program for the weed image processing were developed with funds from the German Federal Ministry of Education and Research (BMBF).

  9. Shelter Index and a simple wind speed parameter to characterize vegetation control of sand transport threshold and Flu

    Science.gov (United States)

    Gillies, J. A.; Nield, J. M.; Nickling, W. G.; Furtak-Cole, E.

    2014-12-01

    Wind erosion and dust emissions occur in many dryland environments from a range of surfaces with different types and amounts of vegetation. Understanding how vegetation modulates these processes remains a research challenge. Here we present results from a study that examines the relationship between an index of shelter (SI=distance from a point to the nearest upwind vegetation/vegetation height) and particle threshold expressed as the ratio of wind speed measured at 0.45 times the mean plant height divided by the wind speed at 17 m when saltation commences, and saltation flux. The results are used to evaluate SI as a parameter to characterize the influence of vegetation on local winds and sediment transport conditions. Wind speed, wind direction, saltation activity and point saltation flux were measured at 35 locations in defined test areas (~13,000 m2) in two vegetation communities: mature streets of mesquite covered nebkhas and incipient nebkhas dominated by low mesquite plants. Measurement positions represent the most open areas, and hence those places most susceptible to wind erosion among the vegetation elements. Shelter index was calculated for each measurement position for each 10° wind direction bin using digital elevation models for each site acquired using terrestrial laser scanning. SI can show the susceptibility to wind erosion at different time scales, i.e., event, seasonal, or annual, but in a supply-limited system it can fail to define actual flux amounts due to a lack of knowledge of the distribution of sediment across the surface of interest with respect to the patterns of SI.

  10. A temperature and vegetation adjusted NTL urban index for urban area mapping and analysis

    Science.gov (United States)

    Zhang, Xiya; Li, Peijun

    2018-01-01

    Accurate and timely information regarding the extent and spatial distribution of urban areas on regional and global scales is crucially important for both scientific and policy-making communities. Stable nighttime light (NTL) data from the Defense Meteorological Satellite Program (DMSP) Operational Linescan System (OLS) provides a unique proxy of human settlement and activity, which has been used in the mapping and analysis of urban areas and urbanization dynamics. However, blooming and saturation effects of DMSP/OLS NTL data are two unresolved problems in regional urban area mapping and analysis. This study proposed a new urban index termed the Temperature and Vegetation Adjusted NTL Urban Index (TVANUI). It is intended to reduce blooming and saturation effects and to enhance urban features by combining DMSP/OLS NTL data with Normalized Difference Vegetation Index (NDVI) and land surface temperature (LST) data from the Moderate Resolution Imaging Spectroradiometer onboard the Terra satellite. The proposed index was evaluated in two study areas by comparison with established urban indices. The results demonstrated the proposed TVANUI was effective in enhancing the variation of DMSP/OLS light in urban areas and in reducing blooming and saturation effects, showing better performance than three established urban indices. The TVANUI also significantly outperformed the established urban indices in urban area mapping using both the global-fixed threshold and the local-optimal threshold methods. Thus, the proposed TVANUI provides a useful variable for urban area mapping and analysis on regional scale, as well as for urbanization dynamics using time-series DMSP/OLS and related satellite data.

  11. Estimating fractional vegetation cover and the vegetation index of bare soil and highly dense vegetation with a physically based method

    Science.gov (United States)

    Song, Wanjuan; Mu, Xihan; Ruan, Gaiyan; Gao, Zhan; Li, Linyuan; Yan, Guangjian

    2017-06-01

    Normalized difference vegetation index (NDVI) of highly dense vegetation (NDVIv) and bare soil (NDVIs), identified as the key parameters for Fractional Vegetation Cover (FVC) estimation, are usually obtained with empirical statistical methods However, it is often difficult to obtain reasonable values of NDVIv and NDVIs at a coarse resolution (e.g., 1 km), or in arid, semiarid, and evergreen areas. The uncertainty of estimated NDVIs and NDVIv can cause substantial errors in FVC estimations when a simple linear mixture model is used. To address this problem, this paper proposes a physically based method. The leaf area index (LAI) and directional NDVI are introduced in a gap fraction model and a linear mixture model for FVC estimation to calculate NDVIv and NDVIs. The model incorporates the Moderate Resolution Imaging Spectroradiometer (MODIS) Bidirectional Reflectance Distribution Function (BRDF) model parameters product (MCD43B1) and LAI product, which are convenient to acquire. Two types of evaluation experiments are designed 1) with data simulated by a canopy radiative transfer model and 2) with satellite observations. The root-mean-square deviation (RMSD) for simulated data is less than 0.117, depending on the type of noise added on the data. In the real data experiment, the RMSD for cropland is 0.127, for grassland is 0.075, and for forest is 0.107. The experimental areas respectively lack fully vegetated and non-vegetated pixels at 1 km resolution. Consequently, a relatively large uncertainty is found while using the statistical methods and the RMSD ranges from 0.110 to 0.363 based on the real data. The proposed method is convenient to produce NDVIv and NDVIs maps for FVC estimation on regional and global scales.

  12. A Phenology-Based Method for Monitoring Woody and Herbaceous Vegetation in Mediterranean Forests from NDVI Time Series

    Directory of Open Access Journals (Sweden)

    David Helman

    2015-09-01

    Full Text Available We present an efficient method for monitoring woody (i.e., evergreen and herbaceous (i.e., ephemeral vegetation in Mediterranean forests at a sub pixel scale from Normalized Difference Vegetation Index (NDVI time series derived from the Moderate Resolution Imaging Spectroradiometer (MODIS. The method is based on the distinct development periods of those vegetation components. In the dry season, herbaceous vegetation is absent or completely dry in Mediterranean forests. Thus the mean NDVI in the dry season was attributed to the woody vegetation (NDVIW. A constant NDVI value was assumed for soil background during this period. In the wet season, changes in NDVI were attributed to the development of ephemeral herbaceous vegetation in the forest floor and its maximum value to the peak green cover (NDVIH. NDVIW and NDVIH agreed well with field estimates of leaf area index and fraction of vegetation cover in two differently structured Mediterranean forests. To further assess the method’s assumptions, understory NDVI was retrieved form MODIS Bidirectional Reflectance Distribution Function (BRDF data and compared with NDVIH. After calibration, leaf area index and woody and herbaceous vegetation covers were assessed for those forests. Applicability for pre- and post-fire monitoring is presented as a potential use of this method for forest management in Mediterranean-climate regions.

  13. A Phenology-Based Method for Monitoring Woody and Herbaceous Vegetation in Mediterranean Forests from NDVI Time Series

    OpenAIRE

    David Helman; Itamar M. Lensky; Naama Tessler; Yagil Osem

    2015-01-01

    We present an efficient method for monitoring woody (i.e., evergreen) and herbaceous (i.e., ephemeral) vegetation in Mediterranean forests at a sub pixel scale from Normalized Difference Vegetation Index (NDVI) time series derived from the Moderate Resolution Imaging Spectroradiometer (MODIS). The method is based on the distinct development periods of those vegetation components. In the dry season, herbaceous vegetation is absent or completely dry in Mediterranean forests. Thus the mean NDVI ...

  14. Normalized difference vegetation index (NDVI) variation among cultivars and environments

    Science.gov (United States)

    Although Nitrogen (N) is an essential nutrient for crop production, large preplant applications of fertilizer N can result in off-field loss that causes environmental concerns. Canopy reflectance is being investigated for use in variable rate (VR) N management. Normalized difference vegetation index...

  15. Development of a New BRDF-Resistant Vegetation Index for Improving the Estimation of Leaf Area Index

    Directory of Open Access Journals (Sweden)

    Su Zhang

    2016-11-01

    Full Text Available The leaf area index (LAI is one of the most important Earth surface parameters used in the modeling of ecosystems and their interaction with climate. Numerous vegetation indices have been developed to estimate the LAI. However, because of the effects of the bi-directional reflectance distribution function (BRDF, most of these vegetation indices are also sensitive to the effect of BRDF. In this study, we aim to present a new BRDF-resistant vegetation index (BRVI, which is sensitive to the LAI but insensitive to the effect of BRDF. Firstly, the BRDF effects of different bands were investigated using both simulated data and in-situ measurements of winter wheat made at different growth stages. We found bi-directional shape similarity in the solar principal plane between the green and the near-infrared (NIR bands and between the blue and red bands for farmland soil conditions and with medium chlorophyll content level. Secondly, the consistency of the shape of the BRDF across different bands was employed to develop a new BRDF-resistant vegetation index for estimating the LAI. The reflectance ratios of the NIR band to the green band and the blue band to the red band were reasonably assumed to be resistant to the BRDF effects. Nevertheless, the variation amplitude of the bi-directional reflectance in the solar principal plane was different for different bands. The divisors in the two reflectance ratios were improved by combining the reflectances at the red and green bands. The new BRVI was defined as a normalized combination of the two improved reflectance ratios. Finally, the potential of the proposed BRVI for estimation of the LAI was evaluated using both simulated data and in-situ measurements and also compared to other popular vegetation indices. The results showed that the influence of the BRDF on the BRVI was the weakest and that the BRVI retrieved LAI values well, with a coefficient of determination (R2 of 0.84 and an RMSE of 0.83 for the field

  16. A Candidate Vegetation Index of Biological Integrity Based on Species Dominance and Habitat Fidelity

    Science.gov (United States)

    Gara, Brian D; Stapanian, Martin A.

    2015-01-01

    Indices of biological integrity of wetlands based on vascular plants (VIBIs) have been developed in many areas of the USA and are used in some states to make critical management decisions. An underlying concept of all VIBIs is that they respond negatively to disturbance. The Ohio VIBI (OVIBI) is calculated from 10 metrics, which are different for each wetland vegetation class. We present a candidate vegetation index of biotic integrity based on floristic quality (VIBI-FQ) that requires only two metrics to calculate an overall score regardless of vegetation class. These metrics focus equally on the critical ecosystem elements of diversity and dominance as related to a species’ degree of fidelity to habitat requirements. The indices were highly correlated but varied among vegetation classes. Both indices responded negatively with a published index of wetland disturbance in 261 Ohio wetlands. Unlike VIBI-FQ, however, errors in classifying wetland vegetation may lead to errors in calculating OVIBI scores. This is especially critical when assessing the ecological condition of rapidly developing ecosystems typically associated with wetland restoration and creation projects. Compared to OVIBI, the VIBI-FQ requires less field work, is much simpler to calculate and interpret, and can potentially be applied to all habitat types. This candidate index, which has been “standardized” across habitats, would make it easier to prioritize funding because it would score the “best” and “worst” of all habitats appropriately and allow for objective comparison across different vegetation classes.

  17. Vegetation index anomaly response to varying lengths of drought across vegetation and climatic gradients in Hawaii

    Science.gov (United States)

    Lucas, M.; Miura, T.; Trauernicht, C.; Frazier, A. G.

    2017-12-01

    A drought which results in prolonged and extended deficit in naturally available water supply and creates multiple stresses across ecosystems is classified as an ecological drought. Detecting and understanding the dynamics and response of such droughts in tropical systems, specifically across various vegetation and climatic gradients is fairly undetermined, yet increasingly important for better understandings of the ecological effects of drought. To understanding the link between what lengths and intensities of known meteorological drought triggers detectable ecological vegetation responses, a landscape scale regression analysis evaluating the response (slope) and relationship strength (R-squared) of several cumulative SPI (standard precipitation index) lengths(1, 3, 6, 12, 18, 24, 36, 48, and 60 month), to various satellite derived monthly vegetation indices anomalies (NDVI, EVI, EVI2, and LSWI) was performed across a matrix of dominant vegetation covers (grassland, shrubland, and forest) and climatic moisture zones (arid, dry, mesic, and wet). The nine different SPI lags across these climactic and vegetation gradients was suggest that stronger relationships and steeper slopes were found in dryer climates (across all vegetation covers) and finer vegetation types (across all moisture zones). Overall NDVI, EVI and EVI2 showed the best utility in these dryer climatic zones across all vegetation types. Within arid and dry areas "best" fits showed increasing lengths of cumulative SPI were with increasing vegetation coarseness respectively. Overall these findings suggest that rainfall driven drought may have a stronger impact on the ecological condition of vegetation in water limited systems with finer vegetation types ecologically responding more rapidly to meteorological drought events than coarser woody vegetation systems. These results suggest that previously and newly documented trends of decreasing rainfall and increasing drought in Hawaiian drylands may have

  18. Remotely Assessing Fraction of Photosynthetically Active Radiation (FPAR for Wheat Canopies Based on Hyperspectral Vegetation Indexes

    Directory of Open Access Journals (Sweden)

    Changwei Tan

    2018-06-01

    Full Text Available Fraction of photosynthetically active radiation (FPAR, as an important index for evaluating yields and biomass production, is key to providing the guidance for crop management. However, the shortage of good hyperspectral data can frequently result in the hindrance of accurate and reliable FPAR assessment, especially for wheat. In the present research, aiming at developing a strategy for accurate FPAR assessment, the relationships between wheat canopy FPAR and vegetation indexes derived from concurrent ground-measured hyperspectral data were explored. FPAR revealed the most strongly correlation with normalized difference index (NDI, and scaled difference index (N*. Both NDI and N* revealed the increase as the increase of FPAR; however, NDI value presented the stagnation as FPAR value beyond 0.70. On the other hand, N* showed a decreasing tendency when FPAR value was higher than 0.70. This special relationship between FPAR and vegetation index could be employed to establish a piecewise FPAR assessment model with NDI as a regression variable during FPAR value lower than 0.70, or N* as the regression variable during FPAR value higher than 0.70. The model revealed higher assessment accuracy up to 16% when compared with FPAR assessment models based on a single vegetation index. In summary, it is feasible to apply NDI and N* for accomplishing wheat canopy FPAR assessment, and establish an FPAR assessment model to overcome the limitations from vegetation index saturation under the condition with high FPAR value.

  19. Relationships between the normalised difference vegetation index and temperature fluctuations in post-mining sites

    Czech Academy of Sciences Publication Activity Database

    Bujalský, L.; Jirka, V.; Zemek, František; Frouz, J.

    2018-01-01

    Roč. 32, č. 4 (2018), s. 254-263 ISSN 1748-0930 R&D Projects: GA MŠk(CZ) LO1415 Institutional support: RVO:67179843 Keywords : temperature * normalised difference * vegetation index (NDVI) * vegetation cover * remote sensing Subject RIV: DF - Soil Science Impact factor: 1.078, year: 2016

  20. Radiative transfer in shrub savanna sites in Niger: preliminary results from HAPEX-Sahel. 3. Optical dynamics and vegetation index sensitivity to biomass and plant cover

    International Nuclear Information System (INIS)

    Leeuwen, W.J.D. van; Huete, A.R.; Duncan, J.; Franklin, J.

    1994-01-01

    A shrub savannah landscape in Niger was optically characterized utilizing blue, green, red and near-infrared wavelengths. Selected vegetation indices were evaluated for their performance and sensitivity to describe the complex Sahelian soil/vegetation canopies. Bidirectional reflectance factors (BRF) of plants and soils were measured at several view angles, and used as input to various vegetation indices. Both soil and vegetation targets had strong anisotropic reflectance properties, rendering all vegetation index (VI) responses to be a direct function of sun and view geometry. Soil background influences were shown to alter the response of most vegetation indices. N-space greenness had the smallest dynamic range in VI response, but the n-space brightness index provided additional useful information. The global environmental monitoring index (GEMI) showed a large VI dynamic range for bare soils, which was undesirable for a vegetation index. The view angle response of the normalized difference vegetation index (NDVI), atmosphere resistant vegetation index (ARVI) and soil atmosphere resistant vegetation index (SARVI) were asymmetric about nadir for multiple view angles, and were, except for the SARVI, altered seriously by soil moisture and/or soil brightness effects. The soil adjusted vegetation index (SAVI) was least affected by surface soil moisture and was symmetric about nadir for grass vegetation covers. Overall the SAVI, SARVI and the n-space vegetation index performed best under all adverse conditions and were recommended to monitor vegetation growth in the sparsely vegetated Sahelian zone. (author)

  1. Sugarcane leaf area estimate obtained from the corrected Normalized Difference Vegetation Index (NDVI

    Directory of Open Access Journals (Sweden)

    Rodrigo Moura Pereira

    2016-06-01

    Full Text Available Large farmland areas and the knowledge on the interaction between solar radiation and vegetation canopies have increased the use of data from orbital remote sensors in sugarcane monitoring. However, the constituents of the atmosphere affect the reflectance values obtained by imaging sensors. This study aimed at improving a sugarcane Leaf Area Index (LAI estimation model, concerning the Normalized Difference Vegetation Index (NDVI subjected to atmospheric correction. The model generated by the NDVI with atmospheric correction showed the best results (R2 = 0.84; d = 0.95; MAE = 0.44; RMSE = 0.55, in relation to the other models compared. LAI estimation with this model, during the sugarcane plant cycle, reached a maximum of 4.8 at the vegetative growth phase and 2.3 at the end of the maturation phase. Thus, the use of atmospheric correction to estimate the sugarcane LAI is recommended, since this procedure increases the correlations between the LAI estimated by image and by plant parameters.

  2. Growing Degree Vegetation Production Index (GDVPI): A Novel and Data-Driven Approach to Delimit Season Cycles

    Science.gov (United States)

    Graham, W. D.; Spruce, J.; Ross, K. W.; Gasser, J.; Grulke, N.

    2014-12-01

    Growing Degree Vegetation Production Index (GDVPI) is a parametric approach to delimiting vegetation seasonal growth and decline cycles using incremental growing degree days (GDD), and NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) normalized difference vegetation index (NDVI) 8-day composite cumulative integral data. We obtain a specific location's daily minimum and maximum temperatures from the nearest National Oceanic and Atmospheric Administration (NOAA) weather stations posted on the National Climate Data Center (NCDC) Climate Data Online (CDO) archive and compute GDD. The date range for this study is January 1, 2000 through December 31, 2012. We employ a novel process, a repeating logistic product (RLP), to compensate for short-term weather variability and data drops from the recording stations and fit a curve to the median daily GDD values, adjusting for asymmetry, amplitude, and phase shift that minimize the sum of squared errors when comparing the observed and predicted GDD. The resulting curve, here referred to as the surrogate GDD, is the time-temperature phasing parameter used to convert Cartesian NDVI values into polar coordinate pairs, multiplying the NDVI values as the radial by the cosine and sine of the surrogate GDD as the angular. Depending on the vegetation type and the original NDVI curve, the polar NDVI curve may be nearly circular, kidney-shaped, or pear-shaped in the case of conifers, deciduous, or agriculture, respectively. We examine the points of tangency about the polar coordinate NDVI curve, identifying values of 1, 0, -1, or infinity, as each of these represent natural inflection points. Lines connecting the origin to each tangent point illustrate and quantify the parametrically segmentation of the growing season based on the GDD and NDVI ostensible dependency. Furthermore, the area contained by each segment represents the apparent vegetation production. A particular benefit is that the inflection points are determined

  3. Monitoring of vegetation dynamics and assessing vegetation response to drought in the Iberian Peninsula

    Energy Technology Data Exchange (ETDEWEB)

    Garcia-Haro, F. J.; Moreno, A.; Perez-Hoyos, A.; Gilabert, M. A.; Melia, J.; Belda, F.; Poquet, D.; Martinez, B.; Verger, A.

    2009-07-01

    Monitoring the vegetation activity over long time-scales is necessary to discern ecosystem response to climate variability. Spatial and temporally consistent estimates of the biophysical variables such as fractional vegetation cover (FVC) and leaf area index (LAI) have been obtained in the context of DULCINEA Project. We used long-term monthly climate statistics to build simple climatic indices (SPI, moisture index) at different time scales. From these indices, we estimated that the climatic disturbances affected both the growing season and the total amount of vegetation. This implies that the anomaly of vegetation cover is a good indicator of moisture condition and can be an important data source when used for detecting an monitoring drought in the Iberian Peninsula. The impact of climate variability on the vegetation dynamics has shown not to be the same for every region. We concluded that the relationships between vegetation anomaly and moisture availability are significant for the arid and semiarid areas. (Author) 6 refs.

  4. Monitoring of vegetation dynamics and assessing vegetation response to drought in the Iberian Peninsula

    International Nuclear Information System (INIS)

    Garcia-Haro, F. J.; Moreno, A.; Perez-Hoyos, A.; Gilabert, M. A.; Melia, J.; Belda, F.; Poquet, D.; Martinez, B.; Verger, A.

    2009-01-01

    Monitoring the vegetation activity over long time-scales is necessary to discern ecosystem response to climate variability. Spatial and temporally consistent estimates of the biophysical variables such as fractional vegetation cover (FVC) and leaf area index (LAI) have been obtained in the context of DULCINEA Project. We used long-term monthly climate statistics to build simple climatic indices (SPI, moisture index) at different time scales. From these indices, we estimated that the climatic disturbances affected both the growing season and the total amount of vegetation. This implies that the anomaly of vegetation cover is a good indicator of moisture condition and can be an important data source when used for detecting an monitoring drought in the Iberian Peninsula. The impact of climate variability on the vegetation dynamics has shown not to be the same for every region. We concluded that the relationships between vegetation anomaly and moisture availability are significant for the arid and semiarid areas. (Author) 6 refs.

  5. Chlorophyll fluorescence, photochemical reflective index and normalized difference vegetative index during plant senescence.

    Science.gov (United States)

    Cordon, Gabriela; Lagorio, M Gabriela; Paruelo, José M

    2016-07-20

    The relationship between the Photochemical Reflectance Index (PRI), Normalized Difference Vegetation Index (NDVI) and chlorophyll fluorescence along senescence was investigated in this work. Reflectance and radiance measurements were performed at canopy level in grass species presenting different photosynthetic metabolism: Avena sativa (C3) and Setaria italica (C4), at different stages of the natural senescence process. Sun induced-chlorophyll fluorescence at 760nm (SIF 760 ) and the apparent fluorescence yield (SIF 760 /a, with a=irradiance at time of measurement) were extracted from the radiance spectra of canopies using the Fraunhofer Line Discrimination-method. The photosynthetic parameters derived from Kautsky kinetics and pigment content were also calculated at leaf level. Whilst stand level NDVI patterns were related to changes in the structure of canopies and not in pigment content, stand level PRI patterns suggested changes both in terms of canopy and of pigment content in leaves. Both SIF 760 /a and Φ PSII decreased progressively along senescence in both species. A strong increment in NPQ was evident in A. sativa while in S. italica NPQ values were lower. Our most important finding was that two chlorophyll fluorescence signals, Φ PSII and SIF 760 /a, correlated with the canopy PRI values in the two grasses assessed, even when tissues at different ontogenic stages were present. Even though significant changes occurred in the Total Chlr/Car ratio along senescence in both studied species, significant correlations between PRI and chlorophyll fluorescence signals might indicate the usefulness of this reflectance index as a proxy of photosynthetic RUE, at least under the conditions of this study. The relationships between stand level PRI and the fluorescence estimators (Φ PSII and SIF 760 /a) were positive in both cases. Therefore, an increase in PRI values as in the fluorescence parameters would indicate higher RUE. Copyright © 2016 Elsevier GmbH. All

  6. Normalized difference vegetation index (NDVI) in the management of mountain meadows

    Czech Academy of Sciences Publication Activity Database

    Mašková, Z.; Zemek, František; Květ, Jan

    2008-01-01

    Roč. 13, - (2008), s. 417-432 ISSN 1239-6095 R&D Projects: GA ČR(CZ) GA206/99/1410 Institutional research plan: CEZ:AV0Z60870520 Keywords : normalized difference vegetation index * mountain medows * mulching Subject RIV: EH - Ecology, Behaviour Impact factor: 1.620, year: 2008 www.borenv.net

  7. NOAA Climate Data Record (CDR) of Normalized Difference Vegetation Index (NDVI), Version 4

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset contains gridded daily Normalized Difference Vegetation Index (NDVI) derived from the NOAA Climate Data Record (CDR) of Advanced Very High Resolution...

  8. Early drought detection by spectral analysis of satellite time series of precipitation and Normalized Difference Vegetation Index (NDVI)

    NARCIS (Netherlands)

    Van Hoek, Mattijn; Jia, Li; Zhou, J.; Zheng, Chaolei; Menenti, M.

    2016-01-01

    The time lag between anomalies in precipitation and vegetation activity plays a critical role in early drought detection as agricultural droughts are caused by precipitation shortages. The aim of this study is to explore a new approach to estimate the time lag between a forcing (precipitation)

  9. Metrics for determining hydrophytic vegetation in wetland delineation: a clarification on the prevalence index

    Science.gov (United States)

    Diane De Steven

    2015-01-01

    A recent publication and an article in Wetland Science & Practice (Lichvar and Gillrich 2014b, 2014a) discuss two metrics for determining if vegetation is hydrophytic for purposes of U.S. wetland delineations, the Prevalence Index (PI) and a proposed Hydrophytic Cover Index (HCI). Based on Wentworth et al. (1988), the PI is a weighted average of ordinal scores (1-5...

  10. Calibration of UAS imagery inside and outside of shadows for improved vegetation index computation

    Science.gov (United States)

    Bondi, Elizabeth; Salvaggio, Carl; Montanaro, Matthew; Gerace, Aaron D.

    2016-05-01

    Vegetation health and vigor can be assessed with data from multi- and hyperspectral airborne and satellite- borne sensors using index products such as the normalized difference vegetation index (NDVI). Recent advances in unmanned aerial systems (UAS) technology have created the opportunity to access these same image data sets in a more cost effective manner with higher temporal and spatial resolution. Another advantage of these systems includes the ability to gather data in almost any weather condition, including complete cloud cover, when data has not been available before from traditional platforms. The ability to collect in these varied conditions, meteorological and temporal, will present researchers and producers with many new challenges. Particularly, cloud shadows and self-shadowing by vegetation must be taken into consideration in imagery collected from UAS platforms to avoid variation in NDVI due to changes in illumination within a single scene, and between collection flights. A workflow is presented to compensate for variations in vegetation indices due to shadows and variation in illumination levels in high resolution imagery collected from UAS platforms. Other calibration methods that producers may currently be utilizing produce NDVI products that still contain shadow boundaries and variations due to illumination, whereas the final NDVI mosaic from this workflow does not.

  11. Estimating Leaf Area Index for an arid region using Spectral Data ...

    African Journals Online (AJOL)

    In this study, spectral reflectance of pearl millet was computed at various wavelengths and at different times during the cropping season, using a spectroradiometer. Three main indices (Normalised Difference Vegetation Index, Ratio Vegetation Index, and Perpendicular Vegetation Index)were derived from the spectral data.

  12. Assessing Sahelian vegetation and stress from seasonal time series of polar orbiting and geostationary satellite imagery

    DEFF Research Database (Denmark)

    Olsen, Jørgen Lundegaard

    that short term variations in anomalies from seasonally detrended time series of indices could carry information on vegetation stress was examined and confirmed. However, it was not found sufficiently robust on pixel level to be implemented for monitoring vegetation water stress on a per-pixel basis...... provide good sensitivity to canopy water content, which can make vegetation stress detection possible. Furthermore, the high frequency observations in the optical spectrum now available from geostationary instruments have the potential for detection of changes in vegetation related surface properties...... on short timescales, which are challenging from polar orbiting instruments. Geostationary NDVI and the NIR and SWIR based Shortwave Infrared Water Stress Index (SIWSI) indices are compared with extensive field data from the Dahra site, supplemented by data from the Agoufou and Demokeya sites. The indices...

  13. Development of indicators of vegetation recovery based on time series analysis of SPOT Vegetation data

    Science.gov (United States)

    Lhermitte, S.; Tips, M.; Verbesselt, J.; Jonckheere, I.; Van Aardt, J.; Coppin, Pol

    2005-10-01

    Large-scale wild fires have direct impacts on natural ecosystems and play a major role in the vegetation ecology and carbon budget. Accurate methods for describing post-fire development of vegetation are therefore essential for the understanding and monitoring of terrestrial ecosystems. Time series analysis of satellite imagery offers the potential to quantify these parameters with spatial and temporal accuracy. Current research focuses on the potential of time series analysis of SPOT Vegetation S10 data (1999-2001) to quantify the vegetation recovery of large-scale burns detected in the framework of GBA2000. The objective of this study was to provide quantitative estimates of the spatio-temporal variation of vegetation recovery based on remote sensing indicators. Southern Africa was used as a pilot study area, given the availability of ground and satellite data. An automated technique was developed to extract consistent indicators of vegetation recovery from the SPOT-VGT time series. Reference areas were used to quantify the vegetation regrowth by means of Regeneration Indices (RI). Two kinds of recovery indicators (time and value- based) were tested for RI's of NDVI, SR, SAVI, NDWI, and pure band information. The effects of vegetation structure and temporal fire regime features on the recovery indicators were subsequently analyzed. Statistical analyses were conducted to assess whether the recovery indicators were different for different vegetation types and dependent on timing of the burning season. Results highlighted the importance of appropriate reference areas and the importance of correct normalization of the SPOT-VGT data.

  14. Coastwide Reference Monitoring System (CRMS) Vegetation Volume Index: An assessment tool for marsh habitat focused on the three-dimensional structure at CRMS vegetation monitoring stations

    Science.gov (United States)

    Wood, William B.; Visser, Jenneke M.; Piazza, Sarai C.; Sharp, Leigh A.; Hundy, Laura C.; McGinnis, Tommy E.

    2015-12-04

    A Vegetation Volume (VV) variable and Vegetation Volume Index (VVI) have been developed for the Coastwide Reference Monitoring System (CRMS). The VV is a measure of the amount of three-dimensional vegetative structure present at each CRMS site and is based on vegetation data collected annually. The VV uses 10 stations per CRMS site to quantify four vegetation layers: carpet, herbaceous, shrub, and tree. For each layer an overall live vegetation percent cover and height are collected to create a layer volume; the individual layer volumes are then summed to generate a site vegetation volume profile. The VV uses the two-dimensional area of live vegetative cover (in square meters) multiplied by the height (in meters) of each layer to produce a volume (in cubic meters) for each layer present in a 2-meter by 2-meter station. These layers are additive, yielding a total volume for each of the 10 herbaceous vegetation stations and an overall CRMS marsh site average.

  15. Analysis of Agricultural Drought in East Java Using Vegetation Health Index

    OpenAIRE

    Amalo, Luisa Febrina; Hidayat, Rahmat; Sulma, Sayidah

    2018-01-01

    Drought is a natural hazard indicated by the decreasing of rainfall and water storage and impacting agricultural sector. Agricultural drought assessment has been used to monitor agricultural sustainability, particularly in East Java as national agricultural production center. Identification of drought characteristics –correlated with El Niño-Southern Oscillation, and agricultural impact on paddy fields and rice production using VHI (Vegetation Health Index) were conducted. VHI is produced by ...

  16. Atmospheric effects on the NDVI - Strategies for its removal. [Normalized Difference Vegetation Index

    Science.gov (United States)

    Kaufman, Y. J.; Tanre, D.; Holben, B. N.; Markham, B.; Gitelson, A.

    1992-01-01

    The compositing technique used to derive global vegetation index (NDVI) from the NOAA AVHRR radiances reduces the residual effect of water vapor and aerosol on the NDVI. The reduction in the atmospheric effect is shown using a comprehensive measured data set for desert conditions, and a simulation for grass with continental aerosol. A statistical analaysis of the probability of occurrence of aerosol optical thickness and precipitable water vapor measured in different climatic regimes is used for this simulation. It is concluded that for a long compositing period (e.g., 27 days), the residual aerosol optical thickness and precipitable water vapor are usually too small to be corrected. For a 9-day compositing, the residual average aerosol effect may be about twice the correction uncertainty. For Landsat TM or Earth Observing System Moderate Resolution Imaging Spectrometer (EOS-MODIS) data, the newly defined atmospherically resistant vegetation index (ARVI) is more promising than possible direct atmospheric correction schemes, except for heavy desert dust conditions.

  17. Determination of Leaf Area Index, Total Foliar N, and Normalized Difference Vegetation Index for Arctic Ecosystems Dominated by Cassiope tetragona

    DEFF Research Database (Denmark)

    Campioli, M; Street, LE; Michelsen, Anders

    2009-01-01

    have not been accurately quantified. We address this knowledge gap by (i) direct measurements of LAI and TFN for C. tetragona, and (ii) determining TFN-LAI and LAI–normalized difference vegetation index (NDVI) relationships for typical C. tetragona tundras in the subarctic (Sweden) and High Arctic...... leaf N and biomass. The LAI-NDVI and TFN-LAI relationships showed high correlation and can be used to estimate indirectly LAI and TFN. The LAI-NDVI relationship for C. tetragona vegetation differed from a generic LAI-NDVI relationship for arctic tundra, whereas the TFN-LAI relationship did not. Overall...

  18. [Vegetation index estimation by chlorophyll content of grassland based on spectral analysis].

    Science.gov (United States)

    Xiao, Han; Chen, Xiu-Wan; Yang, Zhen-Yu; Li, Huai-Yu; Zhu, Han

    2014-11-01

    Comparing the methods of existing remote sensing research on the estimation of chlorophyll content, the present paper confirms that the vegetation index is one of the most practical and popular research methods. In recent years, the increasingly serious problem of grassland degradation. This paper, firstly, analyzes the measured reflectance spectral curve and its first derivative curve in the grasslands of Songpan, Sichuan and Gongger, Inner Mongolia, conducts correlation analysis between these two spectral curves and chlorophyll content, and finds out the regulation between REP (red edge position) and grassland chlorophyll content, that is, the higher the chlorophyll content is, the higher the REIP (red-edge inflection point) value would be. Then, this paper constructs GCI (grassland chlorophyll index) and selects the most suitable band for retrieval. Finally, this paper calculates the GCI by the use of satellite hyperspectral image, conducts the verification and accuracy analysis of the calculation results compared with chlorophyll content data collected from field of twice experiments. The result shows that for grassland chlorophyll content, GCI has stronger sensitivity than other indices of chlorophyll, and has higher estimation accuracy. GCI is the first proposed to estimate the grassland chlorophyll content, and has wide application potential for the remote sensing retrieval of grassland chlorophyll content. In addition, the grassland chlorophyll content estimation method based on remote sensing retrieval in this paper provides new research ideas for other vegetation biochemical parameters' estimation, vegetation growth status' evaluation and grassland ecological environment change's monitoring.

  19. Spatiotemporal changes of normalized difference vegetation index (NDVI) and response to climate extremes and ecological restoration in the Loess Plateau, China

    Science.gov (United States)

    Zhao, Anzhou; Zhang, Anbing; Liu, Xianfeng; Cao, Sen

    2018-04-01

    Extreme drought, precipitation, and other extreme climatic events often have impacts on vegetation. Based on meteorological data from 52 stations in the Loess Plateau (LP) and a satellite-derived normalized difference vegetation index (NDVI) from the third-generation Global Inventory Modeling and Mapping Studies (GIMMS3g) dataset, this study investigated the relationship between vegetation change and climatic extremes from 1982 to 2013. Our results showed that the vegetation coverage increased significantly, with a linear rate of 0.025/10a ( P NDVI revealed an increasing trend from the northwest to the southeast, with about 61.79% of the LP exhibiting a significant increasing trend ( P NDVI at the yearly time scale ( P NDVI during the spring and autumn ( P NDVI and RX1day, TMAXmean, TXn, and TXx was insignificant in summer. Vegetation exhibited a significant negative relationship with precipitation extremes in winter ( P NDVI in Yan'an and Yulin during 1998-2013, r = 0.859 and 0.85, n = 16, P < 0.001.

  20. Generating Vegetation Leaf Area Index Earth System Data Record from Multiple Sensors. Part 1; Theory

    Science.gov (United States)

    Ganguly, Sangram; Schull, Mitchell A.; Samanta, Arindam; Shabanov, Nikolay V.; Milesi, Cristina; Nemani, Ramakrishna R.; Knyazikhin, Yuri; Myneni, Ranga B.

    2008-01-01

    The generation of multi-decade long Earth System Data Records (ESDRs) of Leaf Area Index (LAI) and Fraction of Photosynthetically Active Radiation absorbed by vegetation (FPAR) from remote sensing measurements of multiple sensors is key to monitoring long-term changes in vegetation due to natural and anthropogenic influences. Challenges in developing such ESDRs include problems in remote sensing science (modeling of variability in global vegetation, scaling, atmospheric correction) and sensor hardware (differences in spatial resolution, spectral bands, calibration, and information content). In this paper, we develop a physically based approach for deriving LAI and FPAR products from the Advanced Very High Resolution Radiometer (AVHRR) data that are of comparable quality to the Moderate resolution Imaging Spectroradiometer (MODIS) LAI and FPAR products, thus realizing the objective of producing a long (multi-decadal) time series of these products. The approach is based on the radiative transfer theory of canopy spectral invariants which facilitates parameterization of the canopy spectral bidirectional reflectance factor (BRF). The methodology permits decoupling of the structural and radiometric components and obeys the energy conservation law. The approach is applicable to any optical sensor, however, it requires selection of sensor-specific values of configurable parameters, namely, the single scattering albedo and data uncertainty. According to the theory of spectral invariants, the single scattering albedo is a function of the spatial scale, and thus, accounts for the variation in BRF with sensor spatial resolution. Likewise, the single scattering albedo accounts for the variation in spectral BRF with sensor bandwidths. The second adjustable parameter is data uncertainty, which accounts for varying information content of the remote sensing measurements, i.e., Normalized Difference Vegetation Index (NDVI, low information content), vs. spectral BRF (higher

  1. Phenological response of vegetation to upstream river flow in the Heihe Rive basin by time series analysis of MODIS data

    Directory of Open Access Journals (Sweden)

    L. Jia

    2011-03-01

    Full Text Available Liquid and solid precipitation is abundant in the high elevation, upper reach of the Heihe River basin in northwestern China. The development of modern irrigation schemes in the middle reach of the basin is taking up an increasing share of fresh water resources, endangering the oasis and traditional irrigation systems in the lower reach. In this study, the response of vegetation in the Ejina Oasis in the lower reach of the Heihe River to the water yield of the upper catchment was analyzed by time series analysis of monthly observations of precipitation in the upper and lower catchment, river streamflow downstream of the modern irrigation schemes and satellite observations of vegetation index. Firstly, remotely sensed NDVI data acquired by Terra-MODIS are used to monitor the vegetation dynamic for a seven years period between 2000 and 2006. Due to cloud-contamination, atmospheric influence and different solar and viewing angles, however, the quality and consistence of time series of remotely sensed NDVI data are degraded. A Fourier Transform method – the Harmonic Analysis of Time Series (HANTS algorithm – is used to reconstruct cloud- and noise-free NDVI time series data from the Terra-MODIS NDVI dataset. Modification is made on HANTS by adding additional parameters to deal with large data gaps in yearly time series in combination with a Temporal-Similarity-Statistics (TSS method developed in this study to seek for initial values for the large gap periods. Secondly, the same Fourier Transform method is used to model time series of the vegetation phenology. The reconstructed cloud-free NDVI time series data are used to study the relationship between the water availability (i.e. the local precipitation and upstream water yield and the evolution of vegetation conditions in Ejina Oasis from 2000 to 2006. Anomalies in precipitation, streamflow, and vegetation index are detected by comparing each year with the average year. The results showed that

  2. Automated Land Cover Change Detection and Mapping from Hidden Parameter Estimates of Normalized Difference Vegetation Index (NDVI) Time-Series

    Science.gov (United States)

    Chakraborty, S.; Banerjee, A.; Gupta, S. K. S.; Christensen, P. R.; Papandreou-Suppappola, A.

    2017-12-01

    Multitemporal observations acquired frequently by satellites with short revisit periods such as the Moderate Resolution Imaging Spectroradiometer (MODIS), is an important source for modeling land cover. Due to the inherent seasonality of the land cover, harmonic modeling reveals hidden state parameters characteristic to it, which is used in classifying different land cover types and in detecting changes due to natural or anthropogenic factors. In this work, we use an eight day MODIS composite to create a Normalized Difference Vegetation Index (NDVI) time-series of ten years. Improved hidden parameter estimates of the nonlinear harmonic NDVI model are obtained using the Particle Filter (PF), a sequential Monte Carlo estimator. The nonlinear estimation based on PF is shown to improve parameter estimation for different land cover types compared to existing techniques that use the Extended Kalman Filter (EKF), due to linearization of the harmonic model. As these parameters are representative of a given land cover, its applicability in near real-time detection of land cover change is also studied by formulating a metric that captures parameter deviation due to change. The detection methodology is evaluated by considering change as a rare class problem. This approach is shown to detect change with minimum delay. Additionally, the degree of change within the change perimeter is non-uniform. By clustering the deviation in parameters due to change, this spatial variation in change severity is effectively mapped and validated with high spatial resolution change maps of the given regions.

  3. A Robust Inversion Algorithm for Surface Leaf and Soil Temperatures Using the Vegetation Clumping Index

    Directory of Open Access Journals (Sweden)

    Zunjian Bian

    2017-07-01

    Full Text Available The inversion of land surface component temperatures is an essential source of information for mapping heat fluxes and the angular normalization of thermal infrared (TIR observations. Leaf and soil temperatures can be retrieved using multiple-view-angle TIR observations. In a satellite-scale pixel, the clumping effect of vegetation is usually present, but it is not completely considered during the inversion process. Therefore, we introduced a simple inversion procedure that uses gap frequency with a clumping index (GCI for leaf and soil temperatures over both crop and forest canopies. Simulated datasets corresponding to turbid vegetation, regularly planted crops and randomly distributed forest were generated using a radiosity model and were used to test the proposed inversion algorithm. The results indicated that the GCI algorithm performed well for both crop and forest canopies, with root mean squared errors of less than 1.0 °C against simulated values. The proposed inversion algorithm was also validated using measured datasets over orchard, maize and wheat canopies. Similar results were achieved, demonstrating that using the clumping index can improve inversion results. In all evaluations, we recommend using the GCI algorithm as a foundation for future satellite-based applications due to its straightforward form and robust performance for both crop and forest canopies using the vegetation clumping index.

  4. Feasibility Study of Land Cover Classification Based on Normalized Difference Vegetation Index for Landslide Risk Assessment

    Directory of Open Access Journals (Sweden)

    Thilanki Dahigamuwa

    2016-10-01

    Full Text Available Unfavorable land cover leads to excessive damage from landslides and other natural hazards, whereas the presence of vegetation is expected to mitigate rainfall-induced landslide potential. Hence, unexpected and rapid changes in land cover due to deforestation would be detrimental in landslide-prone areas. Also, vegetation cover is subject to phenological variations and therefore, timely classification of land cover is an essential step in effective evaluation of landslide hazard potential. The work presented here investigates methods that can be used for land cover classification based on the Normalized Difference Vegetation Index (NDVI, derived from up-to-date satellite images, and the feasibility of application in landslide risk prediction. A major benefit of this method would be the eventual ability to employ NDVI as a stand-alone parameter for accurate assessment of the impact of land cover in landslide hazard evaluation. An added benefit would be the timely detection of undesirable practices such as deforestation using satellite imagery. A landslide-prone region in Oregon, USA is used as a model for the application of the classification method. Five selected classification techniques—k-nearest neighbor, Gaussian support vector machine (GSVM, artificial neural network, decision tree and quadratic discriminant analysis support the viability of the NDVI-based land cover classification. Finally, its application in landslide risk evaluation is demonstrated.

  5. Preparing Landsat Image Time Series (LITS for Monitoring Changes in Vegetation Phenology in Queensland, Australia

    Directory of Open Access Journals (Sweden)

    Santosh Bhandari

    2012-06-01

    Full Text Available Time series of images are required to extract and separate information on vegetation change due to phenological cycles, inter-annual climatic variability, and long-term trends. While images from the Landsat Thematic Mapper (TM sensor have the spatial and spectral characteristics suited for mapping a range of vegetation structural and compositional properties, its 16-day revisit period combined with cloud cover problems and seasonally limited latitudinal range, limit the availability of images at intervals and durations suitable for time series analysis of vegetation in many parts of the world. Landsat Image Time Series (LITS is defined here as a sequence of Landsat TM images with observations from every 16 days for a five-year period, commencing on July 2003, for a Eucalyptus woodland area in Queensland, Australia. Synthetic Landsat TM images were created using the Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM algorithm for all dates when images were either unavailable or too cloudy. This was done using cloud-free scenes and a MODIS Nadir BRDF Adjusted Reflectance (NBAR product. The ability of the LITS to measure attributes of vegetation phenology was examined by: (1 assessing the accuracy of predicted image-derived Foliage Projective Cover (FPC estimates using ground-measured values; and (2 comparing the LITS-generated normalized difference vegetation index (NDVI and MODIS NDVI (MOD13Q1 time series. The predicted image-derived FPC products (value ranges from 0 to 100% had an RMSE of 5.6. Comparison between vegetation phenology parameters estimated from LITS-generated NDVI and MODIS NDVI showed no significant difference in trend and less than 16 days (equal to the composite period of the MODIS data used difference in key seasonal parameters, including start and end of season in most of the cases. In comparison to similar published work, this paper tested the STARFM algorithm in a new (broadleaf forest environment and also

  6. Disturbance metrics predict a wetland Vegetation Index of Biotic Integrity

    Science.gov (United States)

    Stapanian, Martin A.; Mack, John; Adams, Jean V.; Gara, Brian; Micacchion, Mick

    2013-01-01

    Indices of biological integrity of wetlands based on vascular plants (VIBIs) have been developed in many areas in the USA. Knowledge of the best predictors of VIBIs would enable management agencies to make better decisions regarding mitigation site selection and performance monitoring criteria. We use a novel statistical technique to develop predictive models for an established index of wetland vegetation integrity (Ohio VIBI), using as independent variables 20 indices and metrics of habitat quality, wetland disturbance, and buffer area land use from 149 wetlands in Ohio, USA. For emergent and forest wetlands, predictive models explained 61% and 54% of the variability, respectively, in Ohio VIBI scores. In both cases the most important predictor of Ohio VIBI score was a metric that assessed habitat alteration and development in the wetland. Of secondary importance as a predictor was a metric that assessed microtopography, interspersion, and quality of vegetation communities in the wetland. Metrics and indices assessing disturbance and land use of the buffer area were generally poor predictors of Ohio VIBI scores. Our results suggest that vegetation integrity of emergent and forest wetlands could be most directly enhanced by minimizing substrate and habitat disturbance within the wetland. Such efforts could include reducing or eliminating any practices that disturb the soil profile, such as nutrient enrichment from adjacent farm land, mowing, grazing, or cutting or removing woody plants.

  7. Integrated NDVI images for Niger 1986-1987. [Normalized Difference Vegetation Index

    Science.gov (United States)

    Harrington, John A., Jr.; Wylie, Bruce K.; Tucker, Compton J.

    1988-01-01

    Two NOAA AVHRR images are presented which provide a comparison of the geographic distribution of an integration of the normalized difference vegetation index (NDVI) for the Sahel zone in Niger for the growing seasons of 1986 and 1987. The production of the images and the application of the images for resource management are discussed. Daily large area coverage with a spatial resolution of 1.1 km at nadir were transformed to the NDVI and geographically registered to produce the images.

  8. Spatiotemporal variability and predictability of Normalized Difference Vegetation Index (NDVI) in Alberta, Canada.

    Science.gov (United States)

    Jiang, Rengui; Xie, Jiancang; He, Hailong; Kuo, Chun-Chao; Zhu, Jiwei; Yang, Mingxiang

    2016-09-01

    As one of the most popular vegetation indices to monitor terrestrial vegetation productivity, Normalized Difference Vegetation Index (NDVI) has been widely used to study the plant growth and vegetation productivity around the world, especially the dynamic response of vegetation to climate change in terms of precipitation and temperature. Alberta is the most important agricultural and forestry province and with the best climatic observation systems in Canada. However, few studies pertaining to climate change and vegetation productivity are found. The objectives of this paper therefore were to better understand impacts of climate change on vegetation productivity in Alberta using the NDVI and provide reference for policy makers and stakeholders. We investigated the following: (1) the variations of Alberta's smoothed NDVI (sNDVI, eliminated noise compared to NDVI) and two climatic variables (precipitation and temperature) using non-parametric Mann-Kendall monotonic test and Thiel-Sen's slope; (2) the relationships between sNDVI and climatic variables, and the potential predictability of sNDVI using climatic variables as predictors based on two predicted models; and (3) the use of a linear regression model and an artificial neural network calibrated by the genetic algorithm (ANN-GA) to estimate Alberta's sNDVI using precipitation and temperature as predictors. The results showed that (1) the monthly sNDVI has increased during the past 30 years and a lengthened growing season was detected; (2) vegetation productivity in northern Alberta was mainly temperature driven and the vegetation in southern Alberta was predominantly precipitation driven for the period of 1982-2011; and (3) better performances of the sNDVI-climate relationships were obtained by nonlinear model (ANN-GA) than using linear (regression) model. Similar results detected in both monthly and summer sNDVI prediction using climatic variables as predictors revealed the applicability of two models for

  9. NOAA JPSS Visible Infrared Imaging Radiometer Suite (VIIRS) Smoothed Normalized Difference Vegetation Index (NDVI) from NDE

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Visible Infrared Imaging Radiometer Suite (VIIRS) Smoothed Normalized Difference Vegetation Index (NDVI) from NDE is a weekly product derived from the VIIRS...

  10. [Responses of normalized difference vegetation index (NDVI) to precipitation changes on the grassland of Tibetan Plateau from 2000 to 2015.

    Science.gov (United States)

    Wang, Zhi Peng; Zhang, Xian Zhou; He, Yong Tao; Li, Meng; Shi, Pei Li; Zu, Jia Xing; Niu, Ben

    2018-01-01

    Precipitation change is an important factor in the inter-annual variation of grassland growth on the Tibetan Plateau. The total amount, distribution pattern and concentration time are three basic characteristics of precipitation change. The temporal and spatial characteristics of precipitation change were analyzed based on climate data of 145 meteorological stations on the Tibetan Plateau and nearby areas from 2000 to 2015. The total precipitation amount was characterized by annual precipitation, distribution pattern of precipitation during the year was characterized by improved precipitation concentration index (PCI), and precipitation centroid (PC) was defined to indicate the change in precipitation concentrated time. To better illustrate the response of grassland to precipitation change, vegetation growth status was characterized by the maximum value of normalized difference vegetation index (NDVI max ). Results indicated that the annual precipitation and PCI had an apparent gradient across the whole plateau and the latest PC occurred in the southern plateau. NDVI max of alpine shrub grassland was significantly correlated with the change of PCI,increased with even distribution of precipitation during growth period, and limited by the total annual precipitation. Alpine meadow did not show significantly correlations with these three indices. The inter-annual variability of NDVI max of steppe was controlled by both PCI and PC. NDVI max of alpine desert grassland was mainly controlled by annual precipitation. In addition to annual total amount of precipitation, the distribution characteristics of precipitation should be further considered when the influence of precipitation change on different types of vegetation on the Qinghai Tibet Plateau was studied.

  11. The effect of bi-directional reflectance distribution function on the estimation of vegetation indices and leaf area index (LAI): A case study of the vegetation in succession stages after forest fire in northwestern Canada

    International Nuclear Information System (INIS)

    Hasegawa, K.; Matsuyama, H.; Tsuzuki, H.; Sweda, T.

    2006-01-01

    The effect of the dependence of the satellite data on sun/sensor geometry must be considered in the case of monitoring vegetation from satellites. Vegetation structure causes uneven scattering of sunlight, which is expressed by bi-directional reflectance distribution function (BRDF). The purpose of this study is to estimate the effect of BRDF of monitoring vegetation using the reflectance of visible and near-infrared bands. We investigated the vegetation in succession stages after forest fire (main species: spruce) in the northwestern Canada. BRF (Bidirectional Reflectance Factor) was measured in the seven sites of some succession stages, along with the measurements of leaf area index (LAI) and biomass. The main results obtained in this study are summarized as follows. (1) In each site, the difference of Normalized Difference Vegetation Index (NDVI) value around 0.1-0.2 was caused by BRDF when the sensor angle was changed from -15deg to 15 deg, being equivalent to the standard image of IKONOS. Also, LAI estimated by NDVI varied from 22% to 65% of the average. (2) The robustness of other vegetation indices to BRDF was compared. The reflectance of the near-infrared band normalized by the sum of other bands (nNIR), and Global Environmental Monitoring Index (GEMI) were investigated along with NDVI. It is clarified that nNIR was most robust in the site where vegetation existed. GEMI was most robust in the sites of scarce vegetation, while NDVI was strongly affected by BRDF in such sites

  12. Seasonal analysis of precipitation, drought and Vegetation index in Indonesian paddy field based on remote sensing data

    International Nuclear Information System (INIS)

    Darmawan, S; Takeuchi, W; Shofiyati, R; Sari, D K; Wikantika, K

    2014-01-01

    Paddy field is important agriculture crop in Indonesia. Rice is a food staple for 237,6 million Indonesian people. Paddy field growth is strongly influenced by water, but the amount of precipitation is unpredictable. Annual and interannual climate variability in Indonesia is unusual. In recent years remote sensing data has been used for measurement and monitoring of precipitation, drought and Vegetation index such as Global Satellite Mapping of Precipitation (GSMaP), Multi-purpose Transmission SATellite (MTSAT) and Moderate Resolution Imaging Spectroradiometer (MODIS). The objective of this research is to investigate seasonal variability of precipitation, drought and Vegetation index in Indonesian paddy field based on remote sensing data. The methodology consists of collecting of enhanced vegetation index (EVI) from MODIS data, mosaicking of image, collecting of region of interest of paddy field, collecting of precipitation and drought index based on Keetch Bryam Drought Index (KBDI) from GSMaP and MTSAT, and seasonal analysis. The result of this research has showed seasonal variability of precipitation, KBDI and EVI on Indonesia paddy field from 2007 until 2012. Precipitation begins from January until May and October until December, and KBDI begins to increase from June and peak in September only in South Sumatera precipitation almost in all month. Seasonal analysis has showed precipitation and KBDI affect on EVI that can indicate variety phenology of Indonesian paddy field. Peak of EVI occurs before peak of KBDI occurs and increasing of KBDI followed by decreasing of EVI. In 2010 all province got higher precipitation and smaller KBDI so EVI has three peaks such as in West Java that can indicated increasing of rice production

  13. Estimating vegetation dryness to optimize fire risk assessment with spot vegetation satellite data in savanna ecosystems

    Science.gov (United States)

    Verbesselt, J.; Somers, B.; Lhermitte, S.; van Aardt, J.; Jonckheere, I.; Coppin, P.

    2005-10-01

    The lack of information on vegetation dryness prior to the use of fire as a management tool often leads to a significant deterioration of the savanna ecosystem. This paper therefore evaluated the capacity of SPOT VEGETATION time-series to monitor the vegetation dryness (i.e., vegetation moisture content per vegetation amount) in order to optimize fire risk assessment in the savanna ecosystem of Kruger National Park in South Africa. The integrated Relative Vegetation Index approach (iRVI) to quantify the amount of herbaceous biomass at the end of the rain season and the Accumulated Relative Normalized Difference vegetation index decrement (ARND) related to vegetation moisture content were selected. The iRVI and ARND related to vegetation amount and moisture content, respectively, were combined in order to monitor vegetation dryness and optimize fire risk assessment in the savanna ecosystems. In situ fire activity data was used to evaluate the significance of the iRVI and ARND to monitor vegetation dryness for fire risk assessment. Results from the binary logistic regression analysis confirmed that the assessment of fire risk was optimized by integration of both the vegetation quantity (iRVI) and vegetation moisture content (ARND) as statistically significant explanatory variables. Consequently, the integrated use of both iRVI and ARND to monitor vegetation dryness provides a more suitable tool for fire management and suppression compared to other traditional satellite-based fire risk assessment methods, only related to vegetation moisture content.

  14. Exploiting differential vegetation phenology for satellite-based mapping of semiarid grass vegetation in the southwestern United States and northern Mexico

    Science.gov (United States)

    Dye, Dennis G.; Middleton, Barry R.; Vogel, John M.; Wu, Zhuoting; Velasco, Miguel G.

    2016-01-01

    We developed and evaluated a methodology for subpixel discrimination and large-area mapping of the perennial warm-season (C4) grass component of vegetation cover in mixed-composition landscapes of the southwestern United States and northern Mexico. We describe the methodology within a general, conceptual framework that we identify as the differential vegetation phenology (DVP) paradigm. We introduce a DVP index, the Normalized Difference Phenometric Index (NDPI) that provides vegetation type-specific information at the subpixel scale by exploiting differential patterns of vegetation phenology detectable in time-series spectral vegetation index (VI) data from multispectral land imagers. We used modified soil-adjusted vegetation index (MSAVI2) data from Landsat to develop the NDPI, and MSAVI2 data from MODIS to compare its performance relative to one alternate DVP metric (difference of spring average MSAVI2 and summer maximum MSAVI2), and two simple, conventional VI metrics (summer average MSAVI2, summer maximum MSAVI2). The NDPI in a scaled form (NDPIs) performed best in predicting variation in perennial C4 grass cover as estimated from landscape photographs at 92 sites (R2 = 0.76, p landscapes of the Southwest, and potentially for monitoring of its response to drought, climate change, grazing and other factors, including land management. With appropriate adjustments, the method could potentially be used for subpixel discrimination and mapping of grass or other vegetation types in other regions where the vegetation components of the landscape exhibit contrasting seasonal patterns of phenology.

  15. Estimation of the soil heat flux/net radiation ratio based on spectral vegetation indexes in high-latitude Arctic areas

    International Nuclear Information System (INIS)

    Jacobsen, A.; Hansen, B.U.

    1999-01-01

    The vegetation communities in the Arctic environment are very sensitive to even minor climatic variations and therefore the estimation of surface energy fluxes from high-latitude vegetated areas is an important subject to be pursued. This study was carried out in July-August and used micro meteorological data, spectral reflectance signatures, and vegetation biomass to establish the relation between the soil heat flux/net radiation (G / Rn) ratio and spectral vegetation indices (SVIs). Continuous measurements of soil temperature and soil heat flux were used to calculate the surface ground heat flux by use of conventional methods, and the relation to surface temperature was investigated. Twenty-seven locations were established, and six samples per location, including the measurement of the surface temperature and net radiation to establish the G/Rn ratio and simultaneous spectral reflectance signatures and wet biomass estimates, were registered. To obtain regional reliability, the locations were chosen in order to represent the different Arctic vegetation communities in the study area; ranging from dry tundra vegetation communities (fell fields and dry dwarf scrubs) to moist/wet tundra vegetation communities (snowbeds, grasslands and fens). Spectral vegetation indices, including the simple ratio vegetation index (RVI) and the normalized difference vegetation index (NDVI), were calculated. A comparison of SVIs to biomass proved that RVI gave the best linear expression, and NDVI the best exponential expression. A comparison of SVIs and the surface energy flux ratio G / Rn proved that NDVI gave the best linear expression. SPOT HRV images from July 1989 and 1992 were used to map NDVI and G / Rn at a regional scale. (author)

  16. Estimation of vegetation cover resilience from satellite time series

    Directory of Open Access Journals (Sweden)

    T. Simoniello

    2008-07-01

    Full Text Available Resilience is a fundamental concept for understanding vegetation as a dynamic component of the climate system. It expresses the ability of ecosystems to tolerate disturbances and to recover their initial state. Recovery times are basic parameters of the vegetation's response to forcing and, therefore, are essential for describing realistic vegetation within dynamical models. Healthy vegetation tends to rapidly recover from shock and to persist in growth and expansion. On the contrary, climatic and anthropic stress can reduce resilience thus favouring persistent decrease in vegetation activity.

    In order to characterize resilience, we analyzed the time series 1982–2003 of 8 km GIMMS AVHRR-NDVI maps of the Italian territory. Persistence probability of negative and positive trends was estimated according to the vegetation cover class, altitude, and climate. Generally, mean recovery times from negative trends were shorter than those estimated for positive trends, as expected for vegetation of healthy status. Some signatures of inefficient resilience were found in high-level mountainous areas and in the Mediterranean sub-tropical ones. This analysis was refined by aggregating pixels according to phenology. This multitemporal clustering synthesized information on vegetation cover, climate, and orography rather well. The consequent persistence estimations confirmed and detailed hints obtained from the previous analyses. Under the same climatic regime, different vegetation resilience levels were found. In particular, within the Mediterranean sub-tropical climate, clustering was able to identify features with different persistence levels in areas that are liable to different levels of anthropic pressure. Moreover, it was capable of enhancing reduced vegetation resilience also in the southern areas under Warm Temperate sub-continental climate. The general consistency of the obtained results showed that, with the help of suited analysis

  17. Detecting post-fire burn severity and vegetation recovery using multitemporal remote sensing spectral indices and field-collected composite burn index data in a ponderosa pine forest

    Science.gov (United States)

    Chen, Xuexia; Vogelmann, James E.; Rollins, Matt; Ohlen, Donald; Key, Carl H.; Yang, Limin; Huang, Chengquan; Shi, Hua

    2011-01-01

    It is challenging to detect burn severity and vegetation recovery because of the relatively long time period required to capture the ecosystem characteristics. Multitemporal remote sensing data can providemultitemporal observations before, during and after a wildfire, and can improve the change detection accuracy. The goal of this study is to examine the correlations between multitemporal spectral indices and field-observed burn severity, and to provide a practical method to estimate burn severity and vegetation recovery. The study site is the Jasper Fire area in the Black Hills National Forest, South Dakota, that burned during August and September 2000. Six multitemporal Landsat images acquired from 2000 (pre-fire), 2001 (post-fire), 2002, 2003, 2005 and 2007 were used to assess burn severity. The normalized difference vegetation index (NDVI), enhanced vegetation index (EVI), normalized burn ratio (NBR), integrated forest index (IFI) and the differences of these indices between the pre-fire and post-fire years were computed and analysed with 66 field-based composite burn index (CBI) plots collected in 2002. Results showed that differences of NDVI and differences of EVI between the pre-fire year and the first two years post-fire were highly correlated with the CBI scores. The correlations were low beyond the second year post-fire. Differences of NBR had good correlation with CBI scores in all study years. Differences of IFI had low correlation with CBI in the first year post-fire and had good correlation in later years. A CBI map of the burnt area was produced using regression tree models and the multitemporal images. The dynamics of four spectral indices from 2000 to 2007 indicated that both NBR and IFI are valuable for monitoring long-term vegetation recovery. The high burn severity areas had a much slower recovery than the moderate and low burn areas.

  18. Monitoring phenology of photosynthesis in temperate evergreen and mixed deciduous forests using the normalized difference vegetation index (NDVI) and the photochemical reflectance index (PRI) at leaf and canopy scales

    Science.gov (United States)

    Wong, C. Y.; Arain, M. A.; Ensminger, I.

    2016-12-01

    Evergreen conifers in boreal and temperate regions undergo strong seasonal changes in photoperiod and temperatures, which determines their phenology of high photosynthetic activity in the growing season and downregulation during the winter. Monitoring the timing of the transition between summer activity and winter downregulation in evergreens is difficult since this is a largely invisible process, unlike in deciduous trees that have a visible budding and a sequence of leaf unfolding in the spring and leaf abscission in the fall. The light-use efficiency (LUE) model estimates gross primary productivity (GPP) and may be parameterized using remotely sensed vegetation indices. Using spectral reflectance data, we derived the normalized difference vegetation index (NDVI), a measure of leaf "greenness", and the photochemical reflectance index (PRI), a proxy for chlorophyll:carotenoid ratios which is related to photosynthetic activity. To better understand the relationship between these vegetation indices and photosynthetic activity and to contrast this relationship between plant functional types, the phenology of NDVI, PRI and photosynthesis was monitored in an evergreen forest and a mixed deciduous forest at the leaf and canopy scale. Our data indicates that the LUE model can be parameterized by NDVI and PRI to track forest phenology. Differences in the sensitivity of PRI and NDVI will be discussed. These findings have implications to address the phenology of evergreen conifers by using PRI to complement NDVI in the LUE model, potentially improving model productivity estimates in northern hemisphere forests, that are dominated by conifers.

  19. HUBUNGAN ANTARA INDEKS VEGETASI NDVI (NORMALIZED DIFFERENCE VEGETATION INDEX DAN KOEFISIEN RESESI BASEFLOW PADA BEBERAPA SUBDAS PROPINSI JAWA TENGAH DAN DAERAH ISTIMEWA YOGYAKARTA

    Directory of Open Access Journals (Sweden)

    Bokiraiya Latuamury

    2013-06-01

    Full Text Available The background of this research is the decrease of environment capacity in cacthment ecosystem, especially impact of vegetation forest on behavior streamflow. The indicators of cacthment destruction can be seen through hydrograph characteristics. Evaluation of cactment respons of flow hydrographic as an evaluation tools of river catchment responses becomes very important to analyze because it is a benchmark in determination several policy about flood, drough, sedimentation and landslide handling. The research purpose is to analyze the relationship between vegetation index NDVI (Normalized Difference Vegetation Index and the characteristic of baseflow recession coefficient at several subcatchment areas in province of Central Java and Specific District of Yogjakarta.The method of this research is surveillance on data recording of AWLR (Automatic Water Level Recorder and data of River Flow Measuring Stations in order to separate the baseflow by calibration curve, and image interpretation of Landsat ETM+ for the transformation of vegetation index (NDVI-Normalized Difference Vegetation Index.The analysis on recession coefficient data (Krb and NDVI were correlated to analyze the strength of relationship between these two parameters. The results of statistical analysis on index NDVI and recession coefficient showsthat NDVI and recession coefficient value at R2 is 0.1427, F = 2.17 which is not significant at 1% significance level of 0.1646. The result shows a very weak correlation of 0.077 which mean that vegetation density (NDVI indexhas a very weak control on low flows. Basically, river baseflow is a genetic component of river flow which comes from aquifer storage and/or other low flow sources. Thus, geology and soil have a significant effect on baseflow.

  20. Spectral Reflectance and Vegetation Index Changes in Deciduous Forest Foliage Following Tree Removal: Potential for Deforestation Monitoring

    Science.gov (United States)

    Peng, D.; Hu, Y.; Li, Z.

    2016-05-01

    It is important to detect and quantify deforestation to guide strategic decisions regarding environment, socioeconomic development, and climate change. In the present study, we conducted a field experiment to examine spectral reflectance and vegetation index changes in poplar and locust tree foliage with different leaf area indices over the course of three sunny days, following tree removal from the canopy. The spectral reflectance of foliage from harvested trees was measured using an ASD FieldSpec Prospectroradiometer; synchronous meteorological data were also obtained. We found that reflectance in short-wave infrared and red-edge reflectance was more time sensitive after tree removal than reflectance in other spectral regions, and that the normalized difference water index (NDWI) and the red-edge chlorophyll index (CIRE) were the preferred indicators of these changes from several indices evaluated. Synthesized meteorological environments were found to influence water and chlorophyll contents after tree removal, and this subsequently changed the spectral canopy reflectance. Our results indicate the potential for such tree removal to be detected with NDWI or CIRE from the second day of a deforestation event.

  1. Tropical forest biomass and successional age class relationships to a vegetation index derived from Landsat TM data

    Science.gov (United States)

    Sader, Steven A.; Waide, Robert B.; Lawrence, William T.; Joyce, Armond T.

    1989-01-01

    Forest stand structure and biomass data were collected using conventional forest inventory techniques in tropical, subtropical, and warm temperate forest biomes. The feasibility of detecting tropical forest successional age class and total biomass differences using Landsat-Thematic mapper (TM) data, was evaluated. The Normalized Difference Vegetation Index (NDVI) calculated from Landsat-TM data were not significantly correlated with forest regeneration age classes in the mountain terrain of the Luquillo Experimental Forest, Puerto Rico. The low sun angle and shadows cast on steep north and west facing slopes reduced spectral reflectance values recorded by TM orbital altitude. The NDVI, calculated from low altitude aircraft scanner data, was significatly correlated with forest age classes. However, analysis of variance suggested that NDVI differences were not detectable for successional forests older than approximately 15-20 years. Also, biomass differences in young successional tropical forest were not detectable using the NDVI. The vegetation index does not appear to be a good predictor of stand structure variables (e.g., height, diameter of main stem) or total biomass in uneven age, mixed broadleaf forest. Good correlation between the vegetation index and low biomass in even age pine plantations were achieved for a warm temperate study site. The implications of the study for the use of NDVI for forest structure and biomass estimation are discussed.

  2. Estimation and Validation of RapidEye-Based Time-Series of Leaf Area Index for Winter Wheat in the Rur Catchment (Germany

    Directory of Open Access Journals (Sweden)

    Muhammad Ali

    2015-03-01

    Full Text Available Leaf Area Index (LAI is an important variable for numerous processes in various disciplines of bio- and geosciences. In situ measurements are the most accurate source of LAI among the LAI measuring methods, but the in situ measurements have the limitation of being labor intensive and site specific. For spatial-explicit applications (from regional to continental scales, satellite remote sensing is a promising source for obtaining LAI with different spatial resolutions. However, satellite-derived LAI measurements using empirical models require calibration and validation with the in situ measurements. In this study, we attempted to validate a direct LAI retrieval method from remotely sensed images (RapidEye with in situ LAI (LAIdestr. Remote sensing LAI (LAIrapideye were derived using different vegetation indices, namely SAVI (Soil Adjusted Vegetation Index and NDVI (Normalized Difference Vegetation Index. Additionally, applicability of the newly available red-edge band (RE was also analyzed through Normalized Difference Red-Edge index (NDRE and Soil Adjusted Red-Edge index (SARE. The LAIrapideye obtained from vegetation indices with red-edge band showed better correlation with LAIdestr (r = 0.88 and Root Mean Square Devation, RMSD = 1.01 & 0.92. This study also investigated the need to apply radiometric/atmospheric correction methods to the time-series of RapidEye Level 3A data prior to LAI estimation. Analysis of the the RapidEye Level 3A data set showed that application of the radiometric/atmospheric correction did not improve correlation of the estimated LAI with in situ LAI.

  3. Monitoring responses of Mason Pine to acid rain in China based on remote sensing vegetation index

    International Nuclear Information System (INIS)

    Jin, Jiaxin; Jiang, Hong; Zhang, Xiuying; Wang, Ying; Hou, Chunliang

    2014-01-01

    Since the 1970s, acid rain has remained in the public spotlight in both Europe and the United States and recently has emerged as an important problem in other regions such as Southeast Asia. To reveal responses of Masson Pine to acid rain during a long time series in central China, we used the interpolation dataset of acid rain and the Global Inventory Modeling and Mapping Studies (GIMMS) normalized difference vegetation index (NDVI) data to derive the monthly pH and NDVI trajectories based on acidity gradients from 1992 to 2006. Then we analyzed inter-annual and seasonal variation of vegetation growth by improved sinusoidal fitting and regression analysis. In the environment of strong acidity and moderate acidity, the growth of Masson Pine was inhibited during the study period, while the slight acidity promoted growth of Masson Pine to some extent. For the multi-year monthly changing trend of NDVI, late spring to mid autumn, the NDVI showed a decreasing trend, especially in June, while from late autumn to the following spring, the NDVI showed a rising tendency, specifically in December and March

  4. Models for the prediction of the cetane index of biofuels obtained from different vegetable oils using their fatty acid composition

    International Nuclear Information System (INIS)

    Sanchez Borroto, Yisel; Piloto Rodriguez, Ramon; Goyos Perez, Leonardo

    2011-01-01

    The objective of the present work is to obtain a physical-mathematical model that establishes a relationship between the cetane index of biofuels obtained from different vegetable oils and its composition of essential fatty acid. This model is based on experimental data obtained by the authors of the present work and an experimental data reported by different extracted authors of indexed databases. The adjustment of the coefficients of the model is based on the obtaining of residual minima in the capacity of prediction of the model. Starting from these results it is established a very useful tool for the determination of such an important parameter for the fuel diesel as it is the cetane index obtained from an analysis of chemical composition and not obtained from tests in engines banks, to save time and economic resources. (author)

  5. Relation of MODIS EVI and LAI across time, vegetation types and hydrological regimes

    Science.gov (United States)

    Alexandridis, Thomas; Ovakoglou, George

    2015-04-01

    Estimation of the Leaf Area Index (LAI) of a landscape is considered important to describe the ecosystems activity and is used as an important input parameter in hydrological and biogeochemical models related to water and carbon cycle, desertification risk, etc. The measurement of LAI in the field is a laborious and costly process and is mainly done by indirect methods, such as hemispherical photographs that are processed by specialized software. For this reason there have been several attempts to estimate LAI with multispectral satellite images, using theoretical biomass development models, or empirical equations using vegetation indices and land cover maps. The aim of this work is to study the relation of MODIS EVI and LAI across time, vegetation type, and hydrological regime. This was achieved by studying 120 maps of EVI and LAI which cover a hydrological year and five hydrologically diverse areas: river Nestos in Greece, Queimados catchment in Brazil, Rijnland catchment in The Netherlands, river Tamega in Portugal, and river Umbeluzi in Mozambique. The following Terra MODIS composite datasets were downloaded for the hydrological year 2012-2013: MOD13A2 "Vegetation Indices" and MCD15A2 "LAI and FPAR", as well as the equivalent quality information layers (QA). All the pixels that fall in a vegetation land cover (according to the MERIS GLOBCOVER map) were sampled for the analysis, with the exception of those that fell at the border between two vegetation or other land cover categories, to avoid the influence of mixed pixels. Using linear regression analysis, the relationship between EVI and LAI was identified per date, vegetation type and study area. Results show that vegetation type has the highest influence in the variation of the relationship between EVI and LAI in each study area. The coefficient of determination (R2) is high and statistically significant (ranging from 0.41 to 0.83 in 90% of the cases). When plotting the EVI factor from the regression equation

  6. Camera derived vegetation greenness index as proxy for gross primary production in a low Arctic wetland area

    DEFF Research Database (Denmark)

    Westergaard-Nielsen, Andreas; Lund, Magnus; Hansen, Birger Ulf

    2013-01-01

    vegetation index (NDVI) product derived from the WorldView-2 satellite. An object-based classification based on a bi-temporal image composite was used to classify the study area into heath, copse, fen, and bedrock. Temporal evolution of vegetation greenness was evaluated and modeled with double sigmoid...... and GPP (R-2 = 0.85, p remote Arctic regions....... (C) 2013 International Society for Photogrammetry and Remote Sensing, Inc. (ISPRS) Published by Elsevier B.V. All rights reserved....

  7. Improvement in remote sensing of low vegetation cover in arid regions by correcting vegetation indices for soil ''noise''

    International Nuclear Information System (INIS)

    Escadafal, R.; Huete, A.

    1991-01-01

    The variations of near-infrared red reflectance ratios of ten aridic soil samples were correlated with a ''redness index'' computed from red and green spectral bands. These variations have been shown to limit the performances of vegetation indices (NDVI and SAVI) in discriminating low vegetation covers. The redness index is used to adjust for this ''soil noise''. Dala simulated for vegetation densities of 5 to 15% cover showed that the sensitivity of the corrected vegetation indices was significantly improved. Specifically, the ''noise-corrected'' SAVI was able to assess vegetation amounts with an error four times smaller than the uncorrected NDVI. These promising results should lead to a significant improvement in assessing biomass in arid lands from remotely sensed data. (author) [fr

  8. Developing Models to Predict the Number of Fire Hotspots from an Accumulated Fuel Dryness Index by Vegetation Type and Region in Mexico

    Directory of Open Access Journals (Sweden)

    D. J. Vega-Nieva

    2018-04-01

    Full Text Available Understanding the linkage between accumulated fuel dryness and temporal fire occurrence risk is key for improving decision-making in forest fire management, especially under growing conditions of vegetation stress associated with climate change. This study addresses the development of models to predict the number of 10-day observed Moderate-Resolution Imaging Spectroradiometer (MODIS active fire hotspots—expressed as a Fire Hotspot Density index (FHD—from an Accumulated Fuel Dryness Index (AcFDI, for 17 main vegetation types and regions in Mexico, for the period 2011–2015. The AcFDI was calculated by applying vegetation-specific thresholds for fire occurrence to a satellite-based fuel dryness index (FDI, which was developed after the structure of the Fire Potential Index (FPI. Linear and non-linear models were tested for the prediction of FHD from FDI and AcFDI. Non-linear quantile regression models gave the best results for predicting FHD using AcFDI, together with auto-regression from previously observed hotspot density values. The predictions of 10-day observed FHD values were reasonably good with R2 values of 0.5 to 0.7 suggesting the potential to be used as an operational tool for predicting the expected number of fire hotspots by vegetation type and region in Mexico. The presented modeling strategy could be replicated for any fire danger index in any region, based on information from MODIS or other remote sensors.

  9. Enhanced Vegetation Index (EVI na análise da dinâmica da vegetação da reserva biológica de Sooretama, ES Use of Enhanced Vegetation Index (EVI in the analysis os vegetation dynamics of the Sooretama biological reservation, ES

    Directory of Open Access Journals (Sweden)

    André Quintão de Almeida

    2008-12-01

    Full Text Available Técnicas de análises de séries temporais são utilizadas para caracterizar o comportamento de fenômenos naturais no domínio do tempo. Neste artigo, segundo a metodologia proposta por Box et al. (1994, 125 observações do Enhanced Vegetation Index (EVI foram analisadas. Os valores modelados correspondem às variações temporais ocorridas no dossel florestal da reserva biológica de Sooretama, localizada ao Norte do Estado do Espírito Santo, no Município de Linhares. Os resultados indicaram que a metodologia foi adequada. Os resíduos do modelo ajustado são não correlacionados com distribuição normal, média zero e variância s². Com o menor valor do Critério de Informação de Akaike (AIC -570,51, o modelo ajustado foi o Sazonal Auto-Regressivo Integrado de Médias Móveis (1,0,1(1,0,112.Temporal series analysis techniques are used to characterize the behavior of natural phenomenon in time domain. In this paper, 125 Enhanced Vegetation Index (EVI observations were analyzed according to the methodology proposed by Box et al.(1994. The values modeled correspond to the temporal variations that occurred in the forest canopy of the Sooretama Biological Reserve, in northern Espírito Santo, in the district of Linhares. The results indicated that such methodology was adequate. The residues of the adjusted model are not correlated with normal distribution, zero average and s² variance. At the lowest value of the Akaike Information Criteria (AIC -570. 51, the model adjusted was the Mobile Average Integrated Self-Regressive Seasonal model (1, 0, 1 (1, 0, 1-12.

  10. Effects of Telecoupling on Global Vegetation Dynamics

    Science.gov (United States)

    Viña, A.; Liu, J.

    2016-12-01

    With the ever increasing trend in telecoupling processes, such as international trade, all countries around the world are becoming more interdependent. However, the effects of this growing interdependence on vegetation (e.g., shifts in the geographic extent and distribution) remain unknown even though vegetation dynamics are crucially important for food production, carbon sequestration, provision of other ecosystem services, and biodiversity conservation. In this study we evaluate the effects of international trade on the spatio-temporal trajectories of vegetation at national and global scales, using vegetation index imagery collected over more than three decades by the Advanced Very High Resolution Radiometer (AVHRR) satellite sensor series together with concurrent national and international data on international trade (and its associated movement of people, goods, services and information). The spatio-temporal trajectories of vegetation are obtained using the scale of fluctuation technique, which is based on the decomposition of the AVHRR image time series to obtain information on its spatial dependence structure over time. Similar to the correlation length, the scale of fluctuation corresponds to the range over which fluctuations in the vegetation index are spatially correlated. Results indicate that global vegetation has changed drastically over the last three decades. These changes are not uniform across space, with hotspots in active trading countries. This study not only has direct implications for understanding global vegetation dynamics, but also sheds important insights on the complexity of human-nature interactions across telecoupled systems.

  11. Climatic factors driving vegetation declines in the 2005 and 2010 Amazon droughts.

    Directory of Open Access Journals (Sweden)

    Wenqian Zhao

    Full Text Available Along with global climate change, the occurrence of extreme droughts in recent years has had a serious impact on the Amazon region. Current studies on the driving factors of the 2005 and 2010 Amazon droughts has focused on the influence of precipitation, whereas the impacts of temperature and radiation have received less attention. This study aims to explore the climate-driven factors of Amazonian vegetation decline during the extreme droughts using vegetation index, precipitation, temperature and radiation datasets. First, time-lag effects of Amazonian vegetation responses to precipitation, radiation and temperature were analyzed. Then, a multiple linear regression model was established to estimate the contributions of climatic factors to vegetation greenness, from which the dominant climate-driving factors were determined. Finally, the climate-driven factors of Amazonian vegetation greenness decline during the 2005 and 2010 extreme droughts were explored. The results showed that (i in the Amazon vegetation greenness responded to precipitation, radiation and temperature, with apparent time lags for most averaging interval periods associated with vegetation index responses of 0-4, 0-9 and 0-6 months, respectively; (ii on average, the three climatic factors without time lags explained 27.28±21.73% (mean±1 SD of vegetation index variation in the Amazon basin, and this value increased by 12.22% and reached 39.50±27.85% when time lags were considered; (iii vegetation greenness in this region in non-drought years was primarily affected by precipitation and shortwave radiation, and these two factors altogether accounted for 93.47% of the total explanation; and (iv in the common epicenter of the two droughts, pixels with a significant variation in precipitation, radiation and temperature accounted for 36.68%, 40.07% and 10.40%, respectively, of all pixels showing a significant decrease in vegetation index in 2005, and 15.69%, 2.01% and 45.25% in

  12. Analyzing Vegetation Change in an Elephant-Impacted Landscape Using the Moving Standard Deviation Index

    Directory of Open Access Journals (Sweden)

    Timothy J. Fullman

    2014-01-01

    Full Text Available Northern Botswana is influenced by various socio-ecological drivers of landscape change. The African elephant (Loxodonta africana is one of the leading sources of landscape shifts in this region. Developing the ability to assess elephant impacts on savanna vegetation is important to promote effective management strategies. The Moving Standard Deviation Index (MSDI applies a standard deviation calculation to remote sensing imagery to assess degradation of vegetation. Used previously for assessing impacts of livestock on rangelands, we evaluate the ability of the MSDI to detect elephant-modified vegetation along the Chobe riverfront in Botswana, a heavily elephant-impacted landscape. At broad scales, MSDI values are positively related to elephant utilization. At finer scales, using data from 257 sites along the riverfront, MSDI values show a consistent negative relationship with intensity of elephant utilization. We suggest that these differences are due to varying effects of elephants across scales. Elephant utilization of vegetation may increase heterogeneity across the landscape, but decrease it within heavily used patches, resulting in the observed MSDI pattern of divergent trends at different scales. While significant, the low explanatory power of the relationship between the MSDI and elephant utilization suggests the MSDI may have limited use for regional monitoring of elephant impacts.

  13. Vegetation index cartography as a methodology complement to the terroir zoning for its use in precision viticulture

    Directory of Open Access Journals (Sweden)

    Alvaro Martínez

    2017-09-01

    Full Text Available Aim: Precision Viticulture (PV is a form of vineyard management based on tools that offer winegrowers georeferenced information of each vineyard, mainly sector mapping (sub-areas differentiated by characteristics capable of influencing vineyard usage. This provides knowledge of the variations in these sectors and PV treats each one of them in an independent and optimised manner. This allows, amongst many other possibilities, to monitor fruit ripening with the objective of performing site-specific harvest based on the characteristics of each given sector. Local variations in soil features and natural environmental factors, such as climate, lithology, geomorphology and soil, determine the units that drive or limit PV. Methods and results: In this paper, multispectral images are used. These have been obtained between veraison and harvest in three different years in order to calculate four vegetation indexes (VI that have been used since the end of the last century to delimit homogenous sectors in vineyards: the Normalized Difference Vegetation Index (NDVI, the Improved Soil Adjusted Vegetation Index (MSAVI, the Simple Ratio Index (SR and the Modified Simple Ratio Index (MSR. Mapping of these VI has allowed to relate their distribution with natural environmental factors with the objective of valuing their use in the discrimination of homogenous sectors as a complement and/or alternative to traditional methodologies to terroir zoning. Results show that, in the area studied, the vineyards planted in alluvial soil and conglomerated zones, over dominant fine-loamy, mixed, mesic, Calcixerollic Xerochrept soil series, at elevations between 519 and 604 m, oriented east and on slopes less than 5º present higher values for all four indexes throughout the three years of study. Conclusions: It is precisely these environmental elements (lithology, soil, elevation, orientation and slope and many soil features that must be relatively uniform in order to make an

  14. Use of Radar Vegetation Index (RVI) in Passive Microwave Algorithms for Soil Moisture Estimates

    Science.gov (United States)

    Rowlandson, T. L.; Berg, A. A.

    2013-12-01

    The Soil Moisture Active Passive (SMAP) satellite will provide a unique opportunity for the estimation of soil moisture by having simultaneous radar and radiometer measurements available. As with the Soil Moisture and Ocean Salinity (SMOS) satellite, the soil moisture algorithms will need to account for the contribution of vegetation to the brightness temperature. Global maps of vegetation volumetric water content (VWC) are difficult to obtain, and the SMOS mission has opted to estimate the optical depth of standing vegetation by using a relationship between the VWC and the leaf area index (LAI). LAI is estimated from optical remote sensing or through soil-vegetation-atmosphere transfer modeling. During the growing season, the VWC of agricultural crops can increase rapidly, and if cloud cover exists during an optical acquisition, the estimation of LAI may be delayed, resulting in an underestimation of the VWC and overestimation of the soil moisture. Alternatively, the radar vegetation index (RVI) has shown strong correlation and linear relationship with VWC for rice and soybeans. Using the SMAP radar to produce RVI values that are coincident to brightness temperature measurements may eliminate the need for LAI estimates. The SMAP Validation Experiment 2012 (SMAPVEX12) was a cal/val campaign for the SMAP mission held in Manitoba, Canada, during a 6-week period in June and July, 2012. During this campaign, soil moisture measurements were obtained for 55 fields with varying soil texture and vegetation cover. Vegetation was sampled from each field weekly to determine the VWC. Soil moisture measurements were taken coincident to overpasses by an aircraft carrying the Passive and Active L-band System (PALS) instrumentation. The aircraft flew flight lines at both high and low altitudes. The low altitude flight lines provided a footprint size approximately equivalent to the size of the SMAPVEX12 field sites. Of the 55 field sites, the low altitude flight lines provided

  15. The Oslo Health Study: A Dietary Index Estimating Frequent Intake of Soft Drinks and Rare Intake of Fruit and Vegetables Is Negatively Associated with Bone Mineral Density

    Science.gov (United States)

    Høstmark, Arne Torbjørn; Søgaard, Anne Johanne; Alvær, Kari; Meyer, Haakon E.

    2011-01-01

    Background. Since nutritional factors may affect bone mineral density (BMD), we have investigated whether BMD is associated with an index estimating the intake of soft drinks, fruits, and vegetables. Methods. BMD was measured in distal forearm in a subsample of the population-based Oslo Health Study. 2126 subjects had both valid BMD measurements and answered all the questions required for calculating a Dietary Index = the sum of intake estimates of colas and non-cola beverages divided by the sum of intake estimates of fruits and vegetables. We did linear regression analyses to study whether the Dietary Index and the single food items included in the index were associated with BMD. Results. There was a consistent negative association between the Dietary Index and forearm BMD. Among the single index components, colas and non-cola soft drinks were negatively associated with BMD. The negative association between the Dietary Index and BMD prevailed after adjusting for gender, age, and body mass index, length of education, smoking, alcohol intake, and physical activity. Conclusion. An index reflecting frequent intake of soft drinks and rare intake of fruit and vegetables was inversely related to distal forearm bone mineral density. PMID:21772969

  16. Cooling parameters for fruits and vegetables of different sizes in a hydrocooling system

    Directory of Open Access Journals (Sweden)

    Teruel Bárbara

    2004-01-01

    Full Text Available The cooling of fruits and vegetables in hydrocooling system can be a suitable technique. This work aimed to define cooling time for fruits and vegetables of different sizes, presenting practical indexes that could be used to estimate cooling time for produce with similar characteristics. Fruits (orange melon-Cucumis melo, mango-Mangifera indica, guava-Psidium guajava, orange-Citrus sinensis Osbeck, plum-Prunus domestica, lime-Citrus limon, and acerola-Prunus cerasus and vegetables (cucumber-Cucumis sativus, carrot-Daucus carota, and green bean-Phaseolus vulgaris, were cooled in a hydrocooling system at 1°C. The volume of fruits and vegetables ranged between 8.18 cm³ and 1,150.35 cm³, and between 13.06 cm³ and 438.4 cm³, respectively. Cooling time varied proportionally to produce volume (from 8.5 to 124 min for fruits, and from 1.5 to 55 min, for vegetables. The relationship between volume and time needed to cool fruits (from 1.03 min cm-3 to 0.107 min cm-3 and vegetables (from 0.06 min cm-3 to 0.12 min cm-3 is an index that could be used to estimate cooling time for fruits and vegetables with similar dimensions as those presented in this work.

  17. A submonthly database for detecting changes in vegetation-atmosphere coupling

    Science.gov (United States)

    Zscheischler, Jakob; Orth, René; Seneviratne, Sonia I.

    2016-04-01

    Land-atmosphere coupling and changes in coupling regimes are important for making precise future climate predictions and understanding vegetation-climate feedbacks. Here we introduce the Vegetation-Atmosphere Coupling (VAC) index which identifies regions and times of concurrent strong anomalies in temperature and photosynthetic activity. The different classes of the index determine whether a location is currently in an energy-limited or water-limited regime, and its high temporal resolution allows to investigate how these regimes change over time at the regional scale. We show that the VAC index helps to distinguish different evaporative regimes. It can therefore provide indirect information about the local soil moisture state. We further demonstrate how the index can be used to understand processes leading to and occurring during extreme climate events, using the 2010 heat wave in Russia and the 2010 Amazon drought as examples.

  18. Vegetation extraction from high-resolution satellite imagery using the Normalized Difference Vegetation Index (NDVI)

    Science.gov (United States)

    AlShamsi, Meera R.

    2016-10-01

    Over the past years, there has been various urban development all over the UAE. Dubai is one of the cities that experienced rapid growth in both development and population. That growth can have a negative effect on the surrounding environment. Hence, there has been a necessity to protect the environment from these fast pace changes. One of the major impacts this growth can have is on vegetation. As technology is evolving day by day, there is a possibility to monitor changes that are happening on different areas in the world using satellite imagery. The data from these imageries can be utilized to identify vegetation in different areas of an image through a process called vegetation detection. Being able to detect and monitor vegetation is very beneficial for municipal planning and management, and environment authorities. Through this, analysts can monitor vegetation growth in various areas and analyze these changes. By utilizing satellite imagery with the necessary data, different types of vegetation can be studied and analyzed, such as parks, farms, and artificial grass in sports fields. In this paper, vegetation features are detected and extracted through SAFIY system (i.e. the Smart Application for Feature extraction and 3D modeling using high resolution satellite ImagerY) by using high-resolution satellite imagery from DubaiSat-2 and DEIMOS-2 satellites, which provide panchromatic images of 1m resolution and spectral bands (red, green, blue and near infrared) of 4m resolution. SAFIY system is a joint collaboration between MBRSC and DEIMOS Space UK. It uses image-processing algorithms to extract different features (roads, water, vegetation, and buildings) to generate vector maps data. The process to extract green areas (vegetation) utilize spectral information (such as, the red and near infrared bands) from the satellite images. These detected vegetation features will be extracted as vector data in SAFIY system and can be updated and edited by end-users, such as

  19. Inversion of Farmland Soil Moisture in Large Region Based on Modified Vegetation Index

    Science.gov (United States)

    Wang, J. X.; Yu, B. S.; Zhang, G. Z.; Zhao, G. C.; He, S. D.; Luo, W. R.; Zhang, C. C.

    2018-04-01

    Soil moisture is an important parameter for agricultural production. Efficient and accurate monitoring of soil moisture is an important link to ensure the safety of agricultural production. Remote sensing technology has been widely used in agricultural moisture monitoring because of its timeliness, cyclicality, dynamic tracking of changes in things, easy access to data, and extensive monitoring. Vegetation index and surface temperature are important parameters for moisture monitoring. Based on NDVI, this paper introduces land surface temperature and average temperature for optimization. This article takes the soil moisture in winter wheat growing area in Henan Province as the research object, dividing Henan Province into three main regions producing winter wheat and dividing the growth period of winter wheat into the early, middle and late stages on the basis of phenological characteristics and regional characteristics. Introducing appropriate correction factor during the corresponding growth period of winter wheat, correcting the vegetation index in the corresponding area, this paper establishes regression models of soil moisture on NDVI and soil moisture on modified NDVI based on correlation analysis and compare models. It shows that modified NDVI is more suitable as a indicator of soil moisture because of the better correlation between soil moisture and modified NDVI and the higher prediction accuracy of the regression model of soil moisture on modified NDVI. The research in this paper has certain reference value for winter wheat farmland management and decision-making.

  20. [Estimation and Visualization of Nitrogen Content in Citrus Canopy Based on Two Band Vegetation Index (TBVI)].

    Science.gov (United States)

    Wang, Qiao-nan; Ye, Xu-jun; Li, Jin-meng; Xiao, Yu-zhao; He, Yong

    2015-03-01

    Nitrogen is a necessary and important element for the growth and development of fruit orchards. Timely, accurate and nondestructive monitoring of nitrogen status in fruit orchards would help maintain the fruit quality and efficient production of the orchard, and mitigate the pollution of water resources caused by excessive nitrogen fertilization. This study investigated the capability of hyperspectral imagery for estimating and visualizing the nitrogen content in citrus canopy. Hyperspectral images were obtained for leaf samples in laboratory as well as for the whole canopy in the field with ImSpector V10E (Spectral Imaging Ltd., Oulu, Finland). The spectral datas for each leaf sample were represented by the average spectral data extracted from the selected region of interest (ROI) in the hyperspectral images with the aid of ENVI software. The nitrogen content in each leaf sample was measured by the Dumas combustion method with the rapid N cube (Elementar Analytical, Germany). Simple correlation analysis and the two band vegetation index (TBVI) were then used to develop the spectra data-based nitrogen content prediction models. Results obtained through the formula calculation indicated that the model with the two band vegetation index (TBVI) based on the wavelengths 811 and 856 nm achieved the optimal estimation of nitrogen content in citrus leaves (R2 = 0.607 1). Furthermore, the canopy image for the identified TBVI was calculated, and the nitrogen content of the canopy was visualized by incorporating the model into the TBVI image. The tender leaves, middle-aged leaves and elder leaves showed distinct nitrogen status from highto low-levels in the canopy image. The results suggested the potential of hyperspectral imagery for the nondestructive detection and diagnosis of nitrogen status in citrus canopy in real time. Different from previous studies focused on nitrogen content prediction at leaf level, this study succeeded in predicting and visualizing the nutrient

  1. Generating Vegetation Leaf Area Index Earth System Data Record from Multiple Sensors. Part 2; Implementation, Analysis and Validation

    Science.gov (United States)

    Ganguly, Sangram; Samanta, Arindam; Schull, Mitchell A.; Shabanov, Nikolay V.; Milesi, Cristina; Nemani, Ramajrushna R,; Knyazikhin, Yuri; Myneni, Ranga B.

    2008-01-01

    The evaluation of a new global monthly leaf area index (LAI) data set for the period July 1981 to December 2006 derived from AVHRR Normalized Difference Vegetation Index (NDVI) data is described. The physically based algorithm is detailed in the first of the two part series. Here, the implementation, production and evaluation of the data set are described. The data set is evaluated both by direct comparisons to ground data and indirectly through inter-comparisons with similar data sets. This indirect validation showed satisfactory agreement with existing LAI products, importantly MODIS, at a range of spatial scales, and significant correlations with key climate variables in areas where temperature and precipitation limit plant growth. The data set successfully reproduced well-documented spatio-temporal trends and inter-annual variations in vegetation activity in the northern latitudes and semi-arid tropics. Comparison with plot scale field measurements over homogeneous vegetation patches indicated a 7% underestimation when all major vegetation types are taken into account. The error in mean values obtained from distributions of AVHRR LAI and high-resolution field LAI maps for different biomes is within 0.5 LAI for six out of the ten selected sites. These validation exercises though limited by the amount of field data, and thus less than comprehensive, indicated satisfactory agreement between the LAI product and field measurements. Overall, the intercomparison with short-term LAI data sets, evaluation of long term trends with known variations in climate variables, and validation with field measurements together build confidence in the utility of this new 26 year LAI record for long term vegetation monitoring and modeling studies.

  2. Estimating riparian and agricultural evapotranspiration by reference crop evapotranspiration and MODIS Enhanced Vegetation Index

    Science.gov (United States)

    Nagler, Pamela L.; Glenn, Edward P.; Nguyen, Uyen; Scott, Russell; Doody, Tania

    2013-01-01

    Dryland river basins frequently support both irrigated agriculture and riparian vegetation and remote sensing methods are needed to monitor water use by both crops and natural vegetation in irrigation districts. We developed an algorithm for estimating actual evapotranspiration (ETa) based on the Enhanced Vegetation Index (EVI) from the Moderate Resolution Imaging Spectrometer (MODIS) sensor on the EOS-1 Terra satellite and locally-derived measurements of reference crop ET (ETo). The algorithm was calibrated with five years of ETa data from three eddy covariance flux towers set in riparian plant associations on the upper San Pedro River, Arizona, supplemented with ETa data for alfalfa and cotton from the literature. The algorithm was based on an equation of the form ETa = ETo [a(1 − e−bEVI) − c], where the term (1 − e−bEVI) is derived from the Beer-Lambert Law to express light absorption by a canopy, with EVI replacing leaf area index as an estimate of the density of light-absorbing units. The resulting algorithm capably predicted ETa across riparian plants and crops (r2 = 0.73). It was then tested against water balance data for five irrigation districts and flux tower data for two riparian zones for which season-long or multi-year ETa data were available. Predictions were within 10% of measured results in each case, with a non-significant (P = 0.89) difference between mean measured and modeled ETa of 5.4% over all validation sites. Validation and calibration data sets were combined to present a final predictive equation for application across crops and riparian plant associations for monitoring individual irrigation districts or for conducting global water use assessments of mixed agricultural and riparian biomes.

  3. Estimating Riparian and Agricultural Actual Evapotranspiration by Reference Evapotranspiration and MODIS Enhanced Vegetation Index

    Directory of Open Access Journals (Sweden)

    Russell L. Scott

    2013-08-01

    Full Text Available Dryland river basins frequently support both irrigated agriculture and riparian vegetation and remote sensing methods are needed to monitor water use by both crops and natural vegetation in irrigation districts. We developed an algorithm for estimating actual evapotranspiration (ETa based on the Enhanced Vegetation Index (EVI from the Moderate Resolution Imaging Spectrometer (MODIS sensor on the EOS-1 Terra satellite and locally-derived measurements of reference crop ET (ETo. The algorithm was calibrated with five years of ETa data from three eddy covariance flux towers set in riparian plant associations on the upper San Pedro River, Arizona, supplemented with ETa data for alfalfa and cotton from the literature. The algorithm was based on an equation of the form ETa = ETo [a(1 − e−bEVI − c], where the term (1 − e−bEVI is derived from the Beer-Lambert Law to express light absorption by a canopy, with EVI replacing leaf area index as an estimate of the density of light-absorbing units. The resulting algorithm capably predicted ETa across riparian plants and crops (r2 = 0.73. It was then tested against water balance data for five irrigation districts and flux tower data for two riparian zones for which season-long or multi-year ETa data were available. Predictions were within 10% of measured results in each case, with a non-significant (P = 0.89 difference between mean measured and modeled ETa of 5.4% over all validation sites. Validation and calibration data sets were combined to present a final predictive equation for application across crops and riparian plant associations for monitoring individual irrigation districts or for conducting global water use assessments of mixed agricultural and riparian biomes.

  4. Satellite assessment of early-season forecasts for vegetation conditions of grazing allotments in Nevada, United States

    Science.gov (United States)

    Fifteen years of enhanced vegetation index data from the MODIS sensor are examined in conjunction with precipitation and the Palmer drought severity index to assess how well growing season conditions for vegetation within grazing allotments of Nevada can be predicted at different times of the year. ...

  5. Satellite Leaf Area Index: Global Scale Analysis of the Tendencies Per Vegetation Type Over the Last 17 Years

    Directory of Open Access Journals (Sweden)

    Simon Munier

    2018-03-01

    Full Text Available The main objective of this study is to detect and quantify changes in the vegetation dynamics of each vegetation type at the global scale over the last 17 years. With recent advances in remote sensing techniques, it is now possible to study the Leaf Area Index (LAI seasonal and interannual variability at the global scale and in a consistent way over the last decades. However, the coarse spatial resolution of these satellite-derived products does not permit distinguishing vegetation types within mixed pixels. Considering only the dominant type per pixel has two main drawbacks: the LAI of the dominant vegetation type is contaminated by spurious signal from other vegetation types and at the global scale, significant areas of individual vegetation types are neglected. In this study, we first developed a Kalman Filtering (KF approach to disaggregate the satellite-derived LAI from GEOV1 over nine main vegetation types, including grasslands and crops as well as evergreen, broadleaf and coniferous forests. The KF approach permits the separation of distinct LAI values for individual vegetation types that coexist within a pixel. The disaggregated LAI product, called LAI-MC (Multi-Cover, consists of world-wide LAI maps provided every 10 days for each vegetation type over the 1999–2015 period. A trend analysis of the original GEOV1 LAI product and of the disaggregated LAI time series was conducted using the Mann-Kendall test. Resulting trends of the GEOV1 LAI (which accounts for all vegetation types compare well with previous regional or global studies, showing a greening over a large part of the globe. When considering each vegetation type individually, the largest global trend from LAI-MC is found for coniferous forests (0.0419 m 2 m − 2 yr − 1 followed by summer crops (0.0394 m 2 m − 2 yr − 1 , while winter crops and grasslands show the smallest global trends (0.0261 m 2 m − 2 yr − 1 and 0.0279 m 2 m − 2 yr − 1 , respectively. The LAI

  6. Interannual variability of the normalized difference vegetation index on the Tibetan Plateau and its relationship with climate change

    Science.gov (United States)

    Zhou, Dingwen; Fan, Guangzhou; Huang, Ronghui; Fang, Zhifang; Liu, Yaqin; Li, Hongquan

    2007-05-01

    The Qinghai-Xizang Plateau, or Tibetan Plateau, is a sensitive region for climate change, where the manifestation of global warming is particularly noticeable. The wide climate variability in this region significantly affects the local land ecosystem and could consequently lead to notable vegetation changes. In this paper, the interannual variations of the plateau vegetation are investigated using a 21-year normalized difference vegetation index (NDVI) dataset to quantify the consequences of climate warming for the regional ecosystem and its interactions. The results show that vegetation coverage is best in the eastern and southern plateau regions and deteriorates toward the west and north. On the whole, vegetation activity demonstrates a gradual enhancement in an oscillatory manner during 1982 2002. The temporal variation also exhibits striking regional differences: an increasing trend is most apparent in the west, south, north and southeast, whereas a decreasing trend is present along the southern plateau boundary and in the central-east region. Covariance analysis between the NDVI and surface temperature/precipitation suggests that vegetation change is closely related to climate change. However, the controlling physical processes vary geographically. In the west and east, vegetation variability is found to be driven predominantly by temperature, with the impact of precipitation being of secondary importance. In the central plateau, however, temperature and precipitation factors are equally important in modulating the interannual vegetation variability.

  7. Climatic drivers of vegetation based on wavelet analysis

    Science.gov (United States)

    Claessen, Jeroen; Martens, Brecht; Verhoest, Niko E. C.; Molini, Annalisa; Miralles, Diego

    2017-04-01

    Vegetation dynamics are driven by climate, and at the same time they play a key role in forcing the different bio-geochemical cycles. As climate change leads to an increase in frequency and intensity of hydro-meteorological extremes, vegetation is expected to respond to these changes, and subsequently feed back on their occurrence. This response can be analysed using time series of different vegetation diagnostics observed from space, in the optical (e.g. Normalised Difference Vegetation Index (NDVI), Solar Induced Fluorescence (SIF)) and microwave (Vegetation Optical Depth (VOD)) domains. In this contribution, we compare the climatic drivers of different vegetation diagnostics, based on a monthly global data-cube of 24 years at a 0.25° resolution. To do so, we calculate the wavelet coherence between each vegetation-related observation and observations of air temperature, precipitation and incoming radiation. The use of wavelet coherence allows unveiling the scale-by-scale response and sensitivity of the diverse vegetation indices to their climatic drivers. Our preliminary results show that the wavelet-based statistics prove to be a suitable tool for extracting information from different vegetation indices. Going beyond traditional methods based on linear correlations, the application of wavelet coherence provides information about: (a) the specific periods at which the correspondence between climate and vegetation dynamics is larger, (b) the frequencies at which this correspondence occurs (e.g. monthly or seasonal scales), and (c) the time lag in the response of vegetation to their climate drivers, and vice versa. As expected, areas of high rainfall volumes are characterised by a strong control of radiation and temperature over vegetation. Furthermore, precipitation is the most important driver of vegetation variability over short terms in most regions of the world - which can be explained by the rapid response of leaf development towards available water content

  8. Estimating the Fractional Vegetation Cover from GLASS Leaf Area Index Product

    Directory of Open Access Journals (Sweden)

    Zhiqiang Xiao

    2016-04-01

    Full Text Available The fractional vegetation cover (FCover is an essential biophysical variable and plays a critical role in the carbon cycle studies. Existing FCover products from satellite observations are spatially incomplete and temporally discontinuous, and also inaccurate for some vegetation types to meet the requirements of various applications. In this study, an operational method is proposed to calculate high-quality, accurate FCover from the Global LAnd Surface Satellite (GLASS leaf area index (LAI product to ensure physical consistency between LAI and FCover retrievals. As a result, a global FCover product (denoted by TRAGL were generated from the GLASS LAI product from 2000 to present. With no missing values, the TRAGL FCover product is spatially complete. A comparison of the TRAGL FCover product with the Geoland2/BioPar version 1 (GEOV1 FCover product indicates that these FCover products exhibit similar spatial distribution pattern. However, there were relatively large discrepancies between these FCover products over equatorial rainforests, broadleaf crops in East-central United States, and needleleaf forests in Europe and Siberia. Temporal consistency analysis indicates that TRAGL FCover product has continuous trajectories. Direct validation with ground-based FCover estimates demonstrated that TRAGL FCover values were more accurate (RMSE = 0.0865, and R2 = 0.8848 than GEOV1 (RMSE = 0.1541, and R2 = 0.7621.

  9. VIP Data Explorer: A Tool for Exploring 30 years of Vegetation Index and Phenology Observations

    Science.gov (United States)

    Barreto-munoz, A.; Didan, K.; Rivera-Camacho, J.; Yitayew, M.; Miura, T.; Tsend-Ayush, J.

    2011-12-01

    Continuous acquisition of global satellite imagery over the years has contributed to the creation of long term data records from AVHRR, MODIS, TM, SPOT-VGT and other sensors. These records account for 30+ years, as these archives grow, they become invaluable tools for environmental, resources management, and climate studies dealing with trends and changes from local, regional to global scale. In this project, the Vegetation Index and Phenology Lab (VIPLab) is processing 30 years of daily global surface reflectance data into an Earth Science Data Record of Vegetation Index and Phenology metrics. Data from AVHRR (N07,N09,N11 and N14) and MODIS (AQUA and TERRA collection 5) for the periods 1981-1999 and 2000-2010, at CMG resolution were processed into one seamless and sensor independent data record using various filtering, continuity and gap filling techniques (Tsend-Ayush et al., AGU 2011, Rivera-Camacho et al, AGU 2011). An interactive online tool (VIP Data Explorer) was developed to support the visualization, qualitative and quantitative exploration, distribution, and documentation of these records using a simple web 2.0 interface. The VIP Data explorer (http://vip.arizona.edu/viplab_data_explorer) can display any combination of multi temporal and multi source data, enable the quickly exploration and cross comparison of the various levels of processing of this data. It uses the Google Earth (GE) model and was developed using the GE API for images rendering, manipulation and geolocation. These ESDRs records can be quickly animated in this environment and explored for visual trends and anomalies detection. Additionally the tool enables extracting and visualizing any land pixel time series while showing the different levels of processing it went through. User can explore this ESDR database within this data explorer GUI environment, and any desired data can be placed into a dynamic "cart" to be ordered and downloaded later. More functionalities are planned and will be

  10. Evaluating the quality of riparian forest vegetation: the Riparian Forest Evaluation (RFV index

    Directory of Open Access Journals (Sweden)

    Fernando Magdaleno

    2014-08-01

    Full Text Available Aim of study: This paper presents a novel index, the Riparian Forest Evaluation (RFV index, for assessing the ecological condition of riparian forests. The status of riparian ecosystems has global importance due to the ecological and social benefits and services they provide. The initiation of the European Water Framework Directive (2000/60/CE requires the assessment of the hydromorphological quality of natural channels. The Directive describes riparian forests as one of the fundamental components that determine the structure of riverine areas. The RFV index was developed to meet the aim of the Directive and to complement the existing methodologies for the evaluation of riparian forests.Area of study: The RFV index was applied to a wide range of streams and rivers (170 water bodies inSpain.Materials and methods: The calculation of the RFV index is based on the assessment of both the spatial continuity of the forest (in its three core dimensions: longitudinal, transversal and vertical and the regeneration capacity of the forest, in a sampling area related to the river hydromorphological pattern. This index enables an evaluation of the quality and degree of alteration of riparian forests. In addition, it helps to determine the scenarios that are necessary to improve the status of riparian forests and to develop processes for restoring their structure and composition.Main results: The results were compared with some previous tools for the assessment of riparian vegetation. The RFV index got the highest average scores in the basins of northernSpain, which suffer lower human influence. The forests in central and southern rivers got worse scores. The bigger differences with other tools were found in complex and partially altered streams and rivers.Research highlights: The study showed the index’s applicability under diverse hydromorphological and ecological conditions and the main advantages of its application. The utilization of the index allows a

  11. Sixteen years of agricultural drought assessment of the BioBío region in Chile using a 250 m resolution Vegetation Condition Index (VCI)

    Science.gov (United States)

    Zambrano, Francisco; Lillo-Saavedra, Mario; Verbist, Koen; Lagos, Octavio

    2016-10-01

    Drought is one of the most complex natural hazards because of its slow onset and long-term impact; it has the potential to negatively affect many people. There are several advantages to using remote sensing to monitor drought, especially in developing countries with limited historical meteorological records and a low weather station density. In the present study, we assessed agricultural drought in the croplands of the BioBio Region in Chile. The vegetation condition index (VCI) allows identifying the temporal and spatial variations of vegetation conditions associated with stress because of rainfall deficit. The VCI was derived at a 250m spatial resolution for the 2000-2015 period with the Moderate Resolution Imaging Spectroradiometer (MODIS) MOD13Q1 product. We evaluated VCI for cropland areas using the land cover MCD12Q1 version 5.1 product and compared it to the in situ Standardized Precipitation Index (SPI) for six-time scales (1-6 months) from 26 weather stations. Results showed that the 3-month SPI (SPI-3), calculated for the modified growing season (Nov-Apr) instead of the regular growing season (Sept-Apr), has the best Pearson correlation with VCI values with an overall correlation of 0.63 and between 0.40 and 0.78 for the administrative units. These results show a very short-term vegetation response to rainfall deficit in September, which is reflected in the vegetation in November, and also explains to a large degree the variation in vegetation stress. It is shown that for the last 16 years in the BioBio Region we could identify the 2007/2008, 2008/2009, and 2014/2015 seasons as the three most important drought events; this is reflected in both the overall regional and administrative unit analyses. These results concur with drought emergencies declared by the regional government. Future studies are needed to associate the remote sensing values observed at high resolution (250m) with the measured crop yield to identify more detailed individual crop

  12. Study of a Vegetation Index Based on HJ CCD Data's top-of-atmosphere reflectance and FPAR Inversion

    International Nuclear Information System (INIS)

    Dong, Taifeng; Wu, Bingfang; Meng, Jihua

    2014-01-01

    The Fraction of Photosynthetically Active Radiation (FPAR)absorbed by plant canopies is a key parameter for monitoring crop condition and estimating crop yield. In general, it is necessary to obtain Top of Canopy (TOC) reflectance from optical remote sensing data in digital number through atmospheric correction procedures before retrieving FPAR. However, there are a few of uncertainties that existe in the process of atmosphere correction and reduced the quality of TOC. This paper presents a vegetation index based on Top-of-Atmosphere (TOA) reflectance derived from HJ-1 CCD satellite for estimating direct crop FPAR. The vegetation index (HJVI) was designed based on the simulated results of a canopy-atmosphere radiative transfer model, including TOA reflectance and corresponded FPAR. The HJVI had taken the advantages of information in the green, the red and the near-infrared spectral domainswith with a aim of reducing the atmospheric effect and enhancing the sensitive to green vegetation. The HJVI was used to estimate soybean FPAR directly and validated using field measurements. The result indicated that the inversion algorithm produced a good relationship between the prediction and measurement (R 2 = 0.546, RMSE = 0.083) and the HJVI showed high potential for estimating FPAR based on the HJ-1 TOA reflectance directly

  13. Assessing Land Degradation and Desertification Using Vegetation Index Data: Current Frameworks and Future Directions

    Directory of Open Access Journals (Sweden)

    Thomas P. Higginbottom

    2014-10-01

    Full Text Available Land degradation and desertification has been ranked as a major environmental and social issue for the coming decades. Thus, the observation and early detection of degradation is a primary objective for a number of scientific and policy organisations, with remote sensing methods being a candidate choice for the development of monitoring systems. This paper reviews the statistical and ecological frameworks of assessing land degradation and desertification using vegetation index data. The development of multi-temporal analysis as a desertification assessment technique is reviewed, with a focus on how current practice has been shaped by controversy and dispute within the literature. The statistical techniques commonly employed are examined from both a statistical as well as ecological point of view, and recommendations are made for future research directions. The scientific requirements for degradation and desertification monitoring systems identified here are: (I the validation of methodologies in a robust and comparable manner; and (II the detection of degradation at minor intensities and magnitudes. It is also established that the multi-temporal analysis of vegetation index data can provide a sophisticated measure of ecosystem health and variation, and that, over the last 30 years, considerable progress has been made in the respective research.

  14. Normalized difference vegetation index (ndvi) analysis for land cover types using landsat 8 oli in besitang watershed, Indonesia

    Science.gov (United States)

    Zaitunah, A.; Samsuri; Ahmad, A. G.; Safitri, R. A.

    2018-03-01

    Watershed is an ecosystem area confined by topography and has function as a catcher, storage, and supplier of water, sediments, pollutants and nutrients in the river system and exit through a single outlet. Various activities around watershed areas of Besitang have changed the land cover and vegetation index (NDVI) that exist in the region. In order to detect changes in land cover and NDVI quickly and accurately, we used remote sensing technology and geographic information systems (GIS). The study aimed to assess changes in land cover and vegetation density (NDVI) between 2005 and 2015, as well as obtaining the density of vegetation (NDVI) on each of the land cover of 2005 and 2015. The research showed the extensive of forest area of 949.65 Ha and a decline of mangrove forest area covering an area of 2,884.06 Ha. The highest vegetation density reduced 39,714.58 Ha, and rather dense increased 24,410.72 Ha between 2005 and 2015. The land cover that have the highest NDVI value range with very dense vegetation density class is the primary dry forest (0.804 to 0.876), followed by secondary dry forest (0.737 to 0.804) for 2015. In 2015 the land cover has NDVI value range the primary dry forest (0.513 to 0.57), then secondary dry forest (0.456 to 0.513) with dense vegetation density class

  15. A MODIS-based vegetation index climatology

    Science.gov (United States)

    Our motivation here is to provide information for the NASA Soil Moisture Active Passive (SMAP) satellite soil moisture retrieval algorithms (launch in 2014). Vegetation attenuates the signal and the algorithms must correct for this effect. One approach is to use data that describes the canopy water ...

  16. Relationships between declining summer sea ice, increasing temperatures and changing vegetation in the Siberian Arctic tundra from MODIS time series (2000–11)

    International Nuclear Information System (INIS)

    Dutrieux, L P; Bartholomeus, H; Herold, M; Verbesselt, J

    2012-01-01

    The concern about Arctic greening has grown recently as the phenomenon is thought to have significant influence on global climate via atmospheric carbon emissions. Earlier work on Arctic vegetation highlighted the role of summer sea ice decline in the enhanced warming and greening phenomena observed in the region, but did not contain enough details for spatially characterizing the interactions between sea ice, temperature and vegetation photosynthetic absorption. By using 1 km resolution data from the Moderate Resolution Imaging Spectrometer (MODIS) as a primary data source, this study presents detailed maps of vegetation and temperature trends for the Siberian Arctic region, using the time integrated normalized difference vegetation index (TI-NDVI) and summer warmth index (SWI) calculated for the period 2000–11 to represent vegetation greenness and temperature respectively. Spatio-temporal relationships between the two indices and summer sea ice conditions were investigated with transects at eight locations using sea ice concentration data from the Special Sensor Microwave/Imager (SSM/I). In addition, the derived vegetation and temperature trends were compared among major Arctic vegetation types and bioclimate subzones. The fine resolution trend map produced confirms the overall greening (+1% yr −1 ) and warming (+0.27% yr −1 ) of the region, reported in previous studies, but also reveals browning areas. The causes of such local decreases in vegetation, while surrounding areas are experiencing the opposite reaction to changing conditions, are still unclear. Overall correlations between sea ice concentration and SWI as well as TI-NDVI decreased in strength with increasing distance from the coast, with a particularly pronounced pattern in the case of SWI. SWI appears to be driving TI-NDVI in many cases, but not systematically, highlighting the presence of limiting factors other than temperature for plant growth in the region. Further unravelling those limiting

  17. Post-fire vegetation recovery in Portugal based on spot/vegetation data

    Science.gov (United States)

    Gouveia, C.; Dacamara, C. C.; Trigo, R. M.

    2010-04-01

    A procedure is presented that allows identifying large burned scars and the monitoring of vegetation recovery in the years following major fire episodes. The procedure relies on 10-day fields of Maximum Value Composites of Normalized Difference Vegetation Index (MVC-NDVI), with a 1 km×1 km spatial resolution obtained from the VEGETATION instrument. The identification of fire scars during the extremely severe 2003 fire season is performed based on cluster analysis of NDVI anomalies that persist during the vegetative cycle of the year following the fire event. Two regions containing very large burned scars were selected, located in Central and Southwestern Portugal, respectively, and time series of MVC-NDVI analysed before the fire events took place and throughout the post-fire period. It is shown that post-fire vegetation dynamics in the two selected regions may be characterised based on maps of recovery rates as estimated by fitting a monoparametric model of vegetation recovery to MVC-NDVI data over each burned scar. Results indicated that the recovery process in the region located in Central Portugal is mostly related to fire damage rather than to vegetation density before 2003, whereas the latter seems to have a more prominent role than vegetation conditions after the fire episode, e.g. in the case of the region in Southwestern Portugal. These differences are consistent with the respective predominant types of vegetation. The burned area located in Central Portugal is dominated by Pinus Pinaster whose natural regeneration crucially depends on the destruction of seeds present on the soil surface during the fire, whereas the burned scar in Southwestern Portugal was populated by Eucalyptus that may quickly re-sprout from buds after fire. Besides its simplicity, the monoparametric model of vegetation recovery has the advantage of being easily adapted to other low-resolution satellite data, as well as to other types of vegetation indices.

  18. Multifractal Downscaling of Rainfall Using Normalized Difference Vegetation Index (NDVI) in the Andes Plateau.

    Science.gov (United States)

    Duffaut Espinosa, L A; Posadas, A N; Carbajal, M; Quiroz, R

    2017-01-01

    In this paper, a multifractal downscaling technique is applied to adequately transformed and lag corrected normalized difference vegetation index (NDVI) in order to obtain daily estimates of rainfall in an area of the Peruvian Andean high plateau. This downscaling procedure is temporal in nature since the original NDVI information is provided at an irregular temporal sampling period between 8 and 11 days, and the desired final scale is 1 day. The spatial resolution of approximately 1 km remains the same throughout the downscaling process. The results were validated against on-site measurements of meteorological stations distributed in the area under study.

  19. The environmental vegetation index: A tool potentially useful for arid land management. [Texas and Mexico, plant growth stress due to water deficits

    Science.gov (United States)

    Gray, T. I., Jr.; Mccrary, D. G. (Principal Investigator)

    1981-01-01

    The NOAA-6 AVHRR data sets acquired over South Texas and Mexico during the spring of 1980 and after Hurricane Allen passed inland are analyzed. These data were processed to produce the Gray-McCrary Index (GMI's) for each pixel location over the selected area, which area contained rangeland and cropland, both irrigated and nonirrigated. The variations in the GMI's appear to reflect well the availability of water for vegetation. The GMI area maps are shown to delineate and to aid in defining the duration of drought; suggesting the possibility that time changes over a selected area could be useful for irrigation management.

  20. A real-time Global Warming Index.

    Science.gov (United States)

    Haustein, K; Allen, M R; Forster, P M; Otto, F E L; Mitchell, D M; Matthews, H D; Frame, D J

    2017-11-13

    We propose a simple real-time index of global human-induced warming and assess its robustness to uncertainties in climate forcing and short-term climate fluctuations. This index provides improved scientific context for temperature stabilisation targets and has the potential to decrease the volatility of climate policy. We quantify uncertainties arising from temperature observations, climate radiative forcings, internal variability and the model response. Our index and the associated rate of human-induced warming is compatible with a range of other more sophisticated methods to estimate the human contribution to observed global temperature change.

  1. A simple model for yield prediction of rice based on vegetation index derived from satellite and AMeDAS data during ripening period

    International Nuclear Information System (INIS)

    Wakiyama, Y.; Inoue, K.; Nakazono, K.

    2003-01-01

    The present study was conducted to show a simple model for rice yield predicting by using a vegetation index (NDVI) derived from satellite and meteorological data. In a field experiment, the relationship between the vegetation index and radiation absorbed by the rice canopy was investigated from transplanting to maturity. Their correlation held. This result revealed that the vegetation index could be used as a measure of absorptance of solar radiation by rice canopy. NDVI multiplied by solar radiation (SR) every day was accumulated (Σ(SR·NDVI)) from the field experiment. Σ(SR·NDVI) was plotted against above ground dry matter. It was obvious that they had a strong relationship. Rice yield largely depends on solar radiation and air temperature during the ripening period. Air temperature affects dry matter production. Relationships between Y SR -1 (Y: rice yield, SR: solar radiation) and mean air temperature were investigated from meteorological data and statistical data on rice yield. There was an optimum air temperature, 21.3°C, for ripening. When it was near 21.3°C in the ripening period, the rice yield was higher. We proposed a simple model for yield prediction of rice based on these results. The model is composed with SR·NDVI and the optimum air temperature. Vegetation index was derived from 3 years, LANDSAT TM data in Toyama, Ishikawa, Fukui and Nagano prefectures at heading. The meteorological data was used from AMeDAS data. The model was described as follows: Y = 0.728 SR·NDVI−2.04(T−21.3) 2 + 282 (r 2 = 0.65, n = 43) where Y is rice yield (kg 10a -1 ), SR is solar radiation (MJ m -2 ) during the ripening period (from 10 days before heading to 30 days after heading), T is mean air temperature (°C) during the ripening period. RMSE was 33.7kg 10a -1 . The model revealed good precision. (author)

  2. [Differences of vegetation phenology monitoring by remote sensing based on different spectral vegetation indices.

    Science.gov (United States)

    Zuo, Lu; Wang, Huan Jiong; Liu, Rong Gao; Liu, Yang; Shang, Rong

    2018-02-01

    Vegetation phenology is a comprehensive indictor for the responses of terrestrial ecosystem to climatic and environmental changes. Remote sensing spectrum has been widely used in the extraction of vegetation phenology information. However, there are many differences between phenology extracted by remote sensing and site observations, with their physical meaning remaining unclear. We selected one tile of MODIS data in northeastern China (2000-2014) to examine the SOS and EOS differences derived from the normalized difference vegetation index (NDVI) and the simple ratio vegetation index (SR) based on both the red and near-infrared bands. The results showed that there were significant differences between NDVI-phenology and SR-phenology. SOS derived from NDVI averaged 18.9 days earlier than that from SR. EOS derived from NDVI averaged 19.0 days later than from SR. NDVI-phenology had a longer growing season. There were significant differences in the inter-annual variation of phenology from NDVI and SR. More than 20% of the pixel SOS and EOS derived from NDVI and SR showed the opposite temporal trend. These results caused by the seasonal curve characteristics and noise resistance differences of NDVI and SR. The observed data source of NDVI and SR were completely consistent, only the mathematical expressions were different, but phenology results were significantly different. Our results indicated that vegetation phenology monitoring by remote sensing is highly dependent on the mathematical expression of vegetation index. How to establish a reliable method for extracting vegetation phenology by remote sensing needs further research.

  3. Mapping swamp timothy (Cripsis schenoides) seed productivity using spectral values and vegetation indices in managed wetlands

    Energy Technology Data Exchange (ETDEWEB)

    Rahilly, P.J.A.; Li, D.; Guo, Q.; Zhu, J.; Ortega, R.; Quinn, N.W.T.; Harmon, T.C.

    2010-01-15

    This work examines the potential to predict the seed productivity of a key wetland plant species using spectral reflectance values and spectral vegetation indices. Specifically, the seed productivity of swamp timothy (Cripsis schenoides) was investigated in two wetland ponds, managed for waterfowl habitat, in California's San Joaquin Valley. Spectral reflectance values were obtained and associated spectral vegetation indices (SVI) calculated from two sets of high resolution aerial images (May 11, 2006 and June 9, 2006) and were compared to the collected vegetation data. Vegetation data were collected and analyzed from 156 plots for total aboveground biomass, total aboveground swamp timothy biomass, and total swamp timothy seed biomass. The SVI investigated included the Simple Ratio (SR), Normalized Difference Vegetation Index (NDVI), Soil Adjusted Vegetation Index (SAVI), Transformed Soil Adjusted Vegetation Index (TSAVI), Modified Soil Adjusted Vegetation Index (MSAVI), and Global Environment Monitoring Index (GEMI). We evaluated the correlation of the various SVI with in situ vegetation measurements for linear, quadratic, exponential and power functions. In all cases, the June image provided better predictive capacity relative to May, a result that underscores the importance of timing imagery to coincide with more favorable vegetation maturity. The north pond with the June image using SR and the exponential function (R{sup 2}=0.603) proved to be the best predictor of swamp timothy seed productivity. The June image for the south pond was less predictive, with TSAVI and the exponential function providing the best correlation (R{sup 2}=0.448). This result was attributed to insufficient vegetal cover in the south pond (or a higher percentage of bare soil) due to poor drainage conditions which resulted in a delay in swamp timothy germination. The results of this work suggest that spectral reflectance can be used to estimate seed productivity in managed seasonal

  4. Simulating Visible/Infrared Imager Radiometer Suite Normalized Difference Vegetation Index Data Using Hyperion and MODIS

    Science.gov (United States)

    Ross, Kenton W.; Russell, Jeffrey; Ryan, Robert E.

    2006-01-01

    The success of MODIS (the Moderate Resolution Imaging Spectrometer) in creating unprecedented, timely, high-quality data for vegetation and other studies has created great anticipation for data from VIIRS (the Visible/Infrared Imager Radiometer Suite). VIIRS will be carried onboard the joint NASA/Department of Defense/National Oceanic and Atmospheric Administration NPP (NPOESS (National Polar-orbiting Operational Environmental Satellite System) Preparatory Project). Because the VIIRS instruments will have lower spatial resolution than the current MODIS instruments 400 m versus 250 m at nadir for the channels used to generate Normalized Difference Vegetation Index data, scientists need the answer to this question: how will the change in resolution affect vegetation studies? By using simulated VIIRS measurements, this question may be answered before the VIIRS instruments are deployed in space. Using simulated VIIRS products, the U.S. Department of Agriculture and other operational agencies can then modify their decision support systems appropriately in preparation for receipt of actual VIIRS data. VIIRS simulations and validations will be based on the ART (Application Research Toolbox), an integrated set of algorithms and models developed in MATLAB(Registerd TradeMark) that enables users to perform a suite of simulations and statistical trade studies on remote sensing systems. Specifically, the ART provides the capability to generate simulated multispectral image products, at various scales, from high spatial hyperspectral and/or multispectral image products. The ART uses acquired ( real ) or synthetic datasets, along with sensor specifications, to create simulated datasets. For existing multispectral sensor systems, the simulated data products are used for comparison, verification, and validation of the simulated system s actual products. VIIRS simulations will be performed using Hyperion and MODIS datasets. The hyperspectral and hyperspatial properties of Hyperion

  5. Seasonality in ENSO-related precipitation, river discharges, soil moisture, and vegetation index in Colombia

    Science.gov (United States)

    Poveda, GermáN.; Jaramillo, Alvaro; Gil, Marta MaríA.; Quiceno, Natalia; Mantilla, Ricardo I.

    2001-08-01

    An analysis of hydrologic variability in Colombia shows different seasonal effects associated with El Niño/Southern Oscillation (ENSO) phenomenon. Spectral and cross-correlation analyses are developed between climatic indices of the tropical Pacific Ocean and the annual cycle of Colombia's hydrology: precipitation, river flows, soil moisture, and the Normalized Difference Vegetation Index (NDVI). Our findings indicate stronger anomalies during December-February and weaker during March-May. The effects of ENSO are stronger for streamflow than for precipitation, owing to concomitant effects on soil moisture and evapotranspiration. We studied time variability of 10-day average volumetric soil moisture, collected at the tropical Andes of central Colombia at depths of 20 and 40 cm, in coffee growing areas characterized by shading vegetation ("shaded coffee"), forest, and sunlit coffee. The annual and interannual variability of soil moisture are highly intertwined for the period 1997-1999, during strong El Niño and La Niña events. Soil moisture exhibited greater negative anomalies during 1997-1998 El Niño, being strongest during the two dry seasons that normally occur in central Colombia. Soil moisture deficits were more drastic at zones covered by sunlit coffee than at those covered by forest and shaded coffee. Soil moisture responds to wetter than normal precipitation conditions during La Niña 1998-1999, reaching maximum levels throughout that period. The probability density function of soil moisture records is highly skewed and exhibits different kinds of multimodality depending upon land cover type. NDVI exhibits strong negative anomalies throughout the year during El Niños, in particular during September-November (year 0) and June-August (year 0). The strong negative relation between NDVI and El Niño has enormous implications for carbon, water, and energy budgets over the region, including the tropical Andes and Amazon River basin.

  6. A MODIS-based begetation index climatology

    Science.gov (United States)

    Passive microwave soil moisture algorithms must account for vegetation attenuation of the signal in the retrieval process. One approach to accounting for vegetation is to use vegetation indices such as the Normalized Difference Vegetation Index (NDVI) to estimate the vegetation optical depth. The pa...

  7. Soil Erosion Risk Map based on irregularity of the vegetative activity

    Science.gov (United States)

    Saa-Requejo, Antonio; Tarquis, Ana Maria; Martín-Sotoca, Juan J.; Valencia, Jose L.; Gobin, Anne; Rodriguez-Sinobas, Leonor

    2016-04-01

    Because of the difficulties to build on both daily rainfall and base shorter time, we explored the possibilities of building indexes based on land cover, which also provide us the opportunity to evaluate their evolution over time. We consider the Fournier index (Fournier, 1960) which is used to assess the rainfall erosivity based on monthly rainfall, alternatively to use of the rainfall intensity in time bases under one hour (eg., van der Knijff et al., 1999; Shamshad et al, 2008). This index can also be interpreted as an index of irregularity and representing a ratio between maximum monthly precipitation and annual rainfall. We propose to calculate this irregularity in terms of irregularity of the vegetative activity. This activity is related to precipitation, but also with the availability of water in the soil reservoir and land use. Therefore, we propose a kind of Fournier index on the effective use of water, which is also closely related to variations in infiltration. Higher is the presence of vegetation higher is the effective use of water. For this "modified Fourier index" we used the NDVI (Normalized Difference Vegetation Index) as index of available vegetative activity, which is widely reported in the literature (Jensen, 2000). Initial calculations have been done with MODIS 500 x 500 m satellite data. The selected area was Cega-Eresma-Adaja subbasin during the period from 2009 to 2012. We selected 8 days composite images product. The calculation of the valid values to eliminate areas with clouds or snow is performed according to the criteria of Martinez Sotoca (2014), ie with a Saturation (based on HSL color model) greater or equal to 0.15. Then, an average of these values was estimated to represent each month of the year. The results are very interesting when we compare Modified Fournier Index on NDVIs with the map of potential soil loss. We have found surprisingly similar patterns and practical equivalence between several classes. Therefore, the Modified

  8. Mapping and characterizing the vegetation types of the Democratic Republic of Congo using SPOT VEGETATION time series

    Science.gov (United States)

    Vancutsem, C.; Pekel, J.-F.; Evrard, C.; Malaisse, F.; Defourny, P.

    2009-02-01

    The need for quantitative and accurate information to characterize the state and evolution of vegetation types at a national scale is widely recognized. This type of information is crucial for the Democratic Republic of Congo, which contains the majority of the tropical forest cover of Central Africa and a large diversity of habitats. In spite of recent progress in earth observation capabilities, vegetation mapping and seasonality analysis in equatorial areas still represent an outstanding challenge owing to high cloud coverage and the extent and limited accessibility of the territory. On one hand, the use of coarse-resolution optical data is constrained by performance in the presence of cloud screening and by noise arising from the compositing process, which limits the spatial consistency of the composite and the temporal resolution. On the other hand, the use of high-resolution data suffers from heterogeneity of acquisition dates, images and interpretation from one scene to another. The objective of the present study was to propose and demonstrate a semi-automatic processing method for vegetation mapping and seasonality characterization based on temporal and spectral information from SPOT VEGETATION time series. A land cover map with 18 vegetation classes was produced using the proposed method that was fed by ecological knowledge gathered from botanists and reference documents. The floristic composition and physiognomy of each vegetation type are described using the Land Cover Classification System developed by the FAO. Moreover, the seasonality of each class is characterized on a monthly basis and the variation in different vegetation indicators is discussed from a phenological point of view. This mapping exercise delivers the first area estimates of seven different forest types, five different savannas characterized by specific seasonality behavior and two aquatic vegetation types. Finally, the result is compared to two recent land cover maps derived from

  9. Phenological characteristics of the main vegetation types on the Tibetan Plateau based on vegetation and water indices

    International Nuclear Information System (INIS)

    Peng, D L; Huang, W J; Zhou, B; Li, C J; Wu, Y P; Yang, X H

    2014-01-01

    Plant phenology is considered one of the most sensitive and easily observable natural indicators of climate change, though few studies have focused on the heterogeneities of phenology across the different vegetation types. In this study, we tried to find the phenological characteristics of the main vegetation types on the Tibetan Plateau. MCD12Q1 images over the Tibetan Plateau from 2001 to 2010 were used to extract the main vegetation types. The Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), and Land Surface Water Index (LSWI) were calculated using surface reflectance values from the blue, red, near-infrared, short-wave infrared (SWIR) 6 (for LSIW6), and SWIR7 (for LSIW7) bands derived from MOD09A1 and used to explore the phenological characteristics of the main vegetation types on the Tibetan Plateau. The results showed that there were eight constant vegetation types on the Tibetan Plateau from 2001 to 2010 demonstrating multiple phenological characteristics. Evergreen needleleaf forest, evergreen broadleaf forest, and permanent wetland had the minimum NDVI values during the summer season, while open shrubland and grassland had the maximum NDVI/EVI values during this period. NDVI and EVI of cropland/natural vegetation had two peaks for their seasonal variations. EVI showed a more significant correlation with LSWI6/LSWI7 than NDVI. Compared to LSWI7, larger EVI values occurred in evergreen needleleaf forest, evergreen broadleaf forest, mixed forest, and permanent wetland, while smaller values occurred in shrubland and barren or sparsely vegetated cover, and nearly equal values occurred in grassland and cropland

  10. Leaf area index retrieval using Hyperion EO-1 data-based vegetation indices in Himalayan forest system

    Science.gov (United States)

    Singh, Dharmendra; Singh, Sarnam

    2016-04-01

    Present Study is being taken to retrieve Leaf Area Indexn(LAI) in Himalayan forest system using vegetation indices developed from Hyperion EO-1 hyperspectral data. Hemispherical photograph were captured in the month of March and April, 2012 at 40 locations, covering moist tropical Sal forest, subtropical Bauhinia and pine forest and temperate Oak forest and analysed using an open source GLA software. LAI in the study region was ranging in between 0.076 m2/m2 to 6.00 m2/m2. These LAI values were used to develop spectral models with the FLAASH corrected Hyperion measurements.Normalized difference vegetation index (NDVI) was used taking spectral reflectance values of all the possible combinations of 170 atmospherically corrected channels. The R2 was ranging from lowest 0.0 to highest 0.837 for the band combinations of spectral region 640 nm and 670 nm. The spectral model obtained was, spectral reflectance (y) = 0.02x LAI(x) - 0.0407.

  11. Comparing MODIS and near-surface vegetation indexes for monitoring tropical dry forest phenology along a successional gradient using optical phenology towers

    Science.gov (United States)

    Rankine, C.; Sánchez-Azofeifa, G. A.; Guzmán, J. Antonio; Espirito-Santo, M. M.; Sharp, Iain

    2017-10-01

    Tropical dry forests (TDFs) present strong seasonal greenness signals ideal for tracking phenology and primary productivity using remote sensing techniques. The tightly synchronized relationship these ecosystems have with water availability offer a valuable natural experiment for observing the complex interactions between the atmosphere and the biosphere in the tropics. To investigate how well the MODIS vegetation indices (normalized difference vegetation index (NDVI) and the enhanced vegetation index (EVI)) represented the phenology of different successional stages of naturally regenerating TDFs, within a widely conserved forest fragment in the semi-arid southeast of Brazil, we installed several canopy towers with radiometric sensors to produce high temporal resolution near-surface vegetation greenness indices. Direct comparison of several years of ground measurements with a combined Aqua/Terra 8 day satellite product showed similar broad temporal trends, but MODIS often suffered from cloud contamination during the onset of the growing season and occasionally during the peak growing season. The strength of the in-situ and MODIS linear relationship was greater for NDVI than for EVI across sites but varied with forest stand age. Furthermore, we describe the onset dates and duration of canopy development phases for three years of in-situ monitoring. A seasonality analysis revealed significant discrepancies between tower and MODIS phenology transitions dates, with up to five weeks differences in growing season length estimation. Our results indicate that 8 and 16 day MODIS satellite vegetation monitoring products are suitable for tracking general patterns of tropical dry forest phenology in this region but are not temporally sufficient to characterize inter-annual differences in phenology phase onset dates or changes in productivity due to mid-season droughts. Such rapid transitions in canopy greenness are important indicators of climate change sensitivity of these

  12. Analysis of vegetation and land cover dynamics in north-western Morocco during the last decade using MODIS NDVI time series data

    Directory of Open Access Journals (Sweden)

    C. Höpfner

    2011-11-01

    Full Text Available Vegetation phenology as well as the current variability and dynamics of vegetation and land cover, including its climatic and human drivers, are examined in a region in north-western Morocco that is nearly 22 700 km2 big. A gapless time series of Normalized Differenced Vegetation Index (NDVI composite raster data from 29 September 2000 to 29 September 2009 is utilised. The data have a spatial resolution of 250 m and were acquired by the Moderate Resolution Imaging Spectroradiometer (MODIS sensor.

    The presented approach allows to compose and to analyse yearly land cover maps in a widely unknown region with scarce validated ground truth data by deriving phenological parameters. Results show that the high temporal resolution of 16 d is sufficient for (a determining local land cover better than global land cover classifications of Plant Functional Types (PFT and Global Land Cover 2000 (GLC2000 and (b for drawing conclusions on vegetation dynamics and its drivers. Areas of stably classified land cover types (i.e. areas that did not change their land cover type show climatically driven inter- and intra-annual variability with indicated influence of droughts. The presented approach to determine human-driven influence on vegetation dynamics caused by agriculture results in a more than ten times larger area compared with stably classified areas. Change detection based on yearly land cover maps shows a gain of high-productive vegetation (cropland of about 259.3 km2. Statistically significant inter-annual trends in vegetation dynamics during the last decade could however not be discovered. A sequence of correlations was respectively carried out to extract the most important periods of rainfall responsible for the production of green biomass and for the extent of land cover types. Results show that mean daily precipitation from 1 October to 15 December has high correlation results (max. r2=0.85 on an intra

  13. Spatio-temporal distribution of vegetation index and its influencing factors—a case study of the Jiaozhou Bay, China

    Science.gov (United States)

    Zheng, Yang; Yu, Ge

    2017-11-01

    The coastal zone is an area characterized by intense interaction between land and sea, high sensitivity to regional environmental changes, and concentrated human activities. Little research has investigated vegetation cover changes in coastal zones resulting from climate change and land-use change, with a lack of knowledge about the driving mechanism. Normalized difference vegetation index (NDVI) can be used as an indicator for change of the coastal environment. In this study, we analyzed the interannual changes and spatial distribution of NDVI in the coastal zone around Jiaozhou Bay in Qingdao, a coastal city undergoing rapid urbanization in northeast China. The underlying causes of NDVI variations were discussed in the context of climate change and land-use change. Results showed that the spatio-temporal distribution of NDVI displayed high spatial variability in the study area and showed a typical trend of gradually increasing from coastal to inland regions. The significant increase area of NDVI was mainly found in newly added construction land, extending along the coastline towards the inland. Land vegetation cover demonstrated a certain response relationship to sea-land climate change and land-based activities. The impact of land-based human activities was slightly greater than that of sea-land climate change for land vegetation cover. The results indicate that promoting ecological policies can build an ecological security framework of vegetation suitable for the resource characteristics of coastal cities. The framework will buffer the negative effects of sea-land climate change and land-based human activities on vegetation cover and thereby achieve the balance of regional development and ecological benefits in the coastal zone.

  14. Soil Drought and Vegetation Response during 2001–2015 in North China Based on GLDAS and MODIS Data

    Directory of Open Access Journals (Sweden)

    Siyao Yang

    2018-01-01

    Full Text Available Drought is a natural disaster caused by long-term water deficit. Because the growth of crops and vegetation is closely related to soil moisture environment, it is of great significance to study the soil drought and vegetation response. In this paper, the soil moisture availability index (SMAI was developed for quantifying soil drought conditions. The effectiveness and the ability of SMAI to recognize drought events were analyzed, while the vegetation condition index (VCI was used to characterize the vegetation status. Temporal and spatial variations of soil drought and vegetation condition as well as the impacts of drought on vegetation in North China during 2001–2015 were comprehensively examined. We firstly concluded that SMAI related well with standardized precipitation evapotranspiration index (SPEI, and drought events can be detected by SMAI. Next, the mean value of SMAI in North China showed a decreasing trend in recent 15 years. Finally, the SMAI positively correlated with VCI in most areas of North China, and the response of four types of vegetation to SMAI differed over time. The results of SMAI on vegetation would assist drought research and application in North China.

  15. Applying Markov Chains for NDVI Time Series Forecasting of Latvian Regions

    Directory of Open Access Journals (Sweden)

    Stepchenko Arthur

    2015-12-01

    Full Text Available Time series of earth observation based estimates of vegetation inform about variations in vegetation at the scale of Latvia. A vegetation index is an indicator that describes the amount of chlorophyll (the green mass and shows the relative density and health of vegetation. NDVI index is an important variable for vegetation forecasting and management of various problems, such as climate change monitoring, energy usage monitoring, managing the consumption of natural resources, agricultural productivity monitoring, drought monitoring and forest fire detection. In this paper, we make a one-step-ahead prediction of 7-daily time series of NDVI index using Markov chains. The choice of a Markov chain is due to the fact that a Markov chain is a sequence of random variables where each variable is located in some state. And a Markov chain contains probabilities of moving from one state to other.

  16. A possible dose-response association between distance to farmers' markets and roadside produce stands, frequency of shopping, fruit and vegetable consumption, and body mass index among customers in the Southern United States.

    Science.gov (United States)

    Jilcott Pitts, Stephanie B; Hinkley, Jedediah; Wu, Qiang; McGuirt, Jared T; Lyonnais, Mary Jane; Rafferty, Ann P; Whitt, Olivia R; Winterbauer, Nancy; Phillips, Lisa

    2017-01-11

    The association between farmers' market characteristics and consumer shopping habits remains unclear. Our objective was to examine associations among distance to farmers' markets, amenities within farmers' markets, frequency of farmers' market shopping, fruit and vegetable consumption, and body mass index (BMI). We hypothesized that the relationship between frequency of farmers' market shopping and BMI would be mediated by fruit and vegetable consumption. In 15 farmers' markets in northeastern North Carolina, July-September 2015, we conducted a cross-sectional survey among 263 farmers' market customers (199 provided complete address data) and conducted farmers' market audits. To participate, customers had to be over 18 years of age, and English speaking. Dependent variables included farmers' market shopping frequency, fruit and vegetable consumption, and BMI. Analysis of variance, adjusted multinomial logistic regression, Poisson regression, and linear regression models, adjusted for age, race, sex, and education, were used to examine associations between distance to farmers' markets, amenities within farmers' markets, frequency of farmers' market shopping, fruit and vegetable consumption, and BMI. Those who reported shopping at farmers' markets a few times per year or less reported consuming 4.4 (standard deviation = 1.7) daily servings of fruits and vegetables, and those who reported shopping 2 or more times per week reported consuming 5.5 (2.2) daily servings. There was no association between farmers' market amenities, and shopping frequency or fruit and vegetable consumption. Those who shopped 2 or more times per week had a statistically significantly lower BMI than those who shopped less frequently. There was no evidence of mediation of the relationship between frequency of shopping and BMI by fruit and vegetable consumption. More work should be done to understand factors within farmers' markets that encourage fruit and vegetable purchases.

  17. A possible dose–response association between distance to farmers’ markets and roadside produce stands, frequency of shopping, fruit and vegetable consumption, and body mass index among customers in the Southern United States

    Directory of Open Access Journals (Sweden)

    Stephanie B. Jilcott Pitts

    2017-01-01

    Full Text Available Abstract Background The association between farmers’ market characteristics and consumer shopping habits remains unclear. Our objective was to examine associations among distance to farmers’ markets, amenities within farmers’ markets, frequency of farmers’ market shopping, fruit and vegetable consumption, and body mass index (BMI. We hypothesized that the relationship between frequency of farmers’ market shopping and BMI would be mediated by fruit and vegetable consumption. Methods In 15 farmers’ markets in northeastern North Carolina, July–September 2015, we conducted a cross-sectional survey among 263 farmers’ market customers (199 provided complete address data and conducted farmers’ market audits. To participate, customers had to be over 18 years of age, and English speaking. Dependent variables included farmers’ market shopping frequency, fruit and vegetable consumption, and BMI. Analysis of variance, adjusted multinomial logistic regression, Poisson regression, and linear regression models, adjusted for age, race, sex, and education, were used to examine associations between distance to farmers’ markets, amenities within farmers’ markets, frequency of farmers’ market shopping, fruit and vegetable consumption, and BMI. Results Those who reported shopping at farmers’ markets a few times per year or less reported consuming 4.4 (standard deviation = 1.7 daily servings of fruits and vegetables, and those who reported shopping 2 or more times per week reported consuming 5.5 (2.2 daily servings. There was no association between farmers’ market amenities, and shopping frequency or fruit and vegetable consumption. Those who shopped 2 or more times per week had a statistically significantly lower BMI than those who shopped less frequently. There was no evidence of mediation of the relationship between frequency of shopping and BMI by fruit and vegetable consumption. Conclusions More work should be done to understand

  18. The assessment of anthropogenic impact on the environment in East Fennoscandia based on the Normalized Difference Vegetation Index data

    Science.gov (United States)

    Miulgauzen, Daria; Pankratova, Lubov

    2017-04-01

    Being a part of Eurasian "cold sector", ecosystems of East Fennoscandia may fit in the category of the most vulnerable to any external impact, including anthropogenic one. The productivity of plant communities can serve as an indicator representing the state of ecosystems, especially in disturbed areas. The present research is aimed at the environmental impact assessment caused by the Pechenganikel Mining and Metallurgical Plant based on the plant communities' productivity data on the example of ecosystems of East Fennoscandia. Vegetation productivity was assessed on the basis of the Normalized Difference Vegetation Index (NDVI) which is often used for screenings to quantify plant canopy. The essence of the method is that of the difference between the spectral reflectance of vegetation in red and near-infrared regions. The index was calculated on the satellite images of Landsat 8 in IDRISI Kilimanjaro (Clark Labs) according to the equation: N DV I = N-IR- RED-; N IR +RED NIR - spectral reflectance measurements in near-infrared region, RED - spectral reflectance measurements in red region. To compare the index calculations with the information on the state of plant communities, the field studies were carried out in the area of 380 km2 in the vicinity of the Pechenganikel Mining and Metallurgical Plant (Kola Peninsula, Nikel urban-type settlement). As a result, there was created a map in MapInfo Professional 12.5 (Pitney Bowes Software) that represents the vegetation damage at a scale of 1:100,000. The field research has revealed the morphogenetic discrepancy between the soil-plant cover of the area in question and the one of "zonal" ecosystems. Plant communities have been widely modified or destroyed because of air pollution and there are numerous disturbances in the soil profile structure. In terms of vegetation productivity, the analysis of the NDVI figures has shown that the closer the pollution source (Pechenganikel Plant) is, the more significant the

  19. Remote-Sensing Time Series Analysis, a Vegetation Monitoring Tool

    Science.gov (United States)

    McKellip, Rodney; Prados, Donald; Ryan, Robert; Ross, Kenton; Spruce, Joseph; Gasser, Gerald; Greer, Randall

    2008-01-01

    The Time Series Product Tool (TSPT) is software, developed in MATLAB , which creates and displays high signal-to- noise Vegetation Indices imagery and other higher-level products derived from remotely sensed data. This tool enables automated, rapid, large-scale regional surveillance of crops, forests, and other vegetation. TSPT temporally processes high-revisit-rate satellite imagery produced by the Moderate Resolution Imaging Spectroradiometer (MODIS) and by other remote-sensing systems. Although MODIS imagery is acquired daily, cloudiness and other sources of noise can greatly reduce the effective temporal resolution. To improve cloud statistics, the TSPT combines MODIS data from multiple satellites (Aqua and Terra). The TSPT produces MODIS products as single time-frame and multitemporal change images, as time-series plots at a selected location, or as temporally processed image videos. Using the TSPT program, MODIS metadata is used to remove and/or correct bad and suspect data. Bad pixel removal, multiple satellite data fusion, and temporal processing techniques create high-quality plots and animated image video sequences that depict changes in vegetation greenness. This tool provides several temporal processing options not found in other comparable imaging software tools. Because the framework to generate and use other algorithms is established, small modifications to this tool will enable the use of a large range of remotely sensed data types. An effective remote-sensing crop monitoring system must be able to detect subtle changes in plant health in the earliest stages, before the effects of a disease outbreak or other adverse environmental conditions can become widespread and devastating. The integration of the time series analysis tool with ground-based information, soil types, crop types, meteorological data, and crop growth models in a Geographic Information System, could provide the foundation for a large-area crop-surveillance system that could identify

  20. Vegetation productivity responses to drought on tribal lands in the four corners region of the Southwest USA

    Science.gov (United States)

    El-Vilaly, Mohamed Abd Salam; Didan, Kamel; Marsh, Stuart E.; van Leeuwen, Willem J. D.; Crimmins, Michael A.; Munoz, Armando Barreto

    2018-03-01

    For more than a decade, the Four Corners Region has faced extensive and persistent drought conditions that have impacted vegetation communities and local water resources while exacerbating soil erosion. These persistent droughts threaten ecosystem services, agriculture, and livestock activities, and expose the hypersensitivity of this region to inter-annual climate variability and change. Much of the intermountainWestern United States has sparse climate and vegetation monitoring stations, making fine-scale drought assessments difficult. Remote sensing data offers the opportunity to assess the impacts of the recent droughts on vegetation productivity across these areas. Here, we propose a drought assessment approach that integrates climate and topographical data with remote sensing vegetation index time series. Multisensor Normalized Difference Vegetation Index (NDVI) time series data from 1989 to 2010 at 5.6 km were analyzed to characterize the vegetation productivity changes and responses to the ongoing drought. A multi-linear regression was applied to metrics of vegetation productivity derived from the NDVI time series to detect vegetation productivity, an ecosystem service proxy, and changes. The results show that around 60.13% of the study area is observing a general decline of greenness ( pchallenges to the region's already stressed ecosystems. Whereas the results provide additional insights into this isolated and vulnerable region, the drought assessment approach used in this study may be adapted for application in other regions where surface-based climate and vegetation monitoring record is spatially and temporally limited.

  1. Post-fire vegetation recovery in Portugal based ewline on spot/vegetation data

    Directory of Open Access Journals (Sweden)

    C. Gouveia

    2010-04-01

    Full Text Available A procedure is presented that allows identifying large burned scars and the monitoring of vegetation recovery in the years following major fire episodes. The procedure relies on 10-day fields of Maximum Value Composites of Normalized Difference Vegetation Index (MVC-NDVI, with a 1 km×1 km spatial resolution obtained from the VEGETATION instrument. The identification of fire scars during the extremely severe 2003 fire season is performed based on cluster analysis of NDVI anomalies that persist during the vegetative cycle of the year following the fire event. Two regions containing very large burned scars were selected, located in Central and Southwestern Portugal, respectively, and time series of MVC-NDVI analysed before the fire events took place and throughout the post-fire period. It is shown that post-fire vegetation dynamics in the two selected regions may be characterised based on maps of recovery rates as estimated by fitting a monoparametric model of vegetation recovery to MVC-NDVI data over each burned scar. Results indicated that the recovery process in the region located in Central Portugal is mostly related to fire damage rather than to vegetation density before 2003, whereas the latter seems to have a more prominent role than vegetation conditions after the fire episode, e.g. in the case of the region in Southwestern Portugal. These differences are consistent with the respective predominant types of vegetation. The burned area located in Central Portugal is dominated by Pinus Pinaster whose natural regeneration crucially depends on the destruction of seeds present on the soil surface during the fire, whereas the burned scar in Southwestern Portugal was populated by Eucalyptus that may quickly re-sprout from buds after fire. Besides its simplicity, the monoparametric model of vegetation recovery has the advantage of being easily adapted to other low-resolution satellite data, as well as to other types of vegetation

  2. The Role of Social Support and Self-efficacy for Planning Fruit and Vegetable Intake.

    Science.gov (United States)

    Zhou, Guangyu; Gan, Yiqun; Hamilton, Kyra; Schwarzer, Ralf

    2017-02-01

    The aim of the current study was to examine the joint effect of self-efficacy, action planning, and received social support on fruit and vegetable intake. The study used a longitudinal design with 3 waves of data collection. Major university campus in Beijing, China. Young adults (n = 286). Age, gender, body mass index, dietary self-efficacy, and baseline behavior were measured at time 1. Two weeks after time 1, received social support and action planning were assessed (time 2); 4 weeks after time 1, subsequent fruit and vegetable consumption was measured (time 3). In a path analysis, action planning at time 2 was specified as a mediator between self-efficacy at time 1 and fruit and vegetable intake at time 3, controlling for age, gender, body mass index, and baseline behavior. In addition, in a conditional process analysis, received social support at time 2 was specified as a moderator of the self-efficacy-planning relationship. Action planning mediated between self-efficacy and subsequent dietary behavior, and received social support moderated between self-efficacy and planning supporting a compensation effect. Action planning served as a proximal predictor of fruit and vegetable intake, and planning one's consumption was facilitated by dietary self-efficacy. Through the identification of social cognitive factors influencing dietary planning, interventions can target self-efficacy and received social support to test the efficacy of these mechanisms in increasing individuals' ability to ensure they consume adequate amounts of fruits and vegetables. Copyright © 2016 Society for Nutrition Education and Behavior. Published by Elsevier Inc. All rights reserved.

  3. Zero refractive index in time-Floquet acoustic metamaterials

    Science.gov (United States)

    Koutserimpas, Theodoros T.; Fleury, Romain

    2018-03-01

    New scientific investigations of artificially structured materials and experiments have exhibited wave manipulation to the extreme. In particular, zero refractive index metamaterials have been on the front line of wave physics research for their unique wave manipulation properties and application potentials. Remarkably, in such exotic materials, time-harmonic fields have an infinite wavelength and do not exhibit any spatial variations in their phase distribution. This unique feature can be achieved by forcing a Dirac cone to the center of the Brillouin zone ( Γ point), as previously predicted and experimentally demonstrated in time-invariant metamaterials by means of accidental degeneracy between three different modes. In this article, we propose a different approach that enables true conical dispersion at Γ with twofold degeneracy and generates zero index properties. We break time-reversal symmetry and exploit a time-Floquet modulation scheme to demonstrate a time-Floquet acoustic metamaterial with zero refractive index. This behavior, predicted using stroboscopic analysis, is confirmed by full-wave finite element simulations. Our results establish the relevance of time-Floquet metamaterials as a novel reconfigurable platform for wave control.

  4. Dimension Reduction of Multi-Spectral Satellite Image Time Series to Improve Deforestation Monitoring

    Directory of Open Access Journals (Sweden)

    Meng Lu

    2017-10-01

    Full Text Available In recent years, sequential tests for detecting structural changes in time series have been adapted for deforestation monitoring using satellite data. The input time series of such sequential tests is typically a vegetation index (e.g., NDVI, which uses two or three bands and ignores all other bands. Being limited to a vegetation index will not benefit from the richer spectral information provided by newly launched satellites and will bring two bottle-necks for deforestation monitoring. Firstly, it is hard to select a suitable vegetation index a priori. Secondly, a single vegetation index is typically affected by seasonal signals, noise and other natural dynamics, which decrease its power for deforestation detection. A novel multispectral time series change monitoring method that combines dimension reduction methods with a sequential hypothesis test is proposed to address these limitations. For each location, the proposed method automatically chooses a “suitable” index for deforestation monitoring. To demonstrate our approach, we implemented it in two study areas: a dry tropical forest in Bolivia (time series length: 444 with strong seasonality and a moist tropical forest in Brazil (time series length: 225 with almost no seasonality. Our method significantly improves accuracy in the presence of strong seasonality, in particular the temporal lag between disturbance and its detection.

  5. Effects of Pheretima Guillelmi Cultivation Time on Microbial Community Diversity and Characteristics of Carbon Metabolism in Vegetable Soil

    Directory of Open Access Journals (Sweden)

    ZHENG Xian-qing

    2015-12-01

    Full Text Available In order to study the effect of different biological tillage time (Pheretima guillelmi on soil microbial community metabolic functions in different soil depths, we set a location test in vegetable field at Chongming Island in Shanghai to analyze the changes of soil microbial community and carbon utilization abilities (Average well- color development, AWCD by using biolog eco-plate method. The three-year results showed that: Bio-tillage significantly improved microbial community activity, and with the increase of tillage years, biological tillage could make the average AWCD 3 to 7 times higher. The Simpson index and Shannon index of the biological tillage treatments were significantly higher than that of the control. The cumulative increase of 0~5 cm soil layer was 49 and 6.28 respectively, and the cumulative increase of 5~20 cm soil layer was 31 and 2.55 respectively. Earthworm bio-tillage significantly increased the soil microbial metabolic ability of 6 kinds of carbon sources, and increased the carbohydrate metabolism activity. In this study, earthworm bio-tillage is an effective way to increase the microbial activity of microbial soil.

  6. Effects of vegetation structure on biomass accumulation in a Balanced Optimality Structure Vegetation Model (BOSVM v1.0

    Directory of Open Access Journals (Sweden)

    Z. Yin

    2014-05-01

    Full Text Available A myriad of interactions exist between vegetation and local climate for arid and semi-arid regions. Vegetation function, structure and individual behavior have large impacts on carbon–water–energy balances, which consequently influence local climate variability that, in turn, feeds back to the vegetation. In this study, a conceptual vegetation structure scheme is formulated and tested in the new Balanced Optimality Structure Vegetation Model (BOSVM to explore the importance of vegetation structure and vegetation adaptation to water stress on equilibrium biomass states. Surface energy, water and carbon fluxes are simulated for a range of vegetation structures across a precipitation gradient in West Africa and optimal vegetation structures that maximize biomass for each precipitation regime are determined. Two different strategies of vegetation adaptation to water stress are included. Under dry conditions vegetation tries to maximize the water use efficiency and leaf area index as it tries to maximize carbon gain. However, a negative feedback mechanism in the vegetation–soil water system is found as the vegetation also tries to minimize its cover to optimize the surrounding bare ground area from which water can be extracted, thereby forming patches of vertical vegetation. Under larger precipitation, a positive feedback mechanism is found in which vegetation tries to maximize its cover as it then can reduce water loss from bare soil while having maximum carbon gain due to a large leaf area index. The competition between vegetation and bare soil determines a transition between a "survival" state to a "growing" state.

  7. Estimating urban vegetation fraction across 25 cities in pan-Pacific using Landsat time series data

    Science.gov (United States)

    Lu, Yuhao; Coops, Nicholas C.; Hermosilla, Txomin

    2017-04-01

    Urbanization globally is consistently reshaping the natural landscape to accommodate the growing human population. Urban vegetation plays a key role in moderating environmental impacts caused by urbanization and is critically important for local economic, social and cultural development. The differing patterns of human population growth, varying urban structures and development stages, results in highly varied spatial and temporal vegetation patterns particularly in the pan-Pacific region which has some of the fastest urbanization rates globally. Yet spatially-explicit temporal information on the amount and change of urban vegetation is rarely documented particularly in less developed nations. Remote sensing offers an exceptional data source and a unique perspective to map urban vegetation and change due to its consistency and ubiquitous nature. In this research, we assess the vegetation fractions of 25 cities across 12 pan-Pacific countries using annual gap-free Landsat surface reflectance products acquired from 1984 to 2012, using sub-pixel, spectral unmixing approaches. Vegetation change trends were then analyzed using Mann-Kendall statistics and Theil-Sen slope estimators. Unmixing results successfully mapped urban vegetation for pixels located in urban parks, forested mountainous regions, as well as agricultural land (correlation coefficient ranging from 0.66 to 0.77). The greatest vegetation loss from 1984 to 2012 was found in Shanghai, Tianjin, and Dalian in China. In contrast, cities including Vancouver (Canada) and Seattle (USA) showed stable vegetation trends through time. Using temporal trend analysis, our results suggest that it is possible to reduce noise and outliers caused by phenological changes particularly in cropland using dense new Landsat time series approaches. We conclude that simple yet effective approaches of unmixing Landsat time series data for assessing spatial and temporal changes of urban vegetation at regional scales can provide

  8. Study of Wetland Ecosystem Vegetation Using Satellite Data

    Science.gov (United States)

    Dyukarev, E. A.; Alekseeva, M. N.; Golovatskaya, E. A.

    2017-12-01

    The normalized difference vegetation index (NDVI) is used to estimate the aboveground net production (ANP) of wetland ecosystems for the key area at the South Taiga zone of West Siberia. The vegetation index and aboveground production are related by linear dependence and are specific for each wetland ecosystem. The NDVI grows with an increase in the ANP at wooded oligotrophic ecosystems. Open oligotrophic bogs and eutrophic wetlands are characterized by an opposite relation. Maps of aboveground production for wetland ecosystems are constructed for each study year and for the whole period of studies. The average aboveground production for all wetland ecosystems of the key area, which was estimated with consideration for the area they occupy and using the data of satellite measurements of the vegetation index, is 305 g C/m2/yr. The total annual carbon accumulation in aboveground wetland vegetation in the key area is 794600 t.

  9. Attribution of trends in global vegetation greenness from 1982 to 2011

    Science.gov (United States)

    Zhu, Z.; Xu, L.; Bi, J.; Myneni, R.; Knyazikhin, Y.

    2012-12-01

    Time series of remotely sensed vegetation indices data provide evidence of changes in terrestrial vegetation activity over the past decades in the world. However, it is difficult to attribute cause-and-effect to vegetation trends because variations in vegetation productivity are driven by various factors. This study investigated changes in global vegetation productivity first, and then attributed the global natural vegetation with greening trend. Growing season integrated normalized difference vegetation index (GSI NDVI) derived from the new GIMMS NDVI3g dataset (1982-2011was analyzed. A combined time series analysis model, which was developed from simper linear trend model (SLT), autoregressive integrated moving average model (ARIMA) and Vogelsang's t-PST model shows that productivity of all vegetation types except deciduous broadleaf forest predominantly showed increasing trends through the 30-year period. The evolution of changes in productivity in the last decade was also investigated. Area of greening vegetation monotonically increased through the last decade, and both the browning and no change area monotonically decreased. To attribute the predominant increase trend of productivity of global natural vegetation, trends of eight climate time series datasets (three temperature, three precipitation and two radiation datasets) were analyzed. The attribution of trends in global vegetation greenness was summarized as relaxation of climatic constraints, fertilization and other unknown reasons. Result shows that nearly all the productivity increase of global natural vegetation was driven by relaxation of climatic constraints and fertilization, which play equally important role in driving global vegetation greenness.; Area fraction and productivity change fraction of IGBP vegetation land cover classes showing statistically significant (10% level) trend in GSI NDVIt;

  10. Research note: Grazing-index method procedures of vegetation ...

    African Journals Online (AJOL)

    In the past, veld condition in the Karoo was assessed using the ecological index methods. This recently changed to the graxing-index method on account of the of the differently estimated grazing-index values being used. The principles governing the method of survey remain the same. The method employs ...

  11. Marsh collapse thresholds for coastal Louisiana estimated using elevation and vegetation index data

    Science.gov (United States)

    Couvillion, Brady R.; Beck, Holly

    2013-01-01

    Forecasting marsh collapse in coastal Louisiana as a result of changes in sea-level rise, subsidence, and accretion deficits necessitates an understanding of thresholds beyond which inundation stress impedes marsh survival. The variability in thresholds at which different marsh types cease to occur (i.e., marsh collapse) is not well understood. We utilized remotely sensed imagery, field data, and elevation data to help gain insight into the relationships between vegetation health and inundation. A Normalized Difference Vegetation Index (NDVI) dataset was calculated using remotely sensed data at peak biomass (August) and used as a proxy for vegetation health and productivity. Statistics were calculated for NDVI values by marsh type for intermediate, brackish, and saline marsh in coastal Louisiana. Marsh-type specific NDVI values of 1.5 and 2 standard deviations below the mean were used as upper and lower limits to identify conditions indicative of collapse. As marshes seldom occur beyond these values, they are believed to represent a range within which marsh collapse is likely to occur. Inundation depth was selected as the primary candidate for evaluation of marsh collapse thresholds. Elevation relative to mean water level (MWL) was calculated by subtracting MWL from an elevation dataset compiled from multiple data types including light detection and ranging (lidar) and bathymetry. A polynomial cubic regression was used to examine a random subset of pixels to determine the relationship between elevation (relative to MWL) and NDVI. The marsh collapse uncertainty range values were found by locating the intercept of the regression line with the 1.5 and 2 standard deviations below the mean NDVI value for each marsh type. Results indicate marsh collapse uncertainty ranges of 30.7–35.8 cm below MWL for intermediate marsh, 20–25.6 cm below MWL for brackish marsh, and 16.9–23.5 cm below MWL for saline marsh. These values are thought to represent the ranges of

  12. Spectral entropy as a mean to quantify water stress history for natural vegetation and irrigated agriculture in a water-stressed tropical environment

    Science.gov (United States)

    Kim, Y.; Johnson, M. S.

    2017-12-01

    Spectral entropy (Hs) is an index which can be used to measure the structural complexity of time series data. When a time series is made up of one periodic function, the Hs value becomes smaller, while Hs becomes larger when a time series is composed of several periodic functions. We hypothesized that this characteristic of the Hs could be used to quantify the water stress history of vegetation. For the ideal condition for which sufficient water is supplied to an agricultural crop or natural vegetation, there should be a single distinct phenological cycle represented in a vegetation index time series (e.g., NDVI and EVI). However, time series data for a vegetation area that repeatedly experiences water stress may include several fluctuations that can be observed in addition to the predominant phenological cycle. This is because the process of experiencing water stress and recovering from it generates small fluctuations in phenological characteristics. Consequently, the value of Hs increases when vegetation experiences several water shortages. Therefore, the Hs could be used as an indicator for water stress history. To test this hypothesis, we analyzed Moderate Resolution Imaging Spectroradiometer (MODIS) Normalized Difference Vegetation Index (NDVI) data for a natural area in comparison to a nearby sugarcane area in seasonally-dry western Costa Rica. In this presentation we will illustrate the use of spectral entropy to evaluate the vegetative responses of natural vegetation (dry tropical forest) and sugarcane under three different irrigation techniques (center pivot irrigation, drip irrigation and flood irrigation). Through this comparative analysis, the utility of Hs as an indicator will be tested. Furthermore, crop response to the different irrigation methods will be discussed in terms of Hs, NDVI and yield.

  13. Dynamic plant ecology: the spectrum of vegetational change in space and time

    Energy Technology Data Exchange (ETDEWEB)

    Delcourt, H R; Delcourt, P A; Webb, T III

    1983-01-01

    Different environmental forcing functions influence vegetational patterns and processes over a wide range of spatial and temporal scales. On the micro-scale (1 year to 5 x 10/sup 3/ years, 1 m/sup 2/ to 10/sup 6/m/sup 2/) natural and anthropogenic disturbances affect establishment and succession of species populations. At the macro-scale (5 x 10/sup 3/ years to 10/sup 6/ years and 10/sup 6/m/sup 2/ to 10/sup 12/m/sup 2/) climatic changes influence regional vegetational processes that include migrations of species as well as displacement of ecosystems. Mega-scale phenomena such as plate tectonics, evolution of the biota and development of global patterns of vegetation occur on the time scale of > 10/sup 6/ years and over areas > 10/sup 12/m/sup 2/. Our knowledge of past vegetational changes resulting from Quaternary climatic change can be used to predict biotic responses to future climatic changes such as global warming that may be induced by increased carbon dioxide (CO/sub 2/) concentrations in the atmosphere. The time scale for future climatic warming may be much more rapid than that characterizing the early- to mid-Holocene, increasing the probability of rapid turnover in species composition, changes in local and regional dominance of important taxa, displacement of species ranges and local extinction of species. Integration of ecological and paleoecological perspectives on vegetational dynamics is fundamental to understanding and managing the biosphere.

  14. Migratory herbivorous waterfowl track satellite-derived green wave index.

    Directory of Open Access Journals (Sweden)

    Mitra Shariatinajafabadi

    Full Text Available Many migrating herbivores rely on plant biomass to fuel their life cycles and have adapted to following changes in plant quality through time. The green wave hypothesis predicts that herbivorous waterfowl will follow the wave of food availability and quality during their spring migration. However, testing this hypothesis is hampered by the large geographical range these birds cover. The satellite-derived normalized difference vegetation index (NDVI time series is an ideal proxy indicator for the development of plant biomass and quality across a broad spatial area. A derived index, the green wave index (GWI, has been successfully used to link altitudinal and latitudinal migration of mammals to spatio-temporal variations in food quality and quantity. To date, this index has not been used to test the green wave hypothesis for individual avian herbivores. Here, we use the satellite-derived GWI to examine the green wave hypothesis with respect to GPS-tracked individual barnacle geese from three flyway populations (Russian n = 12, Svalbard n = 8, and Greenland n = 7. Data were collected over three years (2008-2010. Our results showed that the Russian and Svalbard barnacle geese followed the middle stage of the green wave (GWI 40-60%, while the Greenland geese followed an earlier stage (GWI 20-40%. Despite these differences among geese populations, the phase of vegetation greenness encountered by the GPS-tracked geese was close to the 50% GWI (i.e. the assumed date of peak nitrogen concentration, thereby implying that barnacle geese track high quality food during their spring migration. To our knowledge, this is the first time that the migration of individual avian herbivores has been successfully studied with respect to vegetation phenology using the satellite-derived GWI. Our results offer further support for the green wave hypothesis applying to long-distance migrants on a larger scale.

  15. Life quality time allocation index-an equilibrium economy consistent version of the current life quality index

    DEFF Research Database (Denmark)

    Ditlevsen, Ove; Friis-Hansen, Peter

    2005-01-01

    The definition the Life Quality Index for a country as originally suggested by Nathwani, Lind and Pandey is based on the gross domestic product (GDP), the expected life in good health at birth, and the fraction of life time the anonymous citizen of the country is occupied with money making work...... a further development casting the definition into dimensionless quantities that make the index get a pure unit of time and not the somewhat obscure unit as a power product of a money unit and a time unit. To avoid confusion, this new variant of the LQI is called the Life Quality Time Allocation Index (LQTAI...... of the variables themselves, the relative increment of the LQI becomes defined as a convex combination of the two relative increments. The combination parameter is obtained by an optimality argument about the anonymous citizen’s distribution of his or her time between free time and work time. In the original...

  16. Real time refractive index measurement by ESPI

    International Nuclear Information System (INIS)

    Torroba, R.; Joenathan, C.

    1991-01-01

    In this paper a method to measure refractive index variations in real time is reported. A technique to introduce reference fringes in real time is discussed. Both the theoretical and experimental results are presented and an example with phase shifting is given. (author). 8 refs, 5 figs

  17. Mapping paddy rice planting areas through time series analysis of MODIS land surface temperature and vegetation index data.

    Science.gov (United States)

    Zhang, Geli; Xiao, Xiangming; Dong, Jinwei; Kou, Weili; Jin, Cui; Qin, Yuanwei; Zhou, Yuting; Wang, Jie; Menarguez, Michael Angelo; Biradar, Chandrashekhar

    2015-08-01

    Knowledge of the area and spatial distribution of paddy rice is important for assessment of food security, management of water resources, and estimation of greenhouse gas (methane) emissions. Paddy rice agriculture has expanded rapidly in northeastern China in the last decade, but there are no updated maps of paddy rice fields in the region. Existing algorithms for identifying paddy rice fields are based on the unique physical features of paddy rice during the flooding and transplanting phases and use vegetation indices that are sensitive to the dynamics of the canopy and surface water content. However, the flooding phenomena in high latitude area could also be from spring snowmelt flooding. We used land surface temperature (LST) data from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor to determine the temporal window of flooding and rice transplantation over a year to improve the existing phenology-based approach. Other land cover types (e.g., evergreen vegetation, permanent water bodies, and sparse vegetation) with potential influences on paddy rice identification were removed (masked out) due to their different temporal profiles. The accuracy assessment using high-resolution images showed that the resultant MODIS-derived paddy rice map of northeastern China in 2010 had a high accuracy (producer and user accuracies of 92% and 96%, respectively). The MODIS-based map also had a comparable accuracy to the 2010 Landsat-based National Land Cover Dataset (NLCD) of China in terms of both area and spatial pattern. This study demonstrated that our improved algorithm by using both thermal and optical MODIS data, provides a robust, simple and automated approach to identify and map paddy rice fields in temperate and cold temperate zones, the northern frontier of rice planting.

  18. Use of Vegetation Health Data for Estimation of Aus Rice Yield in Bangladesh

    OpenAIRE

    Rahman, Atiqur; Roytman, Leonid; Krakauer, Nir Y.; Nizamuddin, Mohammad; Goldberg, Mitch

    2009-01-01

    Rice is a vital staple crop for Bangladesh and surrounding countries, with interannual variation in yields depending on climatic conditions. We compared Bangladesh yield of aus rice, one of the main varieties grown, from official agricultural statistics with Vegetation Health (VH) Indices [Vegetation Condition Index (VCI), Temperature Condition Index (TCI) and Vegetation Health Index (VHI)] computed from Advanced Very High Resolution Radiometer (AVHRR) data covering a period of 15 years (1991...

  19. Using Landsat Vegetation Indices to Estimate Impervious Surface Fractions for European Cities

    DEFF Research Database (Denmark)

    Kaspersen, Per Skougaard; Fensholt, Rasmus; Drews, Martin

    2015-01-01

    and applicability of vegetation indices (VI), from Landsat imagery, to estimate IS fractions for European cities. The accuracy of three different measures of vegetation cover is examined for eight urban areas at different locations in Europe. The Normalized Difference Vegetation Index (NDVI) and Soil Adjusted...... Vegetation Index (SAVI) are converted to IS fractions using a regression modelling approach. Also, NDVI is used to estimate fractional vegetation cover (FR), and consequently IS fractions. All three indices provide fairly accurate estimates (MAEs ≈ 10%, MBE’s

  20. Integrated study of biomass index in La Herreria (Sierra de Guadarrama)

    Science.gov (United States)

    Hernandez Díaz-Ambrona, Carlos G.

    2016-04-01

    Drought severity has many implications for society, including its impacts on the water supply, water pollution, reservoir management and ecosystem. There have been many attempts to characterize its severity, resulting in the numerous drought indices that have been developed (Niemeyer 2008). The'biomass index', based on satellite image derived Normalized Difference Vegetation Index (NDVI) has been used in several countries for pasture and forage crops for some years (Rao, 2010; Escribano-Rodriguez et al., 2014). NDVI generally provides a broad overview of the vegetation condition and spatial vegetation distribution in a region. Vegetative drought is closely related with weather impacts. However, in NDVI, the weather component gets subdued by the strong ecological component. Another vegetation index is Vegetation Condition Index (VCI) that separates the short-term weather-related NDVI fluctuations from the long-term ecosystem changes (Kogan, 1990). Therefore, while NDVI shows seasonal vegetation dynamics, VCI rescales vegetation dynamics between 0 and 100 to reflect relative changes in the vegetation condition from extremely bad to optimal (Kogan et al., 2003). In this work a pasture area at La Herreria (Sierra de Guadarrama, Spain) has been delimited. Then, NDVI historical data are reconstructed based on remote sensing imaging MODIS, with 500x500m2 resolution. From the closest meteorological station (Santolaria-Canales, 2015) records of weekly precipitation, temperature and evapotranspiration from 2001 till 2012 were obtained. Standard Precipitation Index (SPI), Crop Moisture Index (CMI) (Palmer, 1968) and Evapotranspiration-Precipitation Ratio (EPR) are calculated in an attempt to relate them to several vegetation indexes: NDVI, VCI and NDVI Change Ratio to Median (RMNDVI). The results are discussed in the context of pasture index insurance. References Escribano Rodriguez, J.Agustín, Carlos Gregorio Hernández Díaz-Ambrona and Ana María Tarquis Alfonso

  1. Assessing the vegetation condition impacts of the 2011 drought across the U.S. southern Great Plains using the vegetation drought response index (VegDRI)

    Science.gov (United States)

    Tadesse, Tsegaye; Wardlow, Brian D.; Brown, Jesslyn F.; Svoboda, Mark; Hayes, Michael; Fuchs, Brian; Gutzmer, Denise

    2015-01-01

    The vegetation drought response index (VegDRI), which combines traditional climate- and satellite-based approaches for assessing vegetation conditions, offers new insights into assessing the impacts of drought from local to regional scales. In 2011, the U.S. southern Great Plains, which includes Texas, Oklahoma, and New Mexico, was plagued by moderate to extreme drought that was intensified by an extended period of record-breaking heat. The 2011 drought presented an ideal case study to evaluate the performance of VegDRI in characterizing developing drought conditions. Assessment of the spatiotemporal drought patterns represented in the VegDRI maps showed that the severity and patterns of the drought across the region corresponded well to the record warm temperatures and much-below-normal precipitation reported by the National Climatic Data Center and the sectoral drought impacts documented by the Drought Impact Reporter (DIR). VegDRI values and maps also showed the evolution of the drought signal before the Las Conchas Fire (the largest fire in New Mexico’s history). Reports in the DIR indicated that the 2011 drought had major adverse impacts on most rangeland and pastures in Texas and Oklahoma, resulting in total direct losses of more than $12 billion associated with crop, livestock, and timber production. These severe impacts on vegetation were depicted by the VegDRI at subcounty, state, and regional levels. This study indicates that the VegDRI maps can be used with traditional drought indicators and other in situ measures to help producers and government officials with various management decisions, such as justifying disaster assistance, assessing fire risk, and identifying locations to move livestock for grazing.

  2. Sensitivity study of land biosphere CO2 exchange through an atmospheric tracer transport model using satellite-derived vegetation index data

    International Nuclear Information System (INIS)

    Knorr, W.; Heimann, M.

    1994-01-01

    We develop a simple, globally uniform model of CO 2 exchange between the atmosphere and the terrestrial biosphere by coupling the model with a three-dimensional atmospheric tracer transport model using observed winds, and checking results against observed concentrations of CO 2 at various monitoring sites. CO 2 fluxes are derived from observed greenness using satellite-derived Global Vegetation Index data, combined with observations of temperature, radiation, and precipitation. We explore a range of CO 2 flux formulations together with some modifications of the modelled atmospheric transport. We find that while some formulations can be excluded, it cannot be decided whether or not to make CO 2 uptake and release dependent on water stress. It appears that the seasonality of net CO 2 fluxes in the tropics, which would be expected to be driven by water availability, is small and is therefore not visible in the seasonal cycle of atmospheric CO 2 . The latter is dominated largely by northern temperate and boreal vegetation, where seasonality is mostly temperature determined. We find some evidence that there is still considerable CO 2 release from soils during northern-hemisphere winter. An exponential air temperature dependence of soil release with a Q 10 of 1.5 is found to be most appropriate, with no cutoff at low freezing temperatures. This result is independent of the year from which observed winds were taken. This is remarkable insofar as year-to-year changes in modelled CO 2 concentrations caused by changes in the wind data clearly outweigh those caused by year-to-year variability in the climate and vegetation index data. (orig.)

  3. Building the vegetation drought response index for Canada (VegDRI-Canada) to monitor agricultural drought: first results

    Science.gov (United States)

    Tadesse, Tsegaye; Champagne, Catherine; Wardlow, Brian D.; Hadwen, Trevor A.; Brown, Jesslyn; Demisse, Getachew B.; Bayissa, Yared A.; Davidson, Andrew M.

    2017-01-01

    Drought is a natural climatic phenomenon that occurs throughout the world and impacts many sectors of society. To help decision-makers reduce the impacts of drought, it is important to improve monitoring tools that provide relevant and timely information in support of drought mitigation decisions. Given that drought is a complex natural hazard that manifests in different forms, monitoring can be improved by integrating various types of information (e.g., remote sensing and climate) that is timely and region specific to identify where and when droughts are occurring. The Vegetation Drought Response Index for Canada (VegDRI-Canada) is a recently developed drought monitoring tool for Canada. VegDRI-Canada extends the initial VegDRI concept developed for the conterminous United States to a broader transnational coverage across North America. VegDRI-Canada models are similar to those developed for the United States, integrating satellite observations of vegetation status, climate data, and biophysical information on land use and land cover, soil characteristics, and other environmental factors. Collectively, these different types of data are integrated into the hybrid VegDRI-Canada to isolate the effects of drought on vegetation. Twenty-three weekly VegDRI-Canada models were built for the growing season (April–September) through the weekly analysis of these data using a regression tree-based data mining approach. A 15-year time series of VegDRI-Canada results (s to 2014) was produced using these models and the output was validated by randomly selecting 20% of the historical data, as well as holdout year (15% unseen data) across the growing season that the Pearson’s correlation ranged from 0.6 to 0.77. A case study was also conducted to evaluate the VegDRI-Canada results over the prairie region of Canada for two drought years and one non-drought year for three weekly periods of the growing season (i.e., early-, mid-, and late season). The comparison of the Veg

  4. Using the Normalized Differential Wetness Index to Scale Leaf Area Index, Create Three-Dimensional Classification Maps, and Scale Seasonal Evapotranspiration Depletions in Canopies Along the Middle Rio Grande Riparian CorridorCorridor

    Science.gov (United States)

    McDonnell, D. E.; Cleverly, J. R.; Dahm, C. N.; Coonrod, J. A.

    2005-12-01

    This research creates temporally and spatially explicit data layers of vegetation, leaf area index (LAI), three dimensional (3D) vegetation classification maps, and seasonal evapotranspiration (ET) depletions along the middle Rio Grande riparian corridor. The first part of this work produces two dimensional (2D) classification maps of native and non-native canopy vegetation using temporal patterns and the decision tree classifier in ENVI 4.0 (Research Systems Inc. Boulder, Colorado). The second part of this work correlates the normalized differential wetness index (NDWI) with field measurements of plant area index (PAI), stem area index (SAI), and leaf area index (LAI) using the LAI-2000 Plant Canopy Analyzer (PCA) (LICOR Inc., Lincoln, Nebraska). SAI is measured in winter to capture only branches and stems. PAI is measured during the growing season. Field measurements taken within 10 days of image capture dates provide adequate correlations though the closer the dates the better the correlation. LAI represents the surface area of active green leafy vegetation. NDWI correlates with both PAI and estimated LAI in both Tamarisk chinensis and Populus deltoides ssp. Wislizeni sites better than the more traditional normalized differential vegetation index (NDVI). This study also suggests that winter PCA measurements approximate SAI which should be subtracted from PAI in woody vegetation like T. chinensis and Salix exigua stands. The results show that correcting for leaf geometry by multiplying T. chinensis areas with cylindrical cladophylls by pi and the remaining flat leaf vegetation by two yields the best relationship between NDWI and total LAI. The 2Dclassification maps can be placed on top of relief maps of LAI to produce 3D classification maps. The final part of this research scales ET from four 3D eddy covariance towers located in two T. chinensis and two P. deltoides study sites. ET is regressed with LAI, percent daylight (PD), and average hourly incoming net

  5. Webcam network and image database for studies of phenological changes of vegetation and snow cover in Finland, image time series from 2014 to 2016

    Science.gov (United States)

    Peltoniemi, Mikko; Aurela, Mika; Böttcher, Kristin; Kolari, Pasi; Loehr, John; Karhu, Jouni; Linkosalmi, Maiju; Melih Tanis, Cemal; Tuovinen, Juha-Pekka; Nadir Arslan, Ali

    2018-01-01

    In recent years, monitoring of the status of ecosystems using low-cost web (IP) or time lapse cameras has received wide interest. With broad spatial coverage and high temporal resolution, networked cameras can provide information about snow cover and vegetation status, serve as ground truths to Earth observations and be useful for gap-filling of cloudy areas in Earth observation time series. Networked cameras can also play an important role in supplementing laborious phenological field surveys and citizen science projects, which also suffer from observer-dependent observation bias. We established a network of digital surveillance cameras for automated monitoring of phenological activity of vegetation and snow cover in the boreal ecosystems of Finland. Cameras were mounted at 14 sites, each site having 1-3 cameras. Here, we document the network, basic camera information and access to images in the permanent data repository (http://www.zenodo.org/communities/phenology_camera/). Individual DOI-referenced image time series consist of half-hourly images collected between 2014 and 2016 (https://doi.org/10.5281/zenodo.1066862). Additionally, we present an example of a colour index time series derived from images from two contrasting sites.

  6. Webcam network and image database for studies of phenological changes of vegetation and snow cover in Finland, image time series from 2014 to 2016

    Directory of Open Access Journals (Sweden)

    M. Peltoniemi

    2018-01-01

    Full Text Available In recent years, monitoring of the status of ecosystems using low-cost web (IP or time lapse cameras has received wide interest. With broad spatial coverage and high temporal resolution, networked cameras can provide information about snow cover and vegetation status, serve as ground truths to Earth observations and be useful for gap-filling of cloudy areas in Earth observation time series. Networked cameras can also play an important role in supplementing laborious phenological field surveys and citizen science projects, which also suffer from observer-dependent observation bias. We established a network of digital surveillance cameras for automated monitoring of phenological activity of vegetation and snow cover in the boreal ecosystems of Finland. Cameras were mounted at 14 sites, each site having 1–3 cameras. Here, we document the network, basic camera information and access to images in the permanent data repository (http://www.zenodo.org/communities/phenology_camera/. Individual DOI-referenced image time series consist of half-hourly images collected between 2014 and 2016 (https://doi.org/10.5281/zenodo.1066862. Additionally, we present an example of a colour index time series derived from images from two contrasting sites.

  7. Relaxation dynamics and thermophysical properties of vegetable oils using time-domain reflectometry.

    Science.gov (United States)

    Sonkamble, Anil A; Sonsale, Rahul P; Kanshette, Mahesh S; Kabara, Komal B; Wananje, Kunal H; Kumbharkhane, Ashok C; Sarode, Arvind V

    2017-04-01

    Dielectric relaxation studies of vegetable oils are important for insights into their hydrogen bonding and intermolecular dynamics. The dielectric relaxation and thermo physical properties of triglycerides present in some vegetable oils have been measured over the frequency range of 10 MHz to 7 GHz in the temperature region 25 to 10 °C using a time-domain reflectometry approach. The frequency and temperature dependence of dielectric constants and dielectric loss factors were determined for coconut, peanut, soya bean, sunflower, palm, and olive oils. The dielectric permittivity spectra for each of the studied vegetable oils are explained using the Debye model with their complex dielectric permittivity analyzed using the Havriliak-Negami equation. The dielectric parameters static permittivity (ε 0 ), high-frequency limiting static permittivity (ε ∞ ), average relaxation time (τ 0 ), and thermodynamic parameters such as free energy (∆F τ ), enthalpy (∆H τ ), and entropy of activation (∆S τ ) were also measured. Calculation and analysis of these thermodynamic parameters agrees with the determined dielectric parameters, giving insights into the temperature dependence of the molecular dynamics of these systems.

  8. Modeling Philippine Stock Exchange Composite Index Using Time Series Analysis

    Science.gov (United States)

    Gayo, W. S.; Urrutia, J. D.; Temple, J. M. F.; Sandoval, J. R. D.; Sanglay, J. E. A.

    2015-06-01

    This study was conducted to develop a time series model of the Philippine Stock Exchange Composite Index and its volatility using the finite mixture of ARIMA model with conditional variance equations such as ARCH, GARCH, EG ARCH, TARCH and PARCH models. Also, the study aimed to find out the reason behind the behaviorof PSEi, that is, which of the economic variables - Consumer Price Index, crude oil price, foreign exchange rate, gold price, interest rate, money supply, price-earnings ratio, Producers’ Price Index and terms of trade - can be used in projecting future values of PSEi and this was examined using Granger Causality Test. The findings showed that the best time series model for Philippine Stock Exchange Composite index is ARIMA(1,1,5) - ARCH(1). Also, Consumer Price Index, crude oil price and foreign exchange rate are factors concluded to Granger cause Philippine Stock Exchange Composite Index.

  9. Monitoring land surface albedo and vegetation dynamics using high spatial and temporal resolution synthetic time series from Landsat and the MODIS BRDF/NBAR/albedo product

    Science.gov (United States)

    Wang, Zhuosen; Schaaf, Crystal B.; Sun, Qingsong; Kim, JiHyun; Erb, Angela M.; Gao, Feng; Román, Miguel O.; Yang, Yun; Petroy, Shelley; Taylor, Jeffrey R.; Masek, Jeffrey G.; Morisette, Jeffrey T.; Zhang, Xiaoyang; Papuga, Shirley A.

    2017-07-01

    Seasonal vegetation phenology can significantly alter surface albedo which in turn affects the global energy balance and the albedo warming/cooling feedbacks that impact climate change. To monitor and quantify the surface dynamics of heterogeneous landscapes, high temporal and spatial resolution synthetic time series of albedo and the enhanced vegetation index (EVI) were generated from the 500 m Moderate Resolution Imaging Spectroradiometer (MODIS) operational Collection V006 daily BRDF/NBAR/albedo products and 30 m Landsat 5 albedo and near-nadir reflectance data through the use of the Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM). The traditional Landsat Albedo (Shuai et al., 2011) makes use of the MODIS BRDF/Albedo products (MCD43) by assigning appropriate BRDFs from coincident MODIS products to each Landsat image to generate a 30 m Landsat albedo product for that acquisition date. The available cloud free Landsat 5 albedos (due to clouds, generated every 16 days at best) were used in conjunction with the daily MODIS albedos to determine the appropriate 30 m albedos for the intervening daily time steps in this study. These enhanced daily 30 m spatial resolution synthetic time series were then used to track albedo and vegetation phenology dynamics over three Ameriflux tower sites (Harvard Forest in 2007, Santa Rita in 2011 and Walker Branch in 2005). These Ameriflux sites were chosen as they are all quite nearby new towers coming on line for the National Ecological Observatory Network (NEON), and thus represent locations which will be served by spatially paired albedo measures in the near future. The availability of data from the NEON towers will greatly expand the sources of tower albedometer data available for evaluation of satellite products. At these three Ameriflux tower sites the synthetic time series of broadband shortwave albedos were evaluated using the tower albedo measurements with a Root Mean Square Error (RMSE) less than 0.013 and a

  10. Suppression of vegetation in LANDSAT ETM+ remote sensing images

    Science.gov (United States)

    Yu, Le; Porwal, Alok; Holden, Eun-Jung; Dentith, Michael

    2010-05-01

    Vegetation cover is an impediment to the interpretation of multispectral remote sensing images for geological applications, especially in densely vegetated terrains. In order to enhance the underlying geological information in such terrains, it is desirable to suppress the reflectance component of vegetation. One form of spectral unmixing that has been successfully used for vegetation reflectance suppression in multispectral images is called "forced invariance". It is based on segregating components of the reflectance spectrum that are invariant with respect to a specific spectral index such as the NDVI. The forced invariance method uses algorithms such as software defoliation. However, the outputs of software defoliation are single channel data, which are not amenable to geological interpretations. Crippen and Blom (2001) proposed a new forced invariance algorithm that utilizes band statistics, rather than band ratios. The authors demonstrated the effectiveness of their algorithms on a LANDSAT TM scene from Nevada, USA, especially in open canopy areas in mixed and semi-arid terrains. In this presentation, we report the results of our experimentation with this algorithm on a densely to sparsely vegetated Landsat ETM+ scene. We selected a scene (Path 119, Row 39) acquired on 18th July, 2004. Two study areas located around the city of Hangzhou, eastern China were tested. One of them covers uninhabited hilly terrain characterized by low rugged topography, parts of the hills are densely vegetated; another one covers both inhabited urban areas and uninhabited hilly terrain, which is densely vegetated. Crippen and Blom's algorithm is implemented in the following sequential steps: (1) dark pixel correction; (2) vegetation index calculation; (3) estimation of statistical relationship between vegetation index and digital number (DN) values for each band; (4) calculation of a smooth best-fit curve for the above relationships; and finally, (5) selection of a target average DN

  11. Drought footprint on European ecosystems between 1999 and 2010 assessed by remotely sensed vegetation phenology and productivity

    DEFF Research Database (Denmark)

    Ivits, Eva; Horion, Stéphanie Marie Anne F; Fensholt, Rasmus

    2014-01-01

    bioclimatic zones. The Standardized Precipitation and Evapotranspiration Index (SPEI) was used as drought indicator whereas changes in growing season length and vegetation productivity were assessed using remote sensing time-series of Normalized Difference Vegetation Index (NDVI). Drought spatio...... length, indicating that these ecosystems did not buffer the effects of drought well. In a climate change perspective, increase in drought frequency or intensity may result in larger impacts over these ecosystems, thus management and adaptation strategies should be strengthened in these areas of concerns.......Drought affects more people than any other natural disaster but there is little understanding of how ecosystems react to droughts. This study jointly analyzed spatio-temporal changes of drought patterns with vegetation phenology and productivity changes between 1999 and 2010 in major European...

  12. Quantifying the Vegetation Health Based on the Resilience in an Arid System

    Directory of Open Access Journals (Sweden)

    Ranjbar Abolfazl

    2018-03-01

    Full Text Available Proper management of natural ecosystems is not possible without the knowledge of the health status of its components. Vegetation, as the main component of the ecosystem, plays an important role in its health. One of the key determinants of vegetation health is its resilience in the face of environmental disorders. This research was conducted in parts of the Namakzar-e Khaf watershed in Northeast of South Khorasan Province with the aim of quantifying the vegetative resilience on behalf of the ecosystem health in response to long-term precipitation changes. First, the annual precipitation standardization was performed during a thirty-year period by the SPI method. Then, the average variation in TNDVI index obtained from the Landsat satellite images was examined and the resilience was tested by calculating the four effective factors (amplitude, malleability, damping and hysteresis. According to the results, the amplitude in the survey period was 6.04% and the vegetation has had different values of damping over the years. The most prominent example of vegetation resilience occurred between 1986 and 1996, with malleability of 0.7 and damping of zero. Vegetation in this period, after the elimination of drought effects (1986, has not only returned to the amount of vegetation of reference year with severe precipitation (1996 but also increased by 0.25%. This increase, as the index of hysteresis, has been presented for the first time in the ecosystem health discussion quantitatively in the present study. A set of quantitative calculations showed that despite reduced annual precipitation and drought events, the vegetation has been able to maintain its resilience, which indicates the health of vegetation in the studied ecosystem.

  13. Environmental quality evaluation. Indexing tools to evaluate environmental quality from biological data, floristic and vegetational data in Ponte Galeria (Rome, Italy)

    International Nuclear Information System (INIS)

    Mazzocchi, F.; Castorina, M.; De Mei, M.

    1998-01-01

    In the present work the study of indexing tools to evaluate environmental quality from biological data has been performed using a certain number of floristic and vegetational indices near Macchia Grande of Ponte Galeria (Rome, Italy). The indices have been applied on the basis of the data coming from a phyto sociological study of the area. Multivariate statistics methodologies have been utilized to obtain a synthetic evaluation of the indices [it

  14. A comparison of multi-resource remote sensing data for vegetation indices

    International Nuclear Information System (INIS)

    Cao, Liqin; Wei, Lifei; Liu, Tingting

    2014-01-01

    With the development of the satellite sensor, multi-resource observation systems have become widely used. However, there is a huge difference between quantitative remote sensing products because of the different sensing observations and the quantitative retrieval algorithms. In this paper, the quantitative relationships between the normalized difference vegetation index (NDVI), the soil-adjusted vegetation index (SAVI) and the vegetation index based on the universal pattern decomposition method (VIUPD) of Landsat ETM+ and ASTER sensors are investigated. The difference in observations was examined between the two sensors, based on a pair of images. The results showed that: 1) There was a strong correlation between the different vegetation indices for the same sensor, with the coefficient of determination being greater than 0.9. 2) Whether for ASTER or Landsat, the information of VIUPD was richer than that of NDVI and SAVI. Furthermore, in dense vegetation areas, the values of NDVI and SAVI could easily reach saturation. 3) The values of SAVI were higher than NDVI in the areas of water or bare soil, while this was the opposite in areas of lush vegetation

  15. Efficient retrieval of vegetation leaf area index and canopy clumping factor from satellite data to support pollutant deposition assessments

    International Nuclear Information System (INIS)

    Nikolov, Ned; Zeller, Karl

    2006-01-01

    Canopy leaf area index (LAI) is an important structural parameter of the vegetation controlling pollutant uptake by terrestrial ecosystems. This paper presents a computationally efficient algorithm for retrieval of vegetation LAI and canopy clumping factor from satellite data using observed Simple Ratios (SR) of near-infrared to red reflectance. The method employs numerical inversion of a physics-based analytical canopy radiative transfer model that simulates the bi-directional reflectance distribution function (BRDF). The algorithm is independent of ecosystem type. The method is applied to 1-km resolution AVHRR satellite images to retrieve a geo-referenced data set of monthly LAI values for the conterminous USA. Satellite-based LAI estimates are compared against independent ground LAI measurements over a range of ecosystem types. Verification results suggest that the new algorithm represents a viable approach to LAI retrieval at continental scale, and can facilitate spatially explicit studies of regional pollutant deposition and trace gas exchange. - The paper presents a physics-based algorithm for retrieval of vegetation LAI and canopy-clumping factor from satellite data to assist research of pollutant deposition and trace-gas exchange. The method is employed to derive a monthly LAI dataset for the conterminous USA and verified at a continental scale

  16. Efficient retrieval of vegetation leaf area index and canopy clumping factor from satellite data to support pollutant deposition assessments

    Energy Technology Data Exchange (ETDEWEB)

    Nikolov, Ned [Natural Resource Research Center, 2150 Centre Avenue, Building A, Room 368, Fort Collins, CO 80526 (United States)]. E-mail: nnikolov@fs.fed.us; Zeller, Karl [USDA FS Rocky Mountain Research Station, 240 W. Prospect Road, Fort Collins, CO 80526 (United States)]. E-mail: kzeller@fs.fed.us

    2006-06-15

    Canopy leaf area index (LAI) is an important structural parameter of the vegetation controlling pollutant uptake by terrestrial ecosystems. This paper presents a computationally efficient algorithm for retrieval of vegetation LAI and canopy clumping factor from satellite data using observed Simple Ratios (SR) of near-infrared to red reflectance. The method employs numerical inversion of a physics-based analytical canopy radiative transfer model that simulates the bi-directional reflectance distribution function (BRDF). The algorithm is independent of ecosystem type. The method is applied to 1-km resolution AVHRR satellite images to retrieve a geo-referenced data set of monthly LAI values for the conterminous USA. Satellite-based LAI estimates are compared against independent ground LAI measurements over a range of ecosystem types. Verification results suggest that the new algorithm represents a viable approach to LAI retrieval at continental scale, and can facilitate spatially explicit studies of regional pollutant deposition and trace gas exchange. - The paper presents a physics-based algorithm for retrieval of vegetation LAI and canopy-clumping factor from satellite data to assist research of pollutant deposition and trace-gas exchange. The method is employed to derive a monthly LAI dataset for the conterminous USA and verified at a continental scale.

  17. Tundra vegetation effects on pan-Arctic albedo

    International Nuclear Information System (INIS)

    Loranty, Michael M; Goetz, Scott J; Beck, Pieter S A

    2011-01-01

    Recent field experiments in tundra ecosystems describe how increased shrub cover reduces winter albedo, and how subsequent changes in surface net radiation lead to altered rates of snowmelt. These findings imply that tundra vegetation change will alter regional energy budgets, but to date the effects have not been documented at regional or greater scales. Using satellite observations and a pan-Arctic vegetation map, we examined the effects of shrub vegetation on albedo across the terrestrial Arctic. We included vegetation classes dominated by low shrubs, dwarf shrubs, tussock-dominated graminoid tundra, and non-tussock graminoid tundra. Each class was further stratified by bioclimate subzones. Low-shrub tundra had higher normalized difference vegetation index values and earlier albedo decline in spring than dwarf-shrub tundra, but for tussock tundra, spring albedo declined earlier than for low-shrub tundra. Our results illustrate how relatively small changes in vegetation properties result in differences in albedo dynamics, regardless of shrub growth, that may lead to differences in net radiation upwards of 50 W m -2 at weekly time scales. Further, our findings imply that changes to the terrestrial Arctic energy budget during this important seasonal transition are under way regardless of whether recent satellite observed productivity trends are the result of shrub expansion. We conclude that a better understanding of changes in vegetation productivity and distribution in Arctic tundra is essential for accurately quantifying and predicting carbon and energy fluxes and associated climate feedbacks.

  18. Assessment of land degradation using time series trend analysis of vegetation indictors in Otindag Sandy land

    International Nuclear Information System (INIS)

    Wang, H Y; Li, Z Y; Gao, Z H; Wu, J J; Sun, B; Li, C L

    2014-01-01

    Land condition assessment is a basic prerequisite for finding the degradation of a territory, which might lead to desertification under climatic and human pressures. The temporal change in vegetation productivity is a key indicator of land degradation. In this paper, taking the Otindag Sandy Land as a case, the mean normalized difference vegetation index (NDVI a ), net primary production (NPP) and vegetation rain use efficiency (RUE) dynamic trends during 2001–2010 were analysed. The Mann-Kendall test and the Correlation Analysis method were used and their sensitivities to land degradation were evaluated. The results showed that the three vegetation indicators (NDVI a , NPP and RUE) showed a downward trend with the two methods in the past 10 years and the land was degraded. For the analysis of the three vegetation indicators (NDVI a , NPP and RUE), it indicated a decreasing trend in 62.57%, 74.16% and 88.56% of the study area according to the Mann-Kendall test and in 57.85%, 68.38% and 85.29% according to the correlation analysis method. However, the change trends were not significant, the significant trends at the 95% confidence level only accounted for a small proportion. Analysis of NDVI a , NPP and RUE series showed a significant decreasing trend in 9.21%, 4.81% and 6.51% with the Mann-Kendall test. The NPP change trends showed obvious positive link with the precipitation in the study area. While the effect of the inter-annual variation of the precipitation for RUE was small, the vegetation RUE can provide valuable insights into the status of land condition and had best sensitivity to land degradation

  19. Estimates of phytomass and net primary productivity in terrestrial ecosystems of the former Soviet Union identified by classified Global Vegetation Index

    Energy Technology Data Exchange (ETDEWEB)

    Gaston, G.G.; Kolchugina, T.P. [Oregon State Univ., Corvallis, OR (United States)

    1995-12-01

    Forty-two regions with similar vegetation and landcover were identified in the former Soviet Union (FSU) by classifying Global Vegetation Index (GVI) images. Image classes were described in terms of vegetation and landcover. Image classes appear to provide more accurate and precise descriptions for most ecosystems when compared to general thematic maps. The area of forest lands were estimated at 1,330 Mha and the actual area of forest ecosystems at 875 Mha. Arable lands were estimated to be 211 Mha. The area of the tundra biome was estimated at 261 Mha. The areas of the forest-tundra/dwarf forest, taiga, mixed-deciduous forest and forest-steppe biomes were estimated t 153, 882, 196, and 144 Mha, respectively. The areas of desert-semidesert biome and arable land with irrigated land and meadows, were estimated at 126 and 237 Mha, respectively. Vegetation and landcover types were associated with the Bazilevich database of phytomass and NPP for vegetation in the FSU. The phytomass in the FSU was estimated at 97.1 Gt C, with 86.8 in forest vegetation, 9.7 in natural non-forest and 0.6 Gt C in arable lands. The NPP was estimated at 8.6 Gt C/yr, with 3.2, 4.8, and 0.6 Gt C/yr of forest, natural non-forest, and arable ecosystems, respectively. The phytomass estimates for forests were greater than previous assessments which considered the age-class distribution of forest stands in the FSU. The NPP of natural ecosystems estimated in this study was 23% greater than previous estimates which used thematic maps to identify ecosystems. 47 refs., 4 figs., 2 tabs.

  20. Time-space trade-offs for lempel-ziv compressed indexing

    DEFF Research Database (Denmark)

    Bille, Philip; Ettienne, Mikko Berggren; Gørtz, Inge Li

    2017-01-01

    Given a string S, the compressed indexing problem is to preprocess S into a compressed representation that supports fast substring queries. The goal is to use little space relative to the compressed size of S while supporting fast queries. We present a compressed index based on the Lempel-Ziv 1977...... compression scheme. Let n, and z denote the size of the input string, and the compressed LZ77 string, respectively. We obtain the following time-space trade-offs. Given a pattern string P of length m, we can solve the problem in (i) O (m + occ lg lg n) time using O(z lg(n/z) lg lg z) space, or (ii) (m (1...... best space bound, but has a leading term in the query time of O(m(1 + lgϵ z/lg(n/z))). However, for any polynomial compression ratio, i.e., z = O(n1-δ), for constant δ > 0, this becomes O(m). Our index also supports extraction of any substring of length ℓ in O(ℓ + lg(n/z)) time. Technically, our...

  1. Analysis of Post-Fire Vegetation Recovery in the Mediterranean Basin using MODIS Derived Vegetation Indices

    Science.gov (United States)

    Hawtree, Daniel; San Miguel, Jesus; Sedano, Fernando; Kempeneers, Pieter

    2010-05-01

    covering an area of at least 1,000 ha were identified. The land-cover / land-use of these large fires sites were then evaluated using the CORINE land-cover data set, and the sites dominated primarily by natural vegetation were identified. Once these candidate sites were identified, a subset was selected across a range of locations and site characteristics for post-fire recovery analysis. To evaluate the post-fire recovery sequence in these locations, time-series of NDVI, EVI, and LAI were derived using 250 meter resolution MODIS data (MOD13Q). The vegetation index values were then compared to pre-fire values to determine recovery relative to the pre-fire vegetative state. The variability in rates of recovery are then considered with respect to moisture availability, vegetation type, and local site conditions to evaluate if any patterns of recovery can be determined.

  2. Improved Vegetation Profiles with GOCI Imagery Using Optimized BRDF Composite

    Directory of Open Access Journals (Sweden)

    Sang-il Kim

    2016-01-01

    Full Text Available The purpose of this study was to optimize a composite method for the Geostationary Ocean Color Imager (GOCI, which is the first geostationary ocean color sensor in the world. Before interpreting the sensitivity of each composite with ground measurements, we evaluated the accuracy of bidirectional reflectance distribution function (BRDF performance by comparing modeled surface reflectance from BRDF simulation with GOCI-measured surface reflectance according to composite period. The root mean square error values for modeled and measured surface reflectance showed reasonable accuracy for all of composite days since each BRDF composite period includes at least seven cloud-free angular sampling for all BRDF performances. Also, GOCI-BRDF-adjusted NDVIs with four different composite periods were compared with field-observation NDVI and we interpreted the sensitivity of temporal crop dynamics of GOCI-BRDF-adjusted NDVIs. The results showed that vegetation index seasonal profiles appeared similar to vegetation growth curves in both field observations from crop scans and GOCI normalized difference vegetation index (NDVI data. Finally, we showed that a 12-day composite period was optimal in terms of BRDF simulation accuracy, surface coverage, and real-time sensitivity.

  3. Evaluating and Quantifying the Climate-Driven Interannual Variability in Global Inventory Modeling and Mapping Studies (GIMMS) Normalized Difference Vegetation Index (NDVI3g) at Global Scales

    Science.gov (United States)

    Zeng, Fanwei; Collatz, George James; Pinzon, Jorge E.; Ivanoff, Alvaro

    2013-01-01

    Satellite observations of surface reflected solar radiation contain informationabout variability in the absorption of solar radiation by vegetation. Understanding thecauses of variability is important for models that use these data to drive land surface fluxesor for benchmarking prognostic vegetation models. Here we evaluated the interannualvariability in the new 30.5-year long global satellite-derived surface reflectance index data,Global Inventory Modeling and Mapping Studies normalized difference vegetation index(GIMMS NDVI3g). Pearsons correlation and multiple linear stepwise regression analyseswere applied to quantify the NDVI interannual variability driven by climate anomalies, andto evaluate the effects of potential interference (snow, aerosols and clouds) on the NDVIsignal. We found ecologically plausible strong controls on NDVI variability by antecedent precipitation and current monthly temperature with distinct spatial patterns. Precipitation correlations were strongest for temperate to tropical water limited herbaceous systemswhere in some regions and seasons 40 of the NDVI variance could be explained byprecipitation anomalies. Temperature correlations were strongest in northern mid- to-high-latitudes in the spring and early summer where up to 70 of the NDVI variance was explained by temperature anomalies. We find that, in western and central North America,winter-spring precipitation determines early summer growth while more recent precipitation controls NDVI variability in late summer. In contrast, current or prior wetseason precipitation anomalies were correlated with all months of NDVI in sub-tropical herbaceous vegetation. Snow, aerosols and clouds as well as unexplained phenomena still account for part of the NDVI variance despite corrections. Nevertheless, this study demonstrates that GIMMS NDVI3g represents real responses of vegetation to climate variability that are useful for global models.

  4. Remotely sensed vegetation moisture as explanatory variable of Lyme borreliosis incidence

    Science.gov (United States)

    Barrios, J. M.; Verstraeten, W. W.; Maes, P.; Clement, J.; Aerts, J. M.; Farifteh, J.; Lagrou, K.; Van Ranst, M.; Coppin, P.

    2012-08-01

    The strong correlation between environmental conditions and abundance and spatial spread of the tick Ixodes ricinus is widely documented. I. ricinus is in Europe the main vector of the bacterium Borrelia burgdorferi, the pathogen causing Lyme borreliosis (LB). Humidity in vegetated systems is a major factor in tick ecology and its effects might translate into disease incidence in humans. Time series of two remotely sensed indices with sensitivity to vegetation greenness and moisture were tested as explanatory variables of LB incidence. Wavelet-based multiresolution analysis allowed the examination of these signals at different temporal scales in study sites in Belgium, where increases in LB incidence were reported in recent years. The analysis showed the potential of the tested indices for disease monitoring, the usefulness of analyzing the signal in different time frames and the importance of local characteristics of the study area for the selection of the vegetation index.

  5. River flow response to changes in vegetation cover in a South ...

    African Journals Online (AJOL)

    It was hypothesised in this study that annual river yield (river flow as a fraction of rainfall) in the Molenaars catchment near Paarl, South Africa co-varies with an index of green vegetation cover derived from satellite data (the normalised difference vegetation index, NDVI). The catchment was partitioned into 'upland' and ...

  6. Monitoring vegetation dynamics with medium resolution MODIS-EVI time series at sub-regional scale in southern Africa

    Science.gov (United States)

    Dubovyk, Olena; Landmann, Tobias; Erasmus, Barend F. N.; Tewes, Andreas; Schellberg, Jürgen

    2015-06-01

    Currently there is a lack of knowledge on spatio-temporal patterns of land surface dynamics at medium spatial scale in southern Africa, even though this information is essential for better understanding of ecosystem response to climatic variability and human-induced land transformations. In this study, we analysed vegetation dynamics across a large area in southern Africa using the 14-years (2000-2013) of medium spatial resolution (250 m) MODIS-EVI time-series data. Specifically, we investigated temporal changes in the time series of key phenometrics including overall greenness, peak and timing of annual greenness over the monitoring period and study region. In order to specifically capture spatial and per pixel vegetation changes over time, we calculated trends in these phenometrics using a robust trend analysis method. The results showed that interannual vegetation dynamics followed precipitation patterns with clearly differentiated seasonality. The earliest peak greenness during 2000-2013 occurred at the end of January in the year 2000 and the latest peak greenness was observed at the mid of March in 2012. Specifically spatial patterns of long-term vegetation trends allowed mapping areas of (i) decrease or increase in overall greenness, (ii) decrease or increase of peak greenness, and (iii) shifts in timing of occurrence of peak greenness over the 14-year monitoring period. The observed vegetation decline in the study area was mainly attributed to human-induced factors. The obtained information is useful to guide selection of field sites for detailed vegetation studies and land rehabilitation interventions and serve as an input for a range of land surface models.

  7. Clustering of financial time series with application to index and enhanced index tracking portfolio

    Science.gov (United States)

    Dose, Christian; Cincotti, Silvano

    2005-09-01

    A stochastic-optimization technique based on time series cluster analysis is described for index tracking and enhanced index tracking problems. Our methodology solves the problem in two steps, i.e., by first selecting a subset of stocks and then setting the weight of each stock as a result of an optimization process (asset allocation). Present formulation takes into account constraints on the number of stocks and on the fraction of capital invested in each of them, whilst not including transaction costs. Computational results based on clustering selection are compared to those of random techniques and show the importance of clustering in noise reduction and robust forecasting applications, in particular for enhanced index tracking.

  8. Wiener index and Diameter of a Planar Graph in Subquadratic Time

    DEFF Research Database (Denmark)

    Wulff-Nilsen, Christian

    2009-01-01

    Consider the problem of computing the sum of distances between each pair of vertices of an unweighted graph. This sum is also known as the Wiener index of the graph, a generalization of a definition given by H. Wiener in 1947. A molecular topological index is a value obtained from the graph...... structure of a molecule such that this value (hopefully) correlates with physical and/or chemical properties of the molecule. The Wiener index is perhaps the most studied molecular topological index with more than a thousand publications. It is open whether the Wiener index of a planar graph can be obtained...... in subquadratic time. In my talk, I will solve this open problem by exhibiting an O(n2 log log n / log n) time algorithm, where n is the size of the graph. A simple modification yields an algorithm with the same time bound that computes the diameter (maximum distance between any vertex pair) of a planar graph. I...

  9. Calibration of transfer functions between phytolith, vegetation and climate for integration of grassland dynamics in vegetation models. Application to a 50,000 yr crater lake core in Tanzania.

    Science.gov (United States)

    Bremond, L.; Alexandre, A.; Hely, C.; Vincens, A.; Williamson, D.; Guiot, J.

    2004-12-01

    Global vegetation models provide a way to translate the outputs from climate models into maps of potential vegetation distribution for present, past and future. Validation of these models goes through the comparison between model outputs and vegetation proxies for well constrained past climatic periods. Grass-dominated biomes are widespread and numerous. This diversity is hardly mirrored by common proxies such as pollen, charcoal or carbon isotopes. Phytoliths are amorphous silica that precipitate in and/or between living plant cells. They are commonly used to trace grasslands dynamics. However, calibration between phytolith assemblages, vegetation, and climate parameters are scarce. This work introduces transfer functions between phytolith indices, inter-tropical grassland physiognomy, and bio-climatic data that will be available for model/data comparisons. The Iph phytolith index discriminates tall from short grass savannas in West Africa. A transfer function allows to estimate evapo-transpiration AET/PET. The Ic phytolith index accurately estimates the proportion of Pooideae and Panicoideae grass sub-families, and potentially the C4/C3 grass dominance on East African mountains. The D/P index appears as a good proxy of Leaf Area Index (LAI) in tropical areas. These environmental parameters are commonly used as vegetation model outputs, but have been, up to now, hardly estimated by vegetation proxies. These transfer functions are applied to a 50,000 yr phytolith sequence from a crater lake (9°S; 33°E Tanzania). The record is compared to the pollen vegetation reconstruction and confronted to simulations of the LPJ-GUESS vegetation model (Stitch et. al, 2003).

  10. Semi-arid vegetation response to antecedent climate and water balance windows

    Science.gov (United States)

    Thoma, David P.; Munson, Seth M.; Irvine, Kathryn M.; Witwicki, Dana L.; Bunting, Erin

    2016-01-01

    Questions Can we improve understanding of vegetation response to water availability on monthly time scales in semi-arid environments using remote sensing methods? What climatic or water balance variables and antecedent windows of time associated with these variables best relate to the condition of vegetation? Can we develop credible near-term forecasts from climate data that can be used to prepare for future climate change effects on vegetation? Location Semi-arid grasslands in Capitol Reef National Park, Utah, USA. Methods We built vegetation response models by relating the normalized difference vegetation index (NDVI) from MODIS imagery in Mar–Nov 2000–2013 to antecedent climate and water balance variables preceding the monthly NDVI observations. We compared how climate and water balance variables explained vegetation greenness and then used a multi-model ensemble of climate and water balance models to forecast monthly NDVI for three holdout years. Results Water balance variables explained vegetation greenness to a greater degree than climate variables for most growing season months. Seasonally important variables included measures of antecedent water input and storage in spring, switching to indicators of drought, input or use in summer, followed by antecedent moisture availability in autumn. In spite of similar climates, there was evidence the grazed grassland showed a response to drying conditions 1 mo sooner than the ungrazed grassland. Lead times were generally short early in the growing season and antecedent window durations increased from 3 mo early in the growing season to 1 yr or more as the growing season progressed. Forecast accuracy for three holdout years using a multi-model ensemble of climate and water balance variables outperformed forecasts made with a naïve NDVI climatology. Conclusions We determined the influence of climate and water balance on vegetation at a fine temporal scale, which presents an opportunity to forecast vegetation

  11. Greenup and evapotranspiration following the Minute 319 pulse flow to Mexico: An analysis using Landsat 8 Normalized Difference Vegetation Index (NDVI) data

    Science.gov (United States)

    Jarchow, Christopher J.; Nagler, Pamela L.; Glenn, Edward P.

    2017-01-01

    In the southwestern U.S., many riparian ecosystems have been altered by dams, water diversions, and other anthropogenic activities. This is particularly true of the Colorado River, where numerous dams and agricultural diversions have affected this water course, especially south of the U.S.–Mexico border. In the spring of 2014, 130 million cubic meters of water was released to the lower Colorado River Delta in Mexico. To understand the impact of this pulse flow release on vegetation in the delta’s riparian corridor, we analyzed a modified form of Landsat 8 Operational Land Imager (OLI) Normalized Difference Vegetation Index (NDVI*) data. We assessed greenup during the growing period and estimated actual evapotranspiration (ETa) for the period prior to (yr. 2013) and following (i.e., yr. 2014 and 2015) the pulse flow. We found a significant increase in NDVI* from 2013 to 2014 (P NDVI*. As a long term solution to the declining condition of vegetation, additional pulse releases are likely needed for restoration and survival of riparian plant communities in the Colorado River Delta.

  12. Comparison of Vegetation Indices from Rpas and SENTINEL-2 Imagery for Detecting Permanent Pastures

    Science.gov (United States)

    Piragnolo, M.; Lusiani, G.; Pirotti, F.

    2018-04-01

    Permanent pastures (PP) are defined as grasslands, which are not subjected to any tillage, but only to natural growth. They are important for local economies in the production of fodder and pastures (Ali et al. 2016). Under these definitions, a pasture is permanent when it is not under any crop-rotation, and its production is related to only irrigation, fertilization and mowing. Subsidy payments to landowners require monitoring activities to determine which sites can be considered PP. These activities are mainly done with visual field surveys by experienced personnel or lately also using remote sensing techniques. The regional agency for SPS subsidies, the Agenzia Veneta per i Pagamenti in Agricoltura (AVEPA) takes care of monitoring and control on behalf of the Veneto Region using remote sensing techniques. The investigation integrate temporal series of Sentinel-2 imagery with RPAS. Indeed, the testing area is specific region were the agricultural land is intensively cultivated for production of hay harvesting four times every year between May and October. The study goal of this study is to monitor vegetation presence and amount using the Normalized Difference Vegetation Index (NDVI), the Soil-adjusted Vegetation Index (SAVI), the Normalized Difference Water Index (NDWI), and the Normalized Difference Built Index (NDBI). The overall objective is to define for each index a set of thresholds to define if a pasture can be classified as PP or not and recognize the mowing.

  13. COMPARISON OF VEGETATION INDICES FROM RPAS AND SENTINEL-2 IMAGERY FOR DETECTING PERMANENT PASTURES

    Directory of Open Access Journals (Sweden)

    M. Piragnolo

    2018-04-01

    Full Text Available Permanent pastures (PP are defined as grasslands, which are not subjected to any tillage, but only to natural growth. They are important for local economies in the production of fodder and pastures (Ali et al. 2016. Under these definitions, a pasture is permanent when it is not under any crop-rotation, and its production is related to only irrigation, fertilization and mowing. Subsidy payments to landowners require monitoring activities to determine which sites can be considered PP. These activities are mainly done with visual field surveys by experienced personnel or lately also using remote sensing techniques. The regional agency for SPS subsidies, the Agenzia Veneta per i Pagamenti in Agricoltura (AVEPA takes care of monitoring and control on behalf of the Veneto Region using remote sensing techniques. The investigation integrate temporal series of Sentinel-2 imagery with RPAS. Indeed, the testing area is specific region were the agricultural land is intensively cultivated for production of hay harvesting four times every year between May and October. The study goal of this study is to monitor vegetation presence and amount using the Normalized Difference Vegetation Index (NDVI, the Soil-adjusted Vegetation Index (SAVI, the Normalized Difference Water Index (NDWI, and the Normalized Difference Built Index (NDBI. The overall objective is to define for each index a set of thresholds to define if a pasture can be classified as PP or not and recognize the mowing.

  14. Disaggregation of SMOS soil moisture over West Africa using the Temperature and Vegetation Dryness Index based on SEVIRI land surface parameters

    DEFF Research Database (Denmark)

    Tagesson, T.; Horion, S.; Nieto, H.

    2018-01-01

    the Temperature and Vegetation Dryness Index (TVDI) that served as SM proxy within the disaggregation process. West Africa (3 N, 26 W; 28 N, 26 E) was selected as a case study as it presents both an important North-South climate gradient and a diverse range of ecosystem types. The main challenge was to set up...... resolution of SMOS SM, with potential application for local drought/flood monitoring of importance for the livelihood of the population of West Africa....

  15. Measurement and comparison of remotely derived leaf area index predictors

    Science.gov (United States)

    Jensen, Ryan Russell

    Environmental change occurs in response to both natural and anthropogenic causes. As the world's human population continues to increase, anthropogenic change will also increase. These changes affect the health and vigor of forests throughout the world, including those in north central Florida. Leaf Area Index (LAI), the amount of leaf area per unit ground area, is an important biophysical variable that is directly related to rates of atmospheric gas exchange, biomass partitioning, and productivity. While global and local models that map biophysical parameters are prevalent in the literature, landscape to regional scale models are less common. Therefore, the ability to map and monitor LAI over landscape to regional scale areas is essential for understanding medium scale biophysical properties and how these properties affect biogeochemical cycling, biomass accumulation, and primary productivity. This study develops and verifies several new models to estimate LAI using in situ field measurements throughout north central Florida, Landsat Thematic Mapper remotely sensed imagery, remotely derived vegetation indices, simple and multiple regression, and artificial neural networks (ANNs). This study concludes that while multiple band regression and regression with individual vegetation indices (Normalized Difference Vegetation Index, Soil Adjusted Vegetation Index, Simple Ratio, and Greenness Vegetation Index) can estimate LAI, the most accurate way to estimate regional scale LAI is to train an ANN using in situ LAI data and remote sensing brightness values measured from six different portions of the electromagnetic spectrum. The new ANN method of estimating LAI is then applied to two forest ecology studies. The first study analyzes LAI in longleaf pine/turkey oak sandhills as a function of time since last burn. It concludes that in the absence of fire, sandhill LAI increases, and this may be useful for identifying where prescribed burns need to be done. The second study

  16. Global patterns of NDVI-indicated vegetation extremes and their sensitivity to climate extremes

    International Nuclear Information System (INIS)

    Liu Guo; Liu Hongyan; Yin Yi

    2013-01-01

    Extremes in climate have significant impacts on ecosystems and are expected to increase under future climate change. Extremes in vegetation could capture such impacts and indicate the vulnerability of ecosystems, but currently have not received a global long-term assessment. In this study, a robust method has been developed to detect significant extremes (low values) in biweekly time series of global normalized difference vegetation index (NDVI) from 1982 to 2006 and thus to acquire a global pattern of vegetation extreme frequency. This pattern coincides with vegetation vulnerability patterns suggested by earlier studies using different methods over different time spans, indicating a consistent mechanism of regulation. Vegetation extremes were found to aggregate in Amazonia and in the semi-arid and semi-humid regions in low and middle latitudes, while they seldom occurred in high latitudes. Among the environmental variables studied, extreme low precipitation has the highest slope against extreme vegetation. For the eight biomes analyzed, these slopes are highest in temperate broadleaf forest and temperate grassland, suggesting a higher sensitivity in these environments. The results presented here contradict the hypothesis that vegetation in water-limited semi-arid and semi-humid regions might be adapted to drought and suggest that vegetation in these regions (especially temperate broadleaf forest and temperate grassland) is highly prone to vegetation extreme events under more severe precipitation extremes. It is also suggested here that more attention be paid to precipitation-induced vegetation changes than to temperature-induced events. (letter)

  17. Monitoring vegetation cover in the postfire in Tavira - São Brás de Alportel (southern Portugal)

    Science.gov (United States)

    Ramos-Simões, Nuno A.; Granja-Martins, Fernando M.; Neto-Paixão, Helena M.; Jordán, Antonio; Zavala, Lorena M.

    2014-05-01

    1. INTRODUCTION Often, restoration of areas affected by fire faces lack of knowledge of how ecosystems respond to the action of fire. Depending on environmental conditions, structure and diversity of the vegetation or the severity of the fire, burnt systems can provide responses ranging from spontaneous recovery in a relatively short time to onset of severe degradation processes. For this reason, it is necessary to monitor the evolution of post-burned in the fire, in order to plan effective strategies for restoring systems and soil erosion control. In order to assess soil erosion risk, this research aims to is to analyse the evolution of vegetation cover in a Mediterranean burnt forest soil, using vegetation indexes derived from Landsat-7 (Thematic Mapper sensor-TM) and Landsat-8 (Operation Land Imager sensor, OLI). 2. METHODS This study was carried out in a forest area affected by a wildfire by 18-22 July 2012. The study area is located within the coordinates 37o 9' - 37o 21' N and 7o 40' - 7o 53' W, including part of the municipalities of Tavira and São Brás de Alportel (southern Portugal). The relief in the studied area has an irregular topography. Soils are shallow and develop mainly metamorphic rocks (as slates or quartzite) and igneous rocks, which produce acidic and nutrient-poor soils, poorly developed in depth. The wildfire was one of the most important fires in Portugal during the recent years, and affected more than 24000 ha. Vegetation is dominated by cork oak (Quercus suber) ,holm oaks (Quercus ilex), strawberry tree (Arbutus unedo) and sclerophyllous vegetation (mostly formed by Quercus coccifera and Rosmarinus officinalis). These species are adapted to acidic-poor soils and show a great capability of resprouting and germination after fire. The study area is poorly developed, with cork and timber harvesting and other forest products or tourism as main economic activities. The area shows a highly fragmented urban fabric with the sparse

  18. Sensitivity of the normalized difference vegetation index to subpixel canopy cover, soil albedo, and pixel scale

    Science.gov (United States)

    Jasinski, Michael F.

    1990-01-01

    An analytical framework is provided for examining the physically based behavior of the normalized difference vegetation index (NDVI) in terms of the variability in bulk subpixel landscape components and with respect to variations in pixel scales, within the context of the stochastic-geometric canopy reflectance model. Analysis focuses on regional scale variability in horizontal plant density and soil background reflectance distribution. Modeling is generalized to different plant geometries and solar angles through the use of the nondimensional solar-geometric similarity parameter. Results demonstrate that, for Poisson-distributed plants and for one deterministic distribution, NDVI increases with increasing subpixel fractional canopy amount, decreasing soil background reflectance, and increasing shadows, at least within the limitations of the geometric reflectance model. The NDVI of a pecan orchard and a juniper landscape is presented and discussed.

  19. [Progress in inversion of vegetation nitrogen concentration by hyperspectral remote sensing].

    Science.gov (United States)

    Wang, Li-Wen; Wei, Ya-Xing

    2013-10-01

    Nitrogen is the necessary element in life activity of vegetation, which takes important function in biosynthesis of protein, nucleic acid, chlorophyll, and enzyme etc, and plays a key role in vegetation photosynthesis. The technology about inversion of vegetation nitrogen concentration by hyperspectral remote sensing has been the research hotspot since the 70s of last century. With the development of hyperspectral remote sensing technology in recent years, the advantage of spectral bands subdivision in a certain spectral region provides the powerful technology measure for correlative spectral characteristic research on vegetation nitrogen. In the present paper, combined with the newest research production about monitoring vegetation nitrogen concentration by hyperspectral remote sensing published in main geography science literature in recent several years, the principle and correlated problem about monitoring vegetation nitrogen concentration by hyperspectral remote sensing were introduced. From four aspects including vegetation nitrogen spectral index, vegetation nitrogen content inversion based on chlorophyll index, regression model, and eliminating influence factors to inversion of vegetation nitrogen concentration, main technology methods about inversion of vegetation nitrogen concentration by hyperspectral remote sensing were detailedly introduced. Correlative research conclusions were summarized and analyzed, and research development trend was discussed.

  20. Impacts of vegetation onset time on the net primary productivity in a mountainous island in Pacific Asia

    International Nuclear Information System (INIS)

    Chang, Chung-Te; Wang, Hsueh-Ching; Huang, Cho-ying

    2013-01-01

    Vegetation phenology reflects the response of a terrestrial ecosystem to climate change. In this study, we attempt to evaluate the El Niño/La Niña-Southern Oscillation (ENSO)-associated temporal dynamics of the vegetation onset and its influence on the net primary productivity (NPP) in a subtropical island (Taiwan) of Pacific Asia. We utilized a decade-long (2001–2010) time series of photosynthetically active vegetation cover (PV) data, which were derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) reflectance data, to delineate the vegetation phenology. These data served as inputs for the phenological analysis toolbox TIMESAT. The results indicated that the delayed vegetation onset time was directly influenced by a dry spring (February and March) in which less than 40 mm of rainfall was received. This seasonal drought impeded vegetation growth in the subsequent growing season, most likely due to delayed impacts of moisture stress related to the preceding ENSO events. The significant correlations obtained between the annual MODIS NPP and both the vegetation onset time and the length of the growing season may imply that the accumulated rainfall in the spring season governs the annual NPP. The model simulations revealed that the frequency and intensity of the ENSO-related spring droughts might increase, which would result in cascading effects on the ecosystem metabolism. (letter)

  1. Comparing forest measurements from tree rings and a space-based index of vegetation activity in Siberia

    International Nuclear Information System (INIS)

    Bunn, Andrew G; Hughes, Malcolm K; Losleben, Mark; Kirdyanov, Alexander V; Shishov, Vladimir V; Vaganov, Eugene A; Berner, Logan T; Oltchev, Alexander

    2013-01-01

    Different methods have been developed for measuring carbon stocks and fluxes in the northern high latitudes, ranging from intensively measured small plots to space-based methods that use reflectance data to drive production efficiency models. The field of dendroecology has used samples of tree growth from radial increments to quantify long-term variability in ecosystem productivity, but these have very limited spatial domains. Since the cambium material in tree cores is itself a product of photosynthesis in the canopy, it would be ideal to link these two approaches. We examine the associations between the normalized differenced vegetation index (NDVI) and tree growth using 19 pairs of tree-ring widths (TRW) and maximum latewood density (MXD) across much of Siberia. We find consistent correlations between NDVI and both measures of tree growth and no systematic difference between MXD and TRW. At the regional level we note strong correspondence between the first principal component of tree growth and NDVI for MXD and TRW in a temperature-limited bioregion, indicating that canopy reflectance and cambial production are broadly linked. Using a network of 21 TRW chronologies from south of Lake Baikal, we find a similarly strong regional correspondence with NDVI in a markedly drier region. We show that tree growth is dominated by variation at decadal and multidecadal time periods, which the satellite record is incapable of recording given its relatively short record. (letter)

  2. [Evaluation and source analysis of the mercury pollution in soils and vegetables around a large-scale zinc smelting plant].

    Science.gov (United States)

    Liu, Fang; Wang, Shu-Xiao; Wu, Qing-Ru; Lin, Hai

    2013-02-01

    The farming soil and vegetable samples around a large-scale zinc smelter were collected for mercury content analyses, and the single pollution index method with relevant regulations was used to evaluate the pollution status of sampled soils and vegetables. The results indicated that the surface soil and vegetables were polluted with mercury to different extent. Of the soil samples, 78% exceeded the national standard. The mercury concentration in the most severely contaminated area was 29 times higher than the background concentration, reaching the severe pollution degree. The mercury concentration in all vegetable samples exceeded the standard of non-pollution vegetables. Mercury concentration, in the most severely polluted vegetables were 64.5 times of the standard, and averagely the mercury concentration in the vegetable samples was 25.4 times of the standard. For 85% of the vegetable samples, the mercury concentration, of leaves were significantly higher than that of roots, which implies that the mercury in leaves mainly came from the atmosphere. The mercury concentrations in vegetable roots were significantly correlated with that in soils, indicating the mercury in roots was mainly from soil. The mercury emissions from the zinc smelter have obvious impacts on the surrounding soils and vegetables. Key words:zinc smelting; mercury pollution; soil; vegetable; mercury content

  3. Effect of Different Household Decontamination Procedures on Antioxidant Activity and Microbial Load of Vegetables

    Directory of Open Access Journals (Sweden)

    Alimohammadi M.*

    2016-12-01

    Full Text Available Abstract Aims: Decontamination procedures are different in each country, as the other applications of disinfection, and standards. The aim of this study was to evaluate the effects of household decontaminations and storage time on the antioxidant activity and microbial load of salad vegetables. Instrument & Methods: This analytic-descriptive study was conducted on 4 types of salad vegetables; cucumber, tomato, lettuce, and sweet basil. After washing, samples with storage time of 0 day were analyzed immediately. Other samples were held in 4°C for 3 and 5 days. Five different washing and decontamination methods were compared; water washing, detergent washing, benzalkonium chloride, sequential washing and Kanz disinfecting method. The Ferric Reducing Ability of Plasma assay was used to measure the antioxidant activity. Aerobic mesophyll bacteria and total coliforms were chosen as microbial load index. ANOVA and Tukey post-hoc tests were used to analyze the data. Findings: By increasing the storage time, the antioxidant activity of all types of vegetables reduced. There was a significant decrease in antioxidant activity in all types of vegetables using sequential washing method with water, detergent, and benzalkonium chloride and Kanz disinfection method. All washing methods were effective in decontamination for either mesophyll bacteria or total coliforms, except for total coliforms in lettuce. There was no significant difference in microbial load among first 4 methods of washing (p>0.05, but a significant difference was observed in Kanz disinfection method (p<0.05. Conclusion: Kanz disinfection is the most effective decontamination method to eliminate microorganisms index, which also reduce the antioxidant activity.

  4. Integrated Gis-remote sensing processing applied to vegetation ...

    African Journals Online (AJOL)

    A remotely sensed digital image of SPOT by its linear enhancement on a large memory, high speed, and digital electronic computer revealed from false colour composite that vegetation is expressed as red. Further processing of SPOT digital image for arithmetic banding of Normalized Differential Vegetation Index (NDVI) ...

  5. Analysis of monotonic greening and browning trends from global NDVI time-series

    NARCIS (Netherlands)

    Jong, de R.; Bruin, de S.; Wit, de A.J.W.; Schaepman, M.E.; Dent, D.L.

    2011-01-01

    Remotely sensed vegetation indices are widely used to detect greening and browning trends; especially the global coverage of time-series normalized difference vegetation index (NDVI) data which are available from 1981. Seasonality and serial auto-correlation in the data have previously been dealt

  6. Body Mass Index and Operating Times in Vascular Procedures

    Directory of Open Access Journals (Sweden)

    M. Durup-Dickenson

    Full Text Available : Introduction: The influence of body mass index (BMI on operating times in central and peripheral vascular surgical procedures was investigated. Report: A national cohort of Danish patients who underwent a vascular procedure between 1983 and 2012 was used for analysis. Data were analysed with pairwise comparisons of BMI groups for operating times using the independent samples Kruskall–Wallis test. Discussion: A total of 3,255 carotid endarterectomies; 6,885 central vascular procedures; and 4,488 peripheral bypasses were included for the analysis. Median operating times for carotid endarterectomy and central vascular procedures were, respectively, 5 and 15 minutes longer in obese patients than in normal weight patients. This represents a 7% and 10% increase in median operating times, respectively. Linear and multi-adjusted linear regressions were conducted adjusting for confounders, showing a significant correlation between BMI and operating time. Obesity significantly increased the operating times in carotid endarterectomy and central vascular procedures. These may have ramifications for the individual operative stress but not necessarily on logistical operation planning. Keywords: Body mass index (BMI, Obesity, Operating time, Surgery, Vascular surgical procedures

  7. Estimation for sparse vegetation information in desertification region based on Tiangong-1 hyperspectral image.

    Science.gov (United States)

    Wu, Jun-Jun; Gao, Zhi-Hai; Li, Zeng-Yuan; Wang, Hong-Yan; Pang, Yong; Sun, Bin; Li, Chang-Long; Li, Xu-Zhi; Zhang, Jiu-Xing

    2014-03-01

    In order to estimate the sparse vegetation information accurately in desertification region, taking southeast of Sunite Right Banner, Inner Mongolia, as the test site and Tiangong-1 hyperspectral image as the main data, sparse vegetation coverage and biomass were retrieved based on normalized difference vegetation index (NDVI) and soil adjusted vegetation index (SAVI), combined with the field investigation data. Then the advantages and disadvantages between them were compared. Firstly, the correlation between vegetation indexes and vegetation coverage under different bands combination was analyzed, as well as the biomass. Secondly, the best bands combination was determined when the maximum correlation coefficient turned up between vegetation indexes (VI) and vegetation parameters. It showed that the maximum correlation coefficient between vegetation parameters and NDVI could reach as high as 0.7, while that of SAVI could nearly reach 0.8. The center wavelength of red band in the best bands combination for NDVI was 630nm, and that of the near infrared (NIR) band was 910 nm. Whereas, when the center wavelength was 620 and 920 nm respectively, they were the best combination for SAVI. Finally, the linear regression models were established to retrieve vegetation coverage and biomass based on Tiangong-1 VIs. R2 of all models was more than 0.5, while that of the model based on SAVI was higher than that based on NDVI, especially, the R2 of vegetation coverage retrieve model based on SAVI was as high as 0.59. By intersection validation, the standard errors RMSE based on SAVI models were lower than that of the model based on NDVI. The results showed that the abundant spectral information of Tiangong-1 hyperspectral image can reflect the actual vegetaion condition effectively, and SAVI can estimate the sparse vegetation information more accurately than NDVI in desertification region.

  8. THEORETICAL MODELLING STUDY ON THE RELATIONSHIP BETWEEN MULTI-FREQUENCY MICROWAVE VEGETATION INDEX AND VEGETATION PROPERTIES (OPTICAL DEPTH AND SINGLE SCATTERING ALBEDO

    Directory of Open Access Journals (Sweden)

    S. Talebi

    2018-04-01

    Full Text Available This paper presents a theoretical study of derivation Microwave Vegetation Indices (MVIs in different pairs of frequencies using two methods. In the first method calculating MVI in different frequencies based on Matrix Doubling Model (to take in to account multi scattering effects has been done and analyzed in various soil properties. The second method was based on MVI theoretical basis and its independency to underlying soil surface signals. Comparing the results from two methods with vegetation properties (single scattering albedo and optical depth indicated partial correlation between MVI from first method and optical depth, and full correlation between MVI from second method and vegetation properties. The second method to derive MVI can be used widely in global microwave vegetation monitoring.

  9. Phenological Characterization of Desert Sky Island Vegetation Communities with Remotely Sensed and Climate Time Series Data

    Directory of Open Access Journals (Sweden)

    Stuart E. Marsh

    2010-01-01

    Full Text Available Climate change and variability are expected to impact the synchronicity and interactions between the Sonoran Desert and the forested sky islands which represent steep biological and environmental gradients. The main objectives were to examine how well satellite greenness time series data and derived phenological metrics (e.g., season start, peak greenness can characterize specific vegetation communities across an elevation gradient, and to examine the interactions between climate and phenological metrics for each vegetation community. We found that representative vegetation types (11, varying between desert scrub, mesquite, grassland, mixed oak, juniper and pine, often had unique seasonal and interannual phenological trajectories and spatial patterns. Satellite derived land surface phenometrics (11 for each of the vegetation communities along the cline showed numerous distinct significant relationships in response to temperature (4 and precipitation (7 metrics. Satellite-derived sky island vegetation phenology can help assess and monitor vegetation dynamics and provide unique indicators of climate variability and patterns of change.

  10. Crop Type Classification Using Vegetation Indices of RapidEye Imagery

    Science.gov (United States)

    Ustuner, M.; Sanli, F. B.; Abdikan, S.; Esetlili, M. T.; Kurucu, Y.

    2014-09-01

    Cutting-edge remote sensing technology has a significant role for managing the natural resources as well as the any other applications about the earth observation. Crop monitoring is the one of these applications since remote sensing provides us accurate, up-to-date and cost-effective information about the crop types at the different temporal and spatial resolution. In this study, the potential use of three different vegetation indices of RapidEye imagery on crop type classification as well as the effect of each indices on classification accuracy were investigated. The Normalized Difference Vegetation Index (NDVI), the Green Normalized Difference Vegetation Index (GNDVI), and the Normalized Difference Red Edge Index (NDRE) are the three vegetation indices used in this study since all of these incorporated the near-infrared (NIR) band. RapidEye imagery is highly demanded and preferred for agricultural and forestry applications since it has red-edge and NIR bands. The study area is located in Aegean region of Turkey. Radial Basis Function (RBF) kernel was used here for the Support Vector Machines (SVMs) classification. Original bands of RapidEye imagery were excluded and classification was performed with only three vegetation indices. The contribution of each indices on image classification accuracy was also tested with single band classification. Highest classification accuracy of 87, 46 % was obtained using three vegetation indices. This obtained classification accuracy is higher than the classification accuracy of any dual-combination of these vegetation indices. Results demonstrate that NDRE has the highest contribution on classification accuracy compared to the other vegetation indices and the RapidEye imagery can get satisfactory results of classification accuracy without original bands.

  11. Future vegetation ecosystem response to warming climate over the Tibetan Plateau

    Science.gov (United States)

    Bao, Y.; Gao, Y.; Wang, Y.

    2017-12-01

    The amplified vegetation response to climate variability has been found over the Tibetan Plateau (TP) in recent decades. In this study, the potential impacts of 21st century climate change on the vegetation ecosystem over the TP are assessed based on the dynamic vegetation outputs of models from Coupled Model Intercomparison Project Phase 5 (CMIP5), and the sensitivity of the TP vegetation in response to warming climate was investigated. Models project a continuous and accelerating greening in future, especially in the eastern TP, which closely associates with the plant type upgrade due to the pronouncing warming in growing season.Vegetation leaf area index (LAI) increase well follows the global warming, suggesting the warming climate instead of co2 fertilization controlls the future TP plant growth. The warming spring may advance the start of green-up day and extend the growing season length. More carbon accumulation in vegetation and soil will intensify the TP carbon cycle and will keep it as a carbon sink in future. Keywords: Leaf Area Index (LAI), Climate Change, Global Dynamic Vegetation Models (DGVMs), CMIP5, Tibetan Plateau (TP)

  12. Single-Index Additive Vector Autoregressive Time Series Models

    KAUST Repository

    LI, YEHUA; GENTON, MARC G.

    2009-01-01

    We study a new class of nonlinear autoregressive models for vector time series, where the current vector depends on single-indexes defined on the past lags and the effects of different lags have an additive form. A sufficient condition is provided

  13. Using Landsat Vegetation Indices to Estimate Impervious Surface Fractions for European Cities

    DEFF Research Database (Denmark)

    Kaspersen, Per Skougaard; Fensholt, Rasmus; Drews, Martin

    2015-01-01

    and applicability of vegetation indices (VI), from Landsat imagery, to estimate IS fractions for European cities. The accuracy of three different measures of vegetation cover is examined for eight urban areas at different locations in Europe. The Normalized Difference Vegetation Index (NDVI) and Soil Adjusted...... Vegetation Index (SAVI) are converted to IS fractions using a regression modelling approach. Also, NDVI is used to estimate fractional vegetation cover (FR), and consequently IS fractions. All three indices provide fairly accurate estimates (MAEs ≈ 10%, MBE’s ... the potential for developing and applying a single regression model to estimate IS fractions for numerous urban areas without reducing the accuracy considerably. Our findings indicate that the models can be applied broadly for multiple urban areas, and that the accuracy is reduced only marginally by applying...

  14. Stomatal conductance, canopy temperature, and leaf area index estimation using remote sensing and OBIA techniques

    Science.gov (United States)

    S. Panda; D.M. Amatya; G. Hoogenboom

    2014-01-01

    Remotely sensed images including LANDSAT, SPOT, NAIP orthoimagery, and LiDAR and relevant processing tools can be used to predict plant stomatal conductance (gs), leaf area index (LAI), and canopy temperature, vegetation density, albedo, and soil moisture using vegetation indices like normalized difference vegetation index (NDVI) or soil adjusted...

  15. Comparison of indexing times among articles from medical, nursing, and pharmacy journals.

    Science.gov (United States)

    Rodriguez, Ryan W

    2016-04-15

    Results of an analysis of the times to indexing of articles published in medical, nursing, and pharmacy journals are reported. MEDLINE data were retrieved for articles published in selected general practice medical, nursing, and pharmacy journals and entered into the PubMed system in 2012 and 2013. Collected data included PubMed entry date, date of indexing with Medical Subject Headings (MeSH) terms, and publication characteristics. Survival analysis was performed to assess the primary outcome of time to indexing. Cox proportional hazards models were developed to assess the effect of healthcare discipline and source journal on the primary outcome. Data were collected for 19,259 articles, of which 78.7%, 12.6%, and 8.7% originated from medical, nursing, and pharmacy journals, respectively. For medical, pharmacy, and nursing journals, 97.8%, 90.8%, and 50.1% of articles, respectively, were indexed within one year of PubMed entry; the corresponding median (interquartile range) times to indexing were 52 (20-68), 186 (150-246), and 252 (168-301) days. Unadjusted hazard ratios derived from Cox models indicated that indexing within one year was significantly less likely for articles published in pharmacy or nursing journals versus medical journals and for articles from all evaluated journals versus a designated reference publication (New England Journal of Medicine). Analysis of major medical, nursing, and pharmacy journals found that articles from nursing and pharmacy journals were indexed with MeSH terms more slowly than articles from medical journals. Journal identity was significantly associated with time to indexing. Copyright © 2016 by the American Society of Health-System Pharmacists, Inc. All rights reserved.

  16. Breaks in MODIS time series portend vegetation change: verification using long-term data in an arid grassland ecosystem.

    Science.gov (United States)

    Browning, Dawn M; Maynard, Jonathan J; Karl, Jason W; Peters, Debra C

    2017-07-01

    Frequency and severity of extreme climatic events are forecast to increase in the 21st century. Predicting how managed ecosystems may respond to climatic extremes is intensified by uncertainty associated with knowing when, where, and how long effects of extreme events will be manifest in an ecosystem. In water-limited ecosystems with high inter-annual variability in rainfall, it is important to be able to distinguish responses that result from seasonal fluctuations in rainfall from long-term directional increases or decreases in precipitation. A tool that successfully distinguishes seasonal from directional biomass responses would allow land managers to make informed decisions about prioritizing mitigation strategies, allocating human resource monitoring efforts, and mobilizing resources to withstand extreme climatic events. We leveraged long-term observations (2000-2013) of quadrat-level plant biomass at multiple locations across a semiarid landscape in southern New Mexico to verify the use of Normalized Difference Vegetation Index (NDVI) time series derived from 250-m Moderate Resolution Imaging Spectroradiometer (MODIS) data as a proxy for changes in aboveground productivity. This period encompassed years of sustained drought (2000-2003) and record-breaking high rainfall (2006 and 2008) followed by subsequent drought years (2011 through 2013) that resulted in a restructuring of plant community composition in some locations. Our objective was to decompose vegetation patterns derived from MODIS NDVI over this period into contributions from (1) the long-term trend, (2) seasonal cycle, and (3) unexplained variance using the Breaks for Additive Season and Trend (BFAST) model. BFAST breakpoints in NDVI trend and seasonal components were verified with field-estimated biomass at 15 sites that differed in species richness, vegetation cover, and soil properties. We found that 34 of 45 breaks in NDVI trend reflected large changes in mean biomass and 16 of 19 seasonal

  17. Satellite time-series data for vegetation phenology detection and environmental assessment in Southeast Asia

    Science.gov (United States)

    Suepa, Tanita

    The relationship between temporal and spatial data is considered the major advantage of remote sensing in research related to biophysical characteristics. With temporally formatted remote sensing products, it is possible to monitor environmental changes as well as global climate change through time and space by analyzing vegetation phenology. Although a number of different methods have been developed to determine the seasonal cycle using time series of vegetation indices, these methods were not designed to explore and monitor changes and trends of vegetation phenology in Southeast Asia (SEA). SEA is adversely affected by impacts of climate change, which causes considerable environmental problems, and the increase in agricultural land conversion and intensification also adds to those problems. Consequently, exploring and monitoring phenological change and environmental impacts are necessary for a better understanding of the ecosystem dynamics and environmental change in this region. This research aimed to investigate inter-annual variability of vegetation phenology and rainfall seasonality, analyze the possible drivers of phenological changes from both climatic and anthropogenic factors, assess the environmental impacts in agricultural areas, and develop an enhanced visualization method for phenological information dissemination. In this research, spatio-temporal patterns of vegetation phenology were analyzed by using MODIS-EVI time series data over the period of 2001-2010. Rainfall seasonality was derived from TRMM daily rainfall rate. Additionally, this research assessed environmental impacts of GHG emissions by using the environmental model (DNDC) to quantify emissions from rice fields in Thailand. Furthermore, a web mapping application was developed to present the output of phenological and environmental analysis with interactive functions. The results revealed that satellite time-series data provided a great opportunity to study regional vegetation variability

  18. Time-delay-induced dynamical behaviors for an ecological vegetation growth system driven by cross-correlated multiplicative and additive noises.

    Science.gov (United States)

    Wang, Kang-Kang; Ye, Hui; Wang, Ya-Jun; Li, Sheng-Hong

    2018-05-14

    In this paper, the modified potential function, the stationary probability distribution function (SPDF), the mean growth time and the mean degeneration time for a vegetation growth system with time delay are investigated, where the vegetation system is assumed to be disturbed by cross-correlated multiplicative and additive noises. The results reveal some fact that the multiplicative and additive noises can both reduce the stability and speed up the decline of the vegetation system, while the strength of the noise correlation and time delay can both enhance the stability of the vegetation and slow down the depression process of the ecological system. On the other hand, with regard to the impacts of noises and time delay on the mean development and degeneration processes of the ecological system, it is discovered that 1) in the development process of the vegetation population, the increase of the noise correlation strength and time delay will restrain the regime shift from the barren state to the boom one, while the increase of the additive noise can lead to the fast regime shift from the barren state to the boom one. 2) Conversely, in the depression process of the ecological system, the increase of the strength of the correlation noise and time delay will prevent the regime shift from the boom state to the barren one. Comparatively, the increase of the additive and multiplicative noises can accelerate the regime shift from the boom state to the barren state.

  19. Study of Maowusu Sandy Land Vegetation Coverage Change Based on Modis Ndvi

    Science.gov (United States)

    Ye, Q.; Liu, H.; Lin, Y.; Han, R.

    2018-04-01

    This paper selected 2006-2016 MODIS NDVI data with a spatial resolution of 500m and time resolution of 16d, got the 11 years' time series NDVI data of Maowusu sandy land through mosaicking, projection transformation, cutting process in batch. Analysed the spatial and temporal distribution and variation characteristics of vegetation cover in year, season and month time scales by maximum value composite, and unary linear regression analysis. Then, we combined the meteorological data of 33 sites around the sandy area, analysed the response characteristics of vegetation cover change to temperature and precipitation through Pearson correlation coefficient. Studies have shown that: (1) The NDVI value has a stable increase trend, which rate is 0.0075 / a. (2) The vegetation growth have significantly difference in four seasons, the NDVI value of summer > autumn > spring > winter. (3) The NDVI value change trend is conformed to the gauss normal distribution in a year, and it comes to be largest in August, its green season is in April, and yellow season is in the middle of November, the growth period is about 220 d. (4) The vegetation has a decreasing trend from the southeast to the northwest, most part is slightly improved, and Etuokeqianqi improved significantly. (5) The correlation indexes of annual NDVI with temperature and precipitation are -0.2178 and 0.6309, the vegetation growth is mainly affected by precipitation. In this study, a complete vegetation cover analysis and evaluation model for sandy land is established. It has important guiding significance for the sand ecological environment protection.

  20. Global assessment of experimental climate warming on tundra vegetation: heterogeneity over space and time.

    Science.gov (United States)

    Elmendorf, Sarah C; Henry, Gregory H R; Hollister, Robert D; Björk, Robert G; Bjorkman, Anne D; Callaghan, Terry V; Collier, Laura Siegwart; Cooper, Elisabeth J; Cornelissen, Johannes H C; Day, Thomas A; Fosaa, Anna Maria; Gould, William A; Grétarsdóttir, Járngerður; Harte, John; Hermanutz, Luise; Hik, David S; Hofgaard, Annika; Jarrad, Frith; Jónsdóttir, Ingibjörg Svala; Keuper, Frida; Klanderud, Kari; Klein, Julia A; Koh, Saewan; Kudo, Gaku; Lang, Simone I; Loewen, Val; May, Jeremy L; Mercado, Joel; Michelsen, Anders; Molau, Ulf; Myers-Smith, Isla H; Oberbauer, Steven F; Pieper, Sara; Post, Eric; Rixen, Christian; Robinson, Clare H; Schmidt, Niels Martin; Shaver, Gaius R; Stenström, Anna; Tolvanen, Anne; Totland, Orjan; Troxler, Tiffany; Wahren, Carl-Henrik; Webber, Patrick J; Welker, Jeffery M; Wookey, Philip A

    2012-02-01

    Understanding the sensitivity of tundra vegetation to climate warming is critical to forecasting future biodiversity and vegetation feedbacks to climate. In situ warming experiments accelerate climate change on a small scale to forecast responses of local plant communities. Limitations of this approach include the apparent site-specificity of results and uncertainty about the power of short-term studies to anticipate longer term change. We address these issues with a synthesis of 61 experimental warming studies, of up to 20 years duration, in tundra sites worldwide. The response of plant groups to warming often differed with ambient summer temperature, soil moisture and experimental duration. Shrubs increased with warming only where ambient temperature was high, whereas graminoids increased primarily in the coldest study sites. Linear increases in effect size over time were frequently observed. There was little indication of saturating or accelerating effects, as would be predicted if negative or positive vegetation feedbacks were common. These results indicate that tundra vegetation exhibits strong regional variation in response to warming, and that in vulnerable regions, cumulative effects of long-term warming on tundra vegetation - and associated ecosystem consequences - have the potential to be much greater than we have observed to date. © 2011 Blackwell Publishing Ltd/CNRS.

  1. Climate contributions to vegetation variations in Central Asian drylands

    DEFF Research Database (Denmark)

    Zhou, Yu; Zhang, Li; Fensholt, Rasmus

    2015-01-01

    Central Asia comprises a large fraction of the world's drylands, known to be vulnerable to climate change. We analyzed the inter-annual trends and the impact of climate variability in the vegetation greenness for Central Asia from 1982 to 2011 using GIMMS3g normalized difference vegetation index...

  2. Using remotely sensed vegetation indices to model ecological pasture conditions in Kara-Unkur watershed, Kyrgyzstan

    Science.gov (United States)

    Masselink, Loes; Baartman, Jantiene; Verbesselt, Jan; Borchardt, Peter

    2017-04-01

    Kyrgyzstan has a long history of nomadic lifestyle in which pastures play an important role. However, currently the pastures are subject to severe grazing-induced degradation. Deteriorating levels of biomass, palatability and biodiversity reduce the pastures' productivity. To counter this and introduce sustainable pasture management, up-to-date information regarding the ecological conditions of the pastures is essential. This research aimed to investigate the potential of a remote sensing-based methodology to detect changing ecological pasture conditions in the Kara-Unkur watershed, Kyrgyzstan. The relations between Vegetation Indices (VIs) from Landsat ETM+ images and biomass, palatability and species richness field data were investigated. Both simple and multiple linear regression (MLR) analyses, including terrain attributes, were applied. Subsequently, trends of these three pasture conditions were mapped using time series analysis. The results show that biomass is most accurately estimated by a model including the Modified Soil Adjusted Vegetation Index (MSAVI) and a slope factor (R2 = 0.65, F = 0.0006). Regarding palatability, a model including the Enhanced Vegetation Index (EVI), Northness Index, Near Infrared (NIR) and Red band was most accurate (R2 = 0.61, F = 0.0160). Species richness was most accurately estimated by a model including Topographic Wetness Index (TWI), Eastness Index and estimated biomass (R2 = 0.81, F = 0.0028). Subsequent trend analyses of all three estimated ecological pasture conditions presented very similar trend patterns. Despite the need for a more robust validation, this study confirms the high potential of a remote sensing based methodology to detect changing ecological pasture conditions.

  3. Elk Distributions Relative to Spring Normalized Difference Vegetation Index Values

    International Nuclear Information System (INIS)

    Smallidge, S.T.; Baker, T.T.; VanLeeuwen, D.; Gould, W.R.; Thompson, B.C.

    2010-01-01

    Rocky Mountain elk (Cervus elaphus) that winter near San Antonio Mountain in northern New Mexico provide important recreational and economic benefits while creating management challenges related to temporospatial variation in their spring movements. Our objective was to examine spring distributions of elk in relation to vegetative emergence as it progresses across the landscape as measured by remote sensing. Spring distributions of elk were closely associated with greater photosynthetic activity of spring vegetation in 2 of 3 years as determined using NDVI values derived from AVHRR datasets. Observed elk locations were up to 271% greater than expected in the category representing the most photosynthetic activity. This association was not observed when analyses at a finer geographic scale were conducted. Managers facing challenges involving human-wildlife interactions and land-use issues should consider environmental conditions that may influence variation in elk association with greener portions of the landscape.

  4. An analysis on vegetation pattern of ecotone in North China

    Energy Technology Data Exchange (ETDEWEB)

    Jia, J.C.; Zhang, H.Y. [North China Electric Power Univ., Beijing (China). Energy and Environmental Research Center

    2008-07-01

    Vegetation pattern is influenced by several natural factors, including climatic elements, elevation factors and soil conditions. Since soil formation and soil types are influenced by water-temperature conditions, much can be learned about vegetation distribution patterns by studying the relationship between water-temperature conditions and vegetation distribution. This paper presented the results of a study whose purpose was to provide scientific evidence for exploiting natural resources, planting trees, and restoring grassland from cropland. A warmth index (WI ) and humidity index (HI) were used to examine the relation between the distribution of vegetation and the water-temperature condition in North China's ecotone, the transition area between two adjacent but different plant communities, including steppe, bush and forest ecosystems. A vegetation map of the study site was digitized and then converted into a vegetation grid map from which 17 different vegetation types were chosen as the study object. A monthly mean temperature grid map and precipitation grid map of the study site were made based on the method of spatial interpolation, by using 119 meteorological data for 50 years during the period from 1951 to 2000. The thermal distribution curves and humidity distribution curves of 17 vegetation types in North China, determined the whole range and optimum range of WI and HI of 17 vegetation types. The relative proportion of each vegetation type distributed in the optimum range of WI and HI were calculated. The vegetation pattern was analyzed according to the WI and HI standard, and was described by species and their relative amount. 10 refs., 5 tabs., 3 figs.

  5. Association between Frequency of Consumption of Fruit, Vegetables, Nuts and Pulses and BMI: Analyses of the International Study of Asthma and Allergies in Childhood (ISAAC

    Directory of Open Access Journals (Sweden)

    Clare R. Wall

    2018-03-01

    Full Text Available Diets which emphasize intakes of plant-based foods are recommended to reduce disease risk and for promoting healthy weight. The aim of this study was to examine the association between fruit, vegetables, pulses and nut intake and body mass index (BMI across countries in adolescents (13–14 years and children (6–7 years. Data from the International Study of Asthma and Allergies in Childhood; 77,243 children’s parents and 201,871 adolescents was used to examine the association between dietary intake (Food Frequency Questionnaire and BMI using general linear models, adjusting for country gross national index. Adolescents who consumed fruit, vegetables, pulses and nuts three or more times a week had a lower BMI than the never or occasional group; eating nuts three or more times a week, was associated with a BMI value of 0.274 kg/m2 lower than the never group (p < 0.001. Compared to children who never or occasionally reported eating vegetables, those reporting that they ate vegetables three or more times per week had a lower BMI of −0.079 kg/m2. In this large global study, an inverse association was observed between BMI and the reported increasing intake of vegetables in 6–7 years old and fruit, vegetables, pulses and nuts in adolescents. This study supports current dietary recommendations which emphasize the consumption of vegetables, nut and pulses, although the effect sizes were small.

  6. The Influence of Rainfall, Vegetation, Elephants and People on Fire Frequency of Miombo Woodlands, Northern Mozambique

    Science.gov (United States)

    Ribeiro, N. S.; Okin, G. S.; Shugart, H. H.; Swap, R. J.

    2008-12-01

    Miombo woodlands are important in southern Africa as they occupy over 50% of the land and, their good and services support a large proportion of people in the region. Anthropogenic fires occur in miombo every year especially in the dry season (May - October). This study explores the influence of annual rainfall, elephant density, human density and corridors, and vegetation on the fire frequency. It was carried out in Niassa Reserve located in northern Mozambique, the largest and more pristine conservation area of miombo woodlands in the world. We used a time series analysis and statistical t-test of MODIS-derived Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) to explore the relationship between biomass and fire frequency. The influence of rainfall, elephants, people and vegetation on fire return was explored using a stepwise logistic regression analysis. The results of this study indicate that fire frequency is higher in places with high biomass at beginning of the dry season. In these areas fire seems to be more intense and to strongly reduce biomass in the late dry season. Land cover is the strongest predictor of fire frequency, but elephant density, annual rainfall and human corridors are also important.

  7. Ten Years of Post-Fire Vegetation Recovery following the 2007 Zaca Fire using Landsat Satellite Imagery

    Science.gov (United States)

    Hallett, J. K. E.; Miller, D.; Roberts, D. A.

    2017-12-01

    Forest fires play a key role in shaping eco-systems. The risk to vegetation depends on the fire regime, fuel conditions (age and amount), fire temperature, and physiological characteristics such as bark thickness and stem diameter. The 2007 Zaca Fire (24 kilometers NE of Buellton, Santa Barbara County, California) burned 826.4 km2 over the course of 2 months. In this study, we used a time series of Landsat 5 Thematic Mapper and Landsat 8 Operational Land Imager imagery, to evaluate plant burn severity and post fire recovery as defined into classes of above average recovery, normal recovery, and below average recovery. We spectrally unmixed the images into green vegetation (GV), non-photosynthetic vegetation (NPV), soil surface (SOIL), and ash with a spectral library developed using Constrained Reference Endmember Selection (CRES). We delineated the fire perimeter using the differenced Normalized Burn Ratio (dNBR) and evaluated changes in this index and the Normalized Difference Vegetation Index through time. The results showed an immediate decline in GV and NPV fractions, with a rise in soil and ash fractions directly following the fire, with a slow recovery in GV fraction and a loss of bare soil cover. The was a sharp increase in the ash fraction following the fire and gradual decrease in the year after. Most areas have recovered as of 2017, with prominent recovery in the center of the burn scar and reduced recovery in areas to the south. These results indicate how post-fire vegetation varies based on initial burn severity and pre-fire GV and NPV fractions.

  8. Comparison of sap flux, moisture flux tower and MODIS enhanced vegetation index methods for estimating riparian evapotranspiration

    Science.gov (United States)

    Nagler, Pamela L.; Glenn, Edward P.; Morino, Kiyomi; Neale, Christopher M.U; Cosh, Michael H.

    2010-01-01

    Riparian evapotranspiration (ET) was measured on a salt cedar (Tamarix spp.) dominated river terrace on the Lower Colorado River from 2007 to 2009 using tissue-heat-balance sap flux sensors at six sites representing very dense, medium dense, and sparse stands of plants. Salt cedar ET varied markedly across sites, and sap flux sensors showed that plants were subject to various degrees of stress, detected as mid-day depression of transpiration and stomatal conductance. Sap flux results were scaled from the leaf level of measurement to the stand level by measuring plant-specific leaf area index and fractional ground cover at each site. Results were compared to Bowen ratio moisture tower data available for three of the sites. Sap flux sensors and flux tower results ranked the sites the same and had similar estimates of ET. A regression equation, relating measured ET of salt cedar and other riparian plants and crops on the Lower Colorado River to the Enhanced Vegetation Index from the MODIS sensor on the Terra satellite and reference crop ET measured at meteorological stations, was able to predict actual ET with an accuracy or uncertainty of about 20%, despite between-site differences for salt cedar. Peak summer salt cedar ET averaged about 6 mm d-1 across sites and methods of measurement.

  9. Global Trends in Seasonality of Normalized Difference Vegetation Index (NDVI, 1982–2011

    Directory of Open Access Journals (Sweden)

    Assaf Anyamba

    2013-09-01

    Full Text Available A 30-year series of global monthly Normalized Difference Vegetation Index (NDVI imagery derived from the Global Inventory Modeling and Mapping Studies (GIMMS NDVI3g archive was analyzed for the presence of trends in changing seasonality. Using the Seasonal Trend Analysis (STA procedure, over half (56.30% of land surfaces were found to exhibit significant trends. Almost half (46.10% of the significant trends belonged to three classes of seasonal trends (or changes. Class 1 consisted of areas that experienced a uniform increase in NDVI throughout the year, and was primarily associated with forested areas, particularly broadleaf forests. Class 2 consisted of areas experiencing an increase in the amplitude of the annual seasonal signal whereby increases in NDVI in the green season were balanced by decreases in the brown season. These areas were found primarily in grassland and shrubland regions. Class 3 was found primarily in the Taiga and Tundra biomes and exhibited increases in the annual summer peak in NDVI. While no single attribution of cause could be determined for each of these classes, it was evident that they are primarily found in natural areas (as opposed to anthropogenic land cover conversions and that they are consistent with climate-related ameliorations of growing conditions during the study period.

  10. Human health risk assessment: heavy metal contamination of vegetables in Bahawalpur, Pakistan

    Directory of Open Access Journals (Sweden)

    Hafiza Hira Iqbal

    2016-01-01

    Full Text Available Dietary exposure of toxic metals is a vital concern for human health through vegetable consumption, especially in developing countries. Aim of the current study was to determine the health risk related to vegetables contamination of heavy metals by irrigated with sewage and turbine water. Irrigation water sources, soils and vegetables were analyzed for selected metals viz: Pb, Cd, Cr and Ni. Heavy metals in water samples were within the permissible limits except Cd in sewage water. The concentration of heavy metals in soil and vegetables irrigated with turbine water were lower than the safe limits. In case of vegetables irrigated with sewage water, Cd was higher in soil while Pb, Cd and Cr were higher in most of the vegetables. Daily intake of metals, health risk index and Bio-concentration factor was also determined. Health risk index values for Cd, Pb and Ni were exceeded the permissible limits (European Union, 2002. Bio-concentration factor (BCF found to be maximum (16.4 mg/kg in Coriandrum sativum cultivated with sewage water. Raphanus caudatus, Coriandrum sativum, Daucus carota, Allium sativum and Solanum tuberosum showed Health Risk Index of Cd > 1 in adults and children. Allium sativum also showed HRI of Pb > 1 in children. We conclude that the quality of vegetables irrigated with sewage water is poor and not fit for human health, evident from the high concentration of Pb, Cd and Cr. Urgent measures are required to prevent consumption and production vegetables irrigated with of sewage water in the study area.

  11. Impact of economic growth on vegetation health in China based on GIMMS NDVI

    NARCIS (Netherlands)

    Jin, X.; Wan, L.; Zhang, Y.K.; Schaepman, M.E.

    2008-01-01

    The negative impact of economic development on vegetation health in China was assessed using gross domestic product (GDP) and the Global Inventory Modelling and Mapping Studies (GIMMS) Normalized Difference Vegetation Index (NDVI) data. Five levels of vegetation changes were established based on the

  12. High School Girl's Adherence to 5-a-Day Serving's Fruits and Vegetables: An Application Theory of Planned Behavior

    Directory of Open Access Journals (Sweden)

    Babak Moeini

    2014-09-01

    Full Text Available Introduction: One of the basics of healthy eating is five times consumption of fruits and vegetable a day. Given the importance of recognizing effective factors of consuming fruit and vegetable in this group, the present study aimed to investigate high school girl's adherence to five-time serving fruits and vegetables per day in Hamadan based on the theory of planned behavior application. Materials and Methods: This descriptive-analytical study was performed on 400 girl students from high schools of Hamadan recruited with a multistage cluster sampling method. Participants filled out questionnaires including demographic variables, the theory of planned behavior constructs and a fruit and vegetable consumption measure one week later. Data analysis was performed using SPSS-18 by Chi-square, Pearson correlation and Logistic regression. Results: Fruit and vegetable consumption by female students is 3.4 times daily. Among the demographic variables, family size, mother's education, father's occupation, household income, body mass index and type of school had significant associations with fruit and vegetable consumption (P<0.05. Behavioral intention predicted 35% of the variation in daily fruit and vegetable consumption. Moreover, subjective norms, perceived behavioral control and attitude were able to predict 32% of behavioral intention. Conclusion: Fruit and vegetable consumption in female students is inadequate. The theory of planned behavior may be a useful framework to design a 5-A-Day intervention for female students.

  13. Assessment of Landsat multispectral scanner spectral indexes for monitoring arid rangeland

    Science.gov (United States)

    Musick, H. B.

    1984-01-01

    Correlations between spectral indices and vegetation parameters in south-central New Mexico were used to determine the utility of Landsat Multispectral Scanner (MSS) spectral indices in arid rangeland monitoring. In addition, spectral index change for 1976-1980 was calculated from retrospective MSS data and compared with qualitative ground truth in order to evaluate vegetation change detection by means of spectral indices. Brightness index change consistently differentiated between cover increase and decrease, but index change appears to have been offset from true cover change; this may at least partly be attributed to the failure of the methods used to standardize MSS scenes for differences in sensor response. Green vegetation indices, by contrast to brightness indices, failed to consistently differentiate between cover increase and decrease.

  14. Recovery of Vegetation Cover and Soil after the Removal of Sheep in Socorro Island, Mexico

    Directory of Open Access Journals (Sweden)

    Antonio Ortíz-Alcaraz

    2016-04-01

    Full Text Available For over 140 years, the habitat of Socorro Island in the Mexican Pacific has been altered by the presence of exotic sheep. Overgrazing, jointly with tropical storms, has caused soil erosion, and more than 2000 hectares of native vegetation have been lost. Sheep eradication was conducted from 2009 to 2012. Since then, the vegetation has begun to recover passively, modifying soil properties. The objective of our study was to verify that this island was resilient enough to be recovered and in a relatively short time scale. To confirm our hypothesis, we analyzed changes in the physical-chemical properties of the soil and vegetation cover, the last one in different times and habitats after sheep eradication. The change in vegetation cover was estimated by comparing the normalized difference vegetation index (NDVI between 2008 and 2013. In sites altered by feral sheep, soil compaction was assessed, and soil samples were taken, analyzing pH, electrical conductivity, organic carbon, total nitrogen, phosphorus, calcium, and magnesium. After a year of total sheep eradication, clear indications in the recovery of vegetation cover and improvement of soil quality parameters were observed and confirmed, specifically compaction and nitrogen, organic carbon, phosphorus, and calcium. The results seem to support our hypothesis.

  15. Observational Quantification of Climatic and Human Influences on Vegetation Greening in China

    Directory of Open Access Journals (Sweden)

    Wenjian Hua

    2017-04-01

    Full Text Available This study attempts to quantify the relative contributions of vegetation greening in China due to climatic and human influences from multiple observational datasets. Satellite measured vegetation greenness, Normalized Difference Vegetation Index (NDVI, and relevant climate, land cover, and socioeconomic data since 1982 are analyzed using a multiple linear regression (MLR method. A statistically significant positive trend of average growing-season (April–October NDVI is found over more than 34% of the vegetated areas, mainly in North China, while significant decreases in NDVI are only seen in less than 5% of the areas. The relationships between vegetation and climate (temperature, precipitation, and radiation vary by geographical location and vegetation type. We estimate the NDVI changes in association with the non-climatic effects by removing the climatic effects from the original NDVI time series using the MLR analysis. Our results indicate that land use change is the dominant factor driving the long-term changes in vegetation greenness. The significant greening in North China is due to the increase in crops, grasslands, and forests. The socioeconomic datasets provide consistent and supportive results for the non-climatic effects at the provincial level that afforestation and reduced fire events generally have a major contribution. This study provides a basis for quantifying the non-climatic effects due to possible human influences on the vegetation greening in China.

  16. Extracting Vegetation Coverage in Dry-hot Valley Regions Based on Alternating Angle Minimum Algorithm

    Science.gov (United States)

    Y Yang, M.; Wang, J.; Zhang, Q.

    2017-07-01

    Vegetation coverage is one of the most important indicators for ecological environment change, and is also an effective index for the assessment of land degradation and desertification. The dry-hot valley regions have sparse surface vegetation, and the spectral information about the vegetation in such regions usually has a weak representation in remote sensing, so there are considerable limitations for applying the commonly-used vegetation index method to calculate the vegetation coverage in the dry-hot valley regions. Therefore, in this paper, Alternating Angle Minimum (AAM) algorithm of deterministic model is adopted for selective endmember for pixel unmixing of MODIS image in order to extract the vegetation coverage, and accuracy test is carried out by the use of the Landsat TM image over the same period. As shown by the results, in the dry-hot valley regions with sparse vegetation, AAM model has a high unmixing accuracy, and the extracted vegetation coverage is close to the actual situation, so it is promising to apply the AAM model to the extraction of vegetation coverage in the dry-hot valley regions.

  17. Climatic Changes Effects On Spectral Vegetation Indices For Forested Areas Analysis From Satellite Data

    International Nuclear Information System (INIS)

    Zoran, M.; Stefan, S.

    2007-01-01

    Climate-induced changes at the land surface may in turn feed back on the climate itself through changes in soil moisture, vegetation, radiative characteristics, and surface-atmosphere exchanges of water vapor. Thresholding based on biophysical variables derived from time trajectories of satellite data is a new approach to classifying forest land cover via remote . sensing .The input data are composite values of the Normalized Difference Vegetation Index (NDVI). Classification accuracies are function of the class, comparison method and season of the year. The aim of the paper is forest biomass assessment and land-cover changes analysis due to climatic effects

  18. Variation of MODIS reflectance and vegetation indices with viewing geometry and soybean development.

    Science.gov (United States)

    Breunig, Fábio M; Galvão, Lênio S; Formaggio, Antônio R; Epiphanio, José C N

    2012-06-01

    Directional effects introduce a variability in reflectance and vegetation index determination, especially when large field-of-view sensors are used (e.g., Moderate Resolution Imaging Spectroradiometer - MODIS). In this study, we evaluated directional effects on MODIS reflectance and four vegetation indices (Normalized Difference Vegetation Index - NDVI; Enhanced Vegetation Index - EVI; Normalized Difference Water Index - NDWI(1640) and NDWI(2120)) with the soybean development in two growing seasons (2004-2005 and 2005-2006). To keep the reproductive stage for a given cultivar as a constant factor while varying viewing geometry, pairs of images obtained in close dates and opposite view angles were analyzed. By using a non-parametric statistics with bootstrapping and by normalizing these indices for angular differences among viewing directions, their sensitivities to directional effects were studied. Results showed that the variation in MODIS reflectance between consecutive phenological stages was generally smaller than that resultant from viewing geometry for closed canopies. The contrary was observed for incomplete canopies. The reflectance of the first seven MODIS bands was higher in the backscattering. Except for the EVI, the other vegetation indices had larger values in the forward scattering direction. Directional effects decreased with canopy closure. The NDVI was lesser affected by directional effects than the other indices, presenting the smallest differences between viewing directions for fixed phenological stages.

  19. Scaling of vegetation indices for environmental change studies

    International Nuclear Information System (INIS)

    Qi, J.; Huete, A.; Sorooshian, S.; Chehbouni, A.; Kerr, Y.

    1992-01-01

    The spatial integration of physical parameters in remote sensing studies is of critical concern when evaluating the global biophysical processes on the earth's surface. When high resolution physical parameters, such as vegetation indices, are degraded for integration into global scale studies, they differ from lower spatial resolution data due to spatial variability and the method by which these parameters are integrated. In this study, multi-spatial resolution data sets of SPOT and ground based data obtained at Walnut Gulch Experimental Watershed in southern Arizona, US during MONSOON '90 were used. These data sets were examined to study the variations of the vegetation index parameters when integrated into coarser resolutions. Different integration methods (conventional mean and Geostatistical mean) were used in simulations of high-to-low resolutions. The sensitivity of the integrated parameters were found to vary with both the spatial variability of the area and the integration methods. Modeled equations describing the scale-dependency of the vegetation index are suggested

  20. Use of Landsat Land Surface Temperature and Vegetation Indices for Monitoring Drought in the Salt Lake Basin Area, Turkey

    Directory of Open Access Journals (Sweden)

    Osman Orhan

    2014-01-01

    Full Text Available The main purpose of this paper is to investigate multitemporal land surface temperature (LST changes by using satellite remote sensing data. The study included a real-time field work performed during the overpass of Landsat-5 satellite on 21/08/2011 over Salt Lake, Turkey. Normalized vegetation index (NDVI, vegetation condition index (VCI, and temperature vegetation index (TVX were used for evaluating drought impact over the region between 1984 and 2011. In the image processing step, geometric and radiometric correction procedures were conducted to make satellite remote sensing data comparable with in situ measurements carried out using thermal infrared thermometer supported by hand-held GPS. The results showed that real-time ground and satellite remote sensing data were in good agreement with correlation coefficient (R2 values of 0.90. The remotely sensed and treated satellite images and resulting thematic indices maps showed that dramatic land surface temperature changes occurred (about 2∘C in the Salt Lake Basin area during the 28-year period (1984–2011. Analysis of air temperature data also showed increases at a rate of 1.5–2∘C during the same period. Intensification of irrigated agriculture particularly in the southern basin was also detected. The use of water supplies, especially groundwater, should be controlled considering particularly summer drought impacts on the basin.

  1. The effect of soil moisture on the 37 GHz microwave polarization difference index (MPDI)

    International Nuclear Information System (INIS)

    Felde, G.W.

    1998-01-01

    Previous studies have shown that the 37 GHz microwave polarization difference index (MPDI) has an inverse nonlinear relationship to the normalized difference vegetation index (NDVI) with the MPDI (NDVI) being more sensitive to vegetation density under sparse (moderate) vegetation conditions. It has also been noted that soil moisture can have a significant influence on the MPDI. This study quantifies the effect of soil moisture on the MPDI using the RADTRAN model and comparison with measurements from a few geographically restricted (eastern USA) study sites. Model results show the MPDI increases with soil moisture but its sensitivity approaches zero when soil moisture values or vegetation densities are large. Results based on special sensor microwave/imager (SSM/I) measured values of MPDI, using the NDVI as a surrogate for vegetation density and an antecedent precipitation index (API) as a surrogate for soil moisture, were consistent with those based on the model. Linear equations, one for each of three categories of vegetation density, expressing MPDI as a function of API were derived based on SSM/I measurements. These equations demonstrate that soil moisture information can be extracted from the MPDI when the NDVI is used to account for the effect of vegetation and that the effect of soil moisture on the MPDI should be taken into account if it is to be used as a vegetation index. The potential to normalize MPDI values for variations in soil moisture is discussed. (author)

  2. [Vegetation spatial and temporal dynamic characteristics based on NDVI time series trajectories in grassland opencast coal mining].

    Science.gov (United States)

    Jia, Duo; Wang, Cang Jiao; Mu, Shou Guo; Zhao, Hua

    2017-06-18

    The spatiotemporal dynamic patterns of vegetation in mining area are still unclear. This study utilized time series trajectory segmentation algorithm to fit Landsat NDVI time series which generated from fusion images at the most prosperous period of growth based on ESTARFM algorithm. Combining with the shape features of the fitted trajectory, this paper extracted five vegetation dynamic patterns including pre-disturbance type, continuous disturbance type, stabilization after disturbance type, stabilization between disturbance and recovery type, and recovery after disturbance type. The result indicated that recovery after disturbance type was the dominant vegetation change pattern among the five types of vegetation dynamic pattern, which accounted for 55.2% of the total number of pixels. The follows were stabilization after disturbance type and continuous disturbance type, accounting for 25.6% and 11.0%, respectively. The pre-disturbance type and stabilization between disturbance and recovery type accounted for 3.5% and 4.7%, respectively. Vegetation disturbance mainly occurred from 2004 to 2009 in Shengli mining area. The onset time of stable state was 2008 and the spatial locations mainlydistributed in open-pit stope and waste dump. The reco-very state mainly started since the year of 2008 and 2010, while the areas were small and mainly distributed at the periphery of open-pit stope and waste dump. Duration of disturbance was mainly 1 year. The duration of stable period usually sustained 7 years. The duration of recovery state of the type of stabilization between disturbances continued 2 to 5 years, while the type of recovery after disturbance often sustained 8 years.

  3. Influence of γ-irradiation on rehydration and cooking time of dehydrated vegetables

    International Nuclear Information System (INIS)

    Wilska-Jeszka, J.; Kubiak, B.

    1975-01-01

    Dehydrated vegetables - carrot, celery and parsley - were exposed to γ-irradiation from 60 Co at doses of 0,25 to 1 Mrad. The dose rate was 1 Mrad/hr. It was found that doses above 0,25 Mrad caused acceleration of the rehydration process and a 2-4 times shortening in cooking time. Optimum effects, without organoleptic changes, are obtained with a dose of 0,5 Mrad. The same doses decrease cellulose content and increase content of water-soluble pectins which indicates the degradation of polysacharides

  4. Fruit and Vegetable Consumption and Mortality

    DEFF Research Database (Denmark)

    Leenders, Max; Sluijs, Ivonne; Ros, Martine M

    2013-01-01

    % CI: 0.70, 1.54), and with a preventable proportion of 2.95%. This association was driven mainly by cardiovascular disease mortality (for the highest quartile, hazard ratio = 0.85, 95% CI: 0.77, 0.93). Stronger inverse associations were observed for participants with high alcohol consumption or high...... body mass index and suggested in smokers. Inverse associations were stronger for raw than for cooked vegetable consumption. These results support the evidence that fruit and vegetable consumption is associated with a lower risk of death....

  5. Performance Evaluation and Market Timing: the Skill Index

    Directory of Open Access Journals (Sweden)

    Ney Roberto Otoni de Brito

    2003-01-01

    Full Text Available MERTON (1981 examines the creation of value by fund managers selecting between stocks and fixed income instruments through market timing. HENRIKSON and MERTON (1981 proceed to propose empirical tests of funds and manager performance in market timing. BRITO, BONA and TACIRO (2003 generalize the results of MERTON (1981 and HENRIKSON and MERTON (1981 for actively managed funds with a clearly defined benchmark portfolio. In the generalized context of active portfolio management, this paper proposes a new index – the Skill Index of Brito (SIB – to measure the performance and efficiency in market timing of actively managed funds. The paper proceeds to test the performance and skill of hedge funds in Brazil using the SIB. A representative sample of 32 hedge funds with a window of 90 trading days on October 31, 1999 was obtained. The empirical tests of performance and skill use the interbank borrowing and lending rate as the passive benchmark. The results indicate the significance at the 5% level of the SIB for ten hedge funds in the sample. Among them seven funds also have shown significance at the 1% level. In sum the results indicate a majority of hedge funds with no significant skill in the Brazilian market in the examined period.

  6. Temporal profiles of vegetation indices for characterizing grazing intensity on natural grasslands in Pampa biome

    Directory of Open Access Journals (Sweden)

    Amanda Heemann Junges

    2016-08-01

    Full Text Available ABSTRACT The Pampa biome is an important ecosystem in Brazil that is highly relevant to livestock production. The objective of this study was to analyze the potential use of vegetation indices to discriminate grazing intensities on natural grasslands in the Pampa biome. Moderate Resolution Imaging Spectroradiometer (MODIS Normalized Difference Vegetation Index (NDVI and Enhanced Vegetation Index (EVI images from Jan to Dec, 2000 to 2013 series, were analyzed for natural grassland experimental units managed under high (forage allowance of 5 ± 2 % live weight – LW, moderate (13 ± 5 % LW and low grazing intensity (19 ± 7 % LW. Regardless of intensity, the temporal profiles showed lower NDVI and EVI during winter, increased values in spring because of summer species regrowth, slightly decreased values in summer, especially in years when there is a water deficit, and increased values in the fall associated with the beginning of winter forage development. The average temporal profiles of moderate grazing intensity exhibited greater vegetation index values compared with low and high grazing intensities. The temporal profiles of less vegetation index were associated with lower green biomass accumulation caused by the negative impact of stocking rates on the leaf area index under high grazing intensity and a floristic composition with a predominance of tussocks under low grazing intensity. Vegetation indices can be used for distinguishing moderate grazing intensity from low and high intensities. The average EVI values can discriminate moderate grazing intensity during any season, and the NDVI values can discriminate moderate grazing intensity during spring and winter.

  7. Drought Dynamics and Vegetation Productivity in Different Land Management Systems of Eastern Cape, South Africa—A Remote Sensing Perspective

    Directory of Open Access Journals (Sweden)

    Valerie Graw

    2017-09-01

    Full Text Available Eastern Cape Province in South Africa has experienced extreme drought events during the last decade. In South Africa, different land management systems exist belonging to two different land tenure classes: commercial large scale farming and communal small-scale subsistence farming. Communal lands are often reported to be affected by land degradation and drought events among others considered as trigger for this process. Against this background, we analyzed vegetation response to drought in different land management and land tenure systems through assessing vegetation productivity trends and monitoring the intensity, frequency and distribution of the drought hazard in grasslands and communal and commercial croplands during drought and non-drought conditions. For the observation period 2000–2016, we used time series of 250 m Vegetation Condition Index (VCI based on the Moderate Resolution Imaging Spectroradiometer (MODIS Enhanced Vegetation Index (EVI and Climate Hazard Group InfraRed Precipitation with Station data (CHIRPS precipitation data with 5 km resolution. For the assessment of vegetation dynamics, we: (1 analyzed vegetation productivity in Eastern Cape over the last 16 years with EVI; (2 analyzed the impact of drought events on vegetation productivity in grasslands as well as commercial and communal croplands; and (3 compared precipitation-vegetation dynamics between the drought season 2015/2016 and the non-drought season 2011/2012. Change in total annual vegetation productivity could detect drought years while drought dynamics during the season could be rather monitored by the VCI. Correlation of vegetation condition and precipitation indicated areas experiencing significant vegetation productivity trends showing low and even negative correlation coefficients indicating other drivers for productivity change and drought impact besides rainfall.

  8. Vegetation burn severity mapping using Landsat-8 and WorldView-2

    Science.gov (United States)

    Wu, Zhuoting; Middleton, Barry R.; Hetzler, Robert; Vogel, John M.; Dye, Dennis G.

    2015-01-01

    We used remotely sensed data from the Landsat-8 and WorldView-2 satellites to estimate vegetation burn severity of the Creek Fire on the San Carlos Apache Reservation, where wildfire occurrences affect the Tribe's crucial livestock and logging industries. Accurate pre- and post-fire canopy maps at high (0.5-meter) resolution were created from World- View-2 data to generate canopy loss maps, and multiple indices from pre- and post-fire Landsat-8 images were used to evaluate vegetation burn severity. Normalized difference vegetation index based vegetation burn severity map had the highest correlation coefficients with canopy loss map from WorldView-2. Two distinct approaches - canopy loss mapping from WorldView-2 and spectral index differencing from Landsat-8 - agreed well with the field-based burn severity estimates and are both effective for vegetation burn severity mapping. Canopy loss maps created with WorldView-2 imagery add to a short list of accurate vegetation burn severity mapping techniques that can help guide effective management of forest resources on the San Carlos Apache Reservation, and the broader fire-prone regions of the Southwest.

  9. Broad-Scale Environmental Conditions Responsible for Post-Fire Vegetation Dynamics

    OpenAIRE

    Casady, Grant M.; Marsh, Stuart E.

    2010-01-01

    Ecosystem response to disturbance is influenced by environmental conditions at a number of scales. Changes in climate have altered fire regimes across the western United States, and have also likely altered spatio-temporal patterns of post-fire vegetation regeneration. Fire occurrence data and a vegetation index (NDVI) derived from the NOAA Advanced Very High Resolution Radiometer (AVHRR) were used to monitor post-fire vegetation from 1989 to 2007. We first investigated differences in post-fi...

  10. Mapping the recovery of the burnt vegetation by classifying pre- and post-fire spectral indices

    Directory of Open Access Journals (Sweden)

    M. A Peña

    2017-12-01

    Full Text Available This study analyzed the state of recovery of the burnt vegetation in the National Park of Torres del Paine between December, 2011 and March, 2012. The calculation and comparison of the NVDI (normalized difference vegetation index of the burnt area throughout a time series of 24 Landsat images acquired before, during and after the fire (2009- 2015, showed the temporal variation in the biomass levels of the burnt vegetation. The subsequent classification and comparison of the spectral indices: NDVI, NBR (normalized burnt ratio and NDWI (normalized difference water index on a full-data available and phenologically matched pre- and post-fire image pair (acquired in October 2009 and 2014, enabled to analyze and mapping the state of recovery of the burnt vegetation. The results show that the area of the lowest classes of all the spectral indices of the pre-fire date became the most dominant on the post-fire date. The pre- and post- fire NDVI class crossing by a confusion matrix showed that the highest and most prevailing pre-fire NDVI classes, mostly corresponding to hydromorphic forests and Andean scrubs, turned into the lowest class in 2014. The remaining area, comprising Patagonian steppe, reestablished its biomass levels in 2014, mostly exhibiting the same pre-fire NDVI classes. These results may provide guidelines to monitor and manage the regeneration of the vegetation impacted by this fire.

  11. Drought impact on vegetation in pre and post fire events in Iberian Peninsula

    Science.gov (United States)

    Gouveia, C. M.; Bastos, A.; Trigo, R. M.; DaCamara, C.

    2012-04-01

    In 2004/2005, the Iberian Peninsula was stricken by an exceptional drought that affected more than one third of Portugal and part of southern Spain during more than 9 months. This severe drought had a strong negative impact on vegetation dynamics, as it coincided with the period of high photosynthetic activity (Gouveia et al., 2009). Since water availability is a crucial factor in post-fire vegetation recovery, it is desirable to assess the impact that such water-stress conditions had on fire sensitivity and post-fire vegetation recovery. Fire events in the European Mediterranean areas have become a serious problem and a major ecosystem disturbance, increasing erosion and soil degradation. In Portugal, the years 2003 and 2005 were particularly devastating. In 2003 it was registered the maximal burnt area since 1980, with more than 425000 ha burned, representing about 5% of Portuguese mainland. The 2005 fire season registered the highest number of fire occurrences in Portugal and the second year with the greatest number of fires in Spain. The high number of fire events observed during the summer 2005 in the Iberian Peninsula is linked, in part, to the extreme drought conditions that prevailed during the preceding winter and spring seasons of 2004/2005. Vegetation recovery after the 2003 and 2005 fire seasons was estimated using the mono-parametric model developed by Gouveia et al. (2010), which relies on monthly values of Normalized Difference Vegetation Index (NDVI), from 1999 to 2009, at 1kmresolution, as obtained from the VEGETATION-SPOT5 instrument.. This model was further used to evaluate the effect of drought in pre and post vegetation activity. Besides the standard NDVI, the Normalized Difference Water Index (NDWI) and the Normalized Difference Drought Index (NDDI) were computed in order to evaluate drought intensity. In the case of the burnt scars of 2003, when data corresponding to the months of drought are removed, recovery times are considerably shorter

  12. Monitoring vegetation recovery in fire-affected areas using temporal profiles of spectral signal from time series MODIS and LANDSAT satellite images

    Science.gov (United States)

    Georgopoulou, Danai; Koutsias, Nikos

    2015-04-01

    Vegetation phenology is an important element of vegetation characteristics that can be useful in vegetation monitoring especially when satellite remote sensing observations are used. In that sense temporal profiles extracted from spectral signal of time series MODIS and LANDSAT satellite images can be used to characterize vegetation phenology and thus to be helpful for monitoring vegetation recovery in fire-affected areas. The aim of this study is to explore the vegetation recovery pattern of the catastrophic wildfires that occurred in Peloponnisos, southern Greece, in 2007. These fires caused the loss of 67 lives and were recognized as the most extreme natural disaster in the country's recent history. Satellite remote sensing data from MODIS and LANDSAT satellites in the period from 2000 to 2014 were acquired and processed to extract the temporal profiles of the spectral signal for selected areas within the fire-affected areas. This dataset and time period analyzed together with the time that these fires occurred gave the opportunity to create temporal profiles seven years before and seven years after the fire. The different scale of the data used gave us the chance to understand how vegetation phenology and therefore the recovery patterns are influenced by the spatial resolution of the satellite data used. Different metrics linked to key phenological events have been created and used to assess vegetation recovery in the fire-affected areas. Our analysis was focused in the main land cover types that were mostly affected by the 2007 wildland fires. Based on CORINE land-cover maps these were agricultural lands highly interspersed with large areas of natural vegetation followed by sclerophyllous vegetation, transitional woodland shrubs, complex cultivation patterns and olive groves. Apart of the use of the original spectral data we estimated and used vegetation indices commonly found in vegetation studies as well as in burned area mapping studies. In this study we

  13. componente vegetal

    Directory of Open Access Journals (Sweden)

    Fabio Moscovich

    2005-01-01

    Full Text Available In order to determine environmental impact, indicators based on vegetation characteristics that would generate the forestry monoculture with the adjacent native forest, 32 sample unit were installed in an area of LIPSIA private enterprise, Esperanza Department, Misiones with those characteristics. The plots of 100 m2 were distributed systematically every 25 meters. The vegetation was divided in stratum: superior (DBH ≥ 10 cm, middle (1,6 cm ≤ DBH > 10 cm and inferior (DBH< cm. There were installed 10 plots in a logged native forest, 10 plots in a 18 years old Pinus elliottii Engelm. with approximately 400 trees/ha., 6 plots in a 10 – 25 years old Araucaria angustifolia (Bertd. Kuntze limiting area with approximately 900 trees/ha., and 6 plots located in this plantation. In the studied area were identified 150 vegetation species. In the inferior stratum there were found differences as function of various floristic diversity indexes. In all the cases the native forest showed larger diversity than plantations, followed by Pinus elliottii, Araucaria plantation and Araucaria limiting area. All the studied forest fitted to a logarithmical series of species distributions, that would indicate the incidence of a environmental factor in this distribution.

  14. Importance of vegetation, topography and flow paths for water transit times of base flow in alpine headwater catchments

    Directory of Open Access Journals (Sweden)

    M. H. Mueller

    2013-04-01

    Full Text Available The mean transit time (MTT of water in a catchment gives information about storage, flow paths, sources of water and thus also about retention and release of solutes in a catchment. To our knowledge there are only a few catchment studies on the influence of vegetation cover changes on base flow MTTs. The main changes in vegetation cover in the Swiss Alps are massive shrub encroachment and forest expansion into formerly open habitats. Four small and relatively steep headwater catchments in the Swiss Alps (Ursern Valley were investigated to relate different vegetation cover to water transit times. Time series of water stable isotopes were used to calculate MTTs. The high temporal variation of the stable isotope signals in precipitation was strongly dampened in stream base flow samples. MTTs of the four catchments were 70 to 102 weeks. The strong dampening of the stable isotope input signal as well as stream water geochemistry points to deeper flow paths and mixing of waters of different ages at the catchments' outlets. MTTs were neither related to topographic indices nor vegetation cover. The major part of the quickly infiltrating precipitation likely percolates through fractured and partially karstified deeper rock zones, which increases the control of bedrock flow paths on MTT. Snow accumulation and the timing of its melt play an important role for stable isotope dynamics during spring and early summer. We conclude that, in mountainous headwater catchments with relatively shallow soil layers, the hydrogeological and geochemical patterns (i.e. geochemistry, porosity and hydraulic conductivity of rocks and snow dynamics influence storage, mixing and release of water in a stronger way than vegetation cover or topography do.

  15. Effects of Warming Hiatuses on Vegetation Growth in the Northern Hemisphere

    Directory of Open Access Journals (Sweden)

    Hong Wei

    2018-04-01

    Full Text Available There have been hiatuses in global warming since the 1990s, and their potential impacts have attracted extensive attention and discussion. Changes in temperature not only directly affect the greening of vegetation but can also indirectly alter both the growth state and the growth tendency of vegetation by altering other climatic elements. The middle-high latitudes of the Northern Hemisphere (NH constitute the region that has experienced the most warming in recent decades; therefore, identifying the effects of warming hiatuses on the vegetation greening in that region is of great importance. Using satellite-derived Normalized Difference Vegetation Index (NDVI data and climatological observation data from 1982–2013, we investigated hiatuses in warming trends and their impact on vegetation greenness in the NH. Our results show that the regions with warming hiatuses in the NH accounted for 50.1% of the total area and were concentrated in Mongolia, central China, and other areas. Among these regions, 18.8% of the vegetation greenness was inhibited in the warming hiatus areas, but 31.3% of the vegetation grew faster. Because temperature was the main positive climatic factor in central China, the warming hiatuses caused the slow vegetation greening rate. However, precipitation was the main positive climatic factor affecting vegetation greenness in Mongolia; an increase in precipitation accelerated vegetation greening. The regions without a warming hiatus, which were mainly distributed in northern Russia, northern central Asia, and other areas, accounted for 49.9% of the total area. Among these regions, 21.4% of the vegetation grew faster over time, but 28.5% of the vegetation was inhibited. Temperature was the main positive factor affecting vegetation greenness in northern Russia; an increase in temperature promoted vegetation greening. However, radiation was the main positive climatic factor in northern central Asia; reductions in radiation

  16. Relationship between tourism development and vegetated landscapes in Luya Mountain Nature Reserve, Shanxi, China.

    Science.gov (United States)

    Cheng, Zhan-Hong; Zhang, Jin-Tun

    2005-09-01

    The relationship between tourism development and vegetated landscapes is analyzed for the Luya Mountain Nature Reserve (LMNR), Shanxi, China, in this study. Indices such as Sensitive Level (SL), Landscape Importance Value (LIV), information index of biodiversity (H'), Shade-tolerant Species Proportion (SSP), and Tourism Influencing Index (TII) are used to characterize vegetated landscapes, the impact of tourism, and their relationship. Their relationship is studied by Two-Way Indicator Species Analysis (TWINSPAN) and Detrended Correspondence Analysis (DCA). TWINSPAN gives correct and rapid partition to the classification, and DCA ordination shows the changing tendency of all vegetation types based on tourism development. These results reflect the ecological relationship between tourism development and vegetated landscapes. In Luya Mountain Nature Reserve, most plant communities are in good or medium condition, which shows that these vegetated landscapes can support more tourism. However, the occurrence of the bad condition shows that there is a severe contradiction between tourism development and vegetated landscapes.

  17. Association between Frequency of Consumption of Fruit, Vegetables, Nuts and Pulses and BMI: Analyses of the International Study of Asthma and Allergies in Childhood (ISAAC).

    Science.gov (United States)

    Wall, Clare R; Stewart, Alistair W; Hancox, Robert J; Murphy, Rinki; Braithwaite, Irene; Beasley, Richard; Mitchell, Edwin A

    2018-03-07

    Diets which emphasize intakes of plant-based foods are recommended to reduce disease risk and for promoting healthy weight. The aim of this study was to examine the association between fruit, vegetables, pulses and nut intake and body mass index (BMI) across countries in adolescents (13-14 years) and children (6-7 years). Data from the International Study of Asthma and Allergies in Childhood; 77,243 children's parents and 201,871 adolescents was used to examine the association between dietary intake (Food Frequency Questionnaire) and BMI using general linear models, adjusting for country gross national index. Adolescents who consumed fruit, vegetables, pulses and nuts three or more times a week had a lower BMI than the never or occasional group; eating nuts three or more times a week, was associated with a BMI value of 0.274 kg/m² lower than the never group ( p BMI of -0.079 kg/m². In this large global study, an inverse association was observed between BMI and the reported increasing intake of vegetables in 6-7 years old and fruit, vegetables, pulses and nuts in adolescents. This study supports current dietary recommendations which emphasize the consumption of vegetables, nut and pulses, although the effect sizes were small.

  18. A Method for Application of Classification Tree Models to Map Aquatic Vegetation Using Remotely Sensed Images from Different Sensors and Dates

    Directory of Open Access Journals (Sweden)

    Ying Cai

    2012-09-01

    Full Text Available In previous attempts to identify aquatic vegetation from remotely-sensed images using classification trees (CT, the images used to apply CT models to different times or locations necessarily originated from the same satellite sensor as that from which the original images used in model development came, greatly limiting the application of CT. We have developed an effective normalization method to improve the robustness of CT models when applied to images originating from different sensors and dates. A total of 965 ground-truth samples of aquatic vegetation types were obtained in 2009 and 2010 in Taihu Lake, China. Using relevant spectral indices (SI as classifiers, we manually developed a stable CT model structure and then applied a standard CT algorithm to obtain quantitative (optimal thresholds from 2009 ground-truth data and images from Landsat7-ETM+, HJ-1B-CCD, Landsat5-TM and ALOS-AVNIR-2 sensors. Optimal CT thresholds produced average classification accuracies of 78.1%, 84.7% and 74.0% for emergent vegetation, floating-leaf vegetation and submerged vegetation, respectively. However, the optimal CT thresholds for different sensor images differed from each other, with an average relative variation (RV of 6.40%. We developed and evaluated three new approaches to normalizing the images. The best-performing method (Method of 0.1% index scaling normalized the SI images using tailored percentages of extreme pixel values. Using the images normalized by Method of 0.1% index scaling, CT models for a particular sensor in which thresholds were replaced by those from the models developed for images originating from other sensors provided average classification accuracies of 76.0%, 82.8% and 68.9% for emergent vegetation, floating-leaf vegetation and submerged vegetation, respectively. Applying the CT models developed for normalized 2009 images to 2010 images resulted in high classification (78.0%–93.3% and overall (92.0%–93.1% accuracies. Our

  19. Poverty index with time-varying consumption and income distributions

    Science.gov (United States)

    Chattopadhyay, Amit K.; Kumar, T. Krishna; Mallick, Sushanta K.

    2017-03-01

    Starting from a stochastic agent-based model to represent market exchange in a developing economy, we study time variations of the probability density function of income with simultaneous variation of the consumption deprivation (CD), where CD represents the shortfall in consumption from the saturation level of an essential commodity, cereal. Together, these two models combine income-expenditure-based market dynamics with time variations in consumption due to income. In this new unified theoretical structure, exchange of trade in assets is only allowed when the income exceeds consumption-deprivation while CD itself is endogenously obtained from a separate kinetic model. Our results reveal that the nature of time variation of the CD function leads to a downward trend in the threshold level of consumption of basic necessities, suggesting a possible dietary transition in terms of lower saturation level of food-grain consumption, possibly through an improvement in the level of living. The new poverty index, defined as CD, is amenable to approximate probabilistic prediction within a short time horizon. A major achievement of this work is the intrinsic independence of the poverty index from an exogenous poverty line, making it more objective for policy formulation as opposed to existing poverty indices in the literature.

  20. Spatial and temporal patterns of greenness on the Yamal Peninsula, Russia: interactions of ecological and social factors affecting the Arctic normalized difference vegetation index

    International Nuclear Information System (INIS)

    Walker, D A; Bhatt, U S; Raynolds, M K; Romanovsky, V E; Leibman, M O; Gubarkov, A A; Khomutov, A V; Moskalenko, N G; Orekhov, P; Ukraientseva, N G; Epstein, H E; Yu, Q; Forbes, B C; Kaarlejaervi, E; Comiso, J C; Jia, G J; Kaplan, J O; Kumpula, T; Kuss, P; Matyshak, G

    2009-01-01

    The causes of a greening trend detected in the Arctic using the normalized difference vegetation index (NDVI) are still poorly understood. Changes in NDVI are a result of multiple ecological and social factors that affect tundra net primary productivity. Here we use a 25 year time series of AVHRR-derived NDVI data (AVHRR: advanced very high resolution radiometer), climate analysis, a global geographic information database and ground-based studies to examine the spatial and temporal patterns of vegetation greenness on the Yamal Peninsula, Russia. We assess the effects of climate change, gas-field development, reindeer grazing and permafrost degradation. In contrast to the case for Arctic North America, there has not been a significant trend in summer temperature or NDVI, and much of the pattern of NDVI in this region is due to disturbances. There has been a 37% change in early-summer coastal sea-ice concentration, a 4% increase in summer land temperatures and a 7% change in the average time-integrated NDVI over the length of the satellite observations. Gas-field infrastructure is not currently extensive enough to affect regional NDVI patterns. The effect of reindeer is difficult to quantitatively assess because of the lack of control areas where reindeer are excluded. Many of the greenest landscapes on the Yamal are associated with landslides and drainage networks that have resulted from ongoing rapid permafrost degradation. A warming climate and enhanced winter snow are likely to exacerbate positive feedbacks between climate and permafrost thawing. We present a diagram that summarizes the social and ecological factors that influence Arctic NDVI. The NDVI should be viewed as a powerful monitoring tool that integrates the cumulative effect of a multitude of factors affecting Arctic land-cover change.

  1. Spatial and temporal patterns of greenness on the Yamal Peninsula, Russia: interactions of ecological and social factors affecting the Arctic normalized difference vegetation index

    Energy Technology Data Exchange (ETDEWEB)

    Walker, D A; Bhatt, U S; Raynolds, M K; Romanovsky, V E [University of Alaska Fairbanks, Fairbanks, AK (United States); Leibman, M O; Gubarkov, A A; Khomutov, A V; Moskalenko, N G; Orekhov, P; Ukraientseva, N G [Earth Cryosphere Institute, Russian Academy of Science, Siberian Branch, Tyumen (Russian Federation); Epstein, H E; Yu, Q [University of Virginia, Charlottesville, VA (United States); Forbes, B C; Kaarlejaervi, E [Arctic Center, University of Lapland, Rovaniemi (Finland); Comiso, J C [NASA Goddard Space Flight Center, MD (United States); Jia, G J [Chinese Academy of Sciences, Institute for Atmospheric Physics, Beijing (China); Kaplan, J O [Swiss Federal Institute for Forest Snow and Landscape Research, Birmensdorf (Switzerland); Kumpula, T [University of Joensuu, Joensuu (Finland); Kuss, P [University of Berne, Berne (Switzerland); Matyshak, G [Moscow State University, Moscow (Russian Federation)

    2009-10-15

    The causes of a greening trend detected in the Arctic using the normalized difference vegetation index (NDVI) are still poorly understood. Changes in NDVI are a result of multiple ecological and social factors that affect tundra net primary productivity. Here we use a 25 year time series of AVHRR-derived NDVI data (AVHRR: advanced very high resolution radiometer), climate analysis, a global geographic information database and ground-based studies to examine the spatial and temporal patterns of vegetation greenness on the Yamal Peninsula, Russia. We assess the effects of climate change, gas-field development, reindeer grazing and permafrost degradation. In contrast to the case for Arctic North America, there has not been a significant trend in summer temperature or NDVI, and much of the pattern of NDVI in this region is due to disturbances. There has been a 37% change in early-summer coastal sea-ice concentration, a 4% increase in summer land temperatures and a 7% change in the average time-integrated NDVI over the length of the satellite observations. Gas-field infrastructure is not currently extensive enough to affect regional NDVI patterns. The effect of reindeer is difficult to quantitatively assess because of the lack of control areas where reindeer are excluded. Many of the greenest landscapes on the Yamal are associated with landslides and drainage networks that have resulted from ongoing rapid permafrost degradation. A warming climate and enhanced winter snow are likely to exacerbate positive feedbacks between climate and permafrost thawing. We present a diagram that summarizes the social and ecological factors that influence Arctic NDVI. The NDVI should be viewed as a powerful monitoring tool that integrates the cumulative effect of a multitude of factors affecting Arctic land-cover change.

  2. [Cross comparison of ASTER and Landsat ETM+ multispectral measurements for NDVI and SAVI vegetation indices].

    Science.gov (United States)

    Xu, Han-qiu; Zhang, Tie-jun

    2011-07-01

    The present paper investigates the quantitative relationship between the NDVI and SAVI vegetation indices of Landsat and ASTER sensors based on three tandem image pairs. The study examines how well ASTER sensor vegetation observations replicate ETM+ vegetation observations, and more importantly, the difference in the vegetation observations between the two sensors. The DN values of the three image pairs were first converted to at-sensor reflectance to reduce radiometric differences between two sensors, images. The NDVI and SAVI vegetation indices of the two sensors were then calculated using the converted reflectance. The quantitative relationship was revealed through regression analysis on the scatter plots of the vegetation index values of the two sensors. The models for the conversion between the two sensors, vegetation indices were also obtained from the regression. The results show that the difference does exist between the two sensors, vegetation indices though they have a very strong positive linear relationship. The study found that the red and near infrared measurements differ between the two sensors, with ASTER generally producing higher reflectance in the red band and lower reflectance in the near infrared band than the ETM+ sensor. This results in the ASTER sensor producing lower spectral vegetation index measurements, for the same target, than ETM+. The relative spectral response function differences in the red and near infrared bands between the two sensors are believed to be the main factor contributing to their differences in vegetation index measurements, because the red and near infrared relative spectral response features of the ASTER sensor overlap the vegetation "red edge" spectral region. The obtained conversion models have high accuracy with a RMSE less than 0.04 for both sensors' inter-conversion between corresponding vegetation indices.

  3. Application of Cocktail method in vegetation classification

    Directory of Open Access Journals (Sweden)

    Hamed Asadi

    2016-09-01

    Full Text Available This study intends to assess the application of Cocktail method in the classification of large vegetation databases. For this purpose, Buxus hyrcana dataset consisted of 442 relevés with 89 species were used and by the modified TWINSPAN. For running the Cocktail method, first primarily classification was done by modified TWINSPAN, and by performing phi analysis in the groups resulted five species were selected which had the highest fidelity value. Then sociological species groups were formed by examining co-occurrence of these 5 species with other species in the database. 21 plant communities belongs to 6 variant, 17 sub associations, 11 associations, 4 alliance, 1 order and 1 class were recognized by assigning 379 releves to the sociological species groups by using logical formulas. Also, 63 releves by the logical formula were not assigned to any sociological species groups, by FPFI index were assigned to the sociological species groups which had the most index value. According to 91% classification agreement with Brown-Blanquet classification and Cocktail classification, we suggest Cocktail method to vegetation scientists as an efficient alternative of Braun-Blanquet method to classify large vegetation databases.

  4. Vegetation Cover based on Eagleson's Ecohydrological Optimality in Northeast China Transect (NECT)

    Science.gov (United States)

    Cong, Z.; Mo, K.; Qinshu, L.; Zhang, L.

    2016-12-01

    Vegetation is considered as the indicator of climate, thus the study of vegetation growth and distribution is of great importance to cognize the ecosystem construction and functions. Vegetation cover is used as an important index to describe vegetation conditions. In Eagleson's ecohydrological optimality, the theoretical optimal vegetation cover M* can be estimated by solving water balance equations. In this study, the theory is applied in the Northeast China Transect (NECT), one of International Geosphere-Biosphere Programs (IGBP) terrestrial transects. The spatial distribution of actual vegetation cover M, which is derived from Normalized Vegetation Index (NDVI) from Moderate-resolution Imaging Spectroradiometer (MODIS), shows that there is a significant gradient ranging from 1 in the east forests to 0 in the west desert. The result indicates that the theoretical M* fits the actual M well (for forest, M* = 0.822 while M = 0.826; for grassland, M* = 0.353 while M = 0.352; the correlation coefficient between M and M* is 0.81). The reasonable calculated proportion of water balance components further demonstrates the applicability of the ecohydrological optimality theory. M* increases with the increase of LAI, leaf angle, stem fraction and temperature, and decreases with the increase of precipitation amount. This method offers the possibility to analyze the impacts of climate change to vegetation cover quantitatively, thus providing advices for eco-restoration projects.

  5. Development of multi-functional streetscape green infrastructure using a performance index approach

    International Nuclear Information System (INIS)

    Tiwary, A.; Williams, I.D.; Heidrich, O.; Namdeo, A.; Bandaru, V.; Calfapietra, C.

    2016-01-01

    This paper presents a performance evaluation framework for streetscape vegetation. A performance index (PI) is conceived using the following seven traits, specific to the street environments – Pollution Flux Potential (PFP), Carbon Sequestration Potential (CSP), Thermal Comfort Potential (TCP), Noise Attenuation Potential (NAP), Biomass Energy Potential (BEP), Environmental Stress Tolerance (EST) and Crown Projection Factor (CPF). Its application is demonstrated through a case study using fifteen street vegetation species from the UK, utilising a combination of direct field measurements and inventoried literature data. Our results indicate greater preference to small-to-medium size trees and evergreen shrubs over larger trees for streetscaping. The proposed PI approach can be potentially applied two-fold: one, for evaluation of the performance of the existing street vegetation, facilitating the prospects for further improving them through management strategies and better species selection; two, for planning new streetscapes and multi-functional biomass as part of extending the green urban infrastructure. - Highlights: • A performance evaluation framework for streetscape vegetation is presented. • Seven traits, relevant to street vegetation, are included in a performance index (PI). • The PI approach is applied to quantify and rank fifteen street vegetation species. • Medium size trees and evergreen shrubs are found more favourable for streetscapes. • The PI offers a metric for developing sustainable streetscape green infrastructure. - A performance index is developed and applied to fifteen vegetation species indicating greater preference to medium size trees and evergreen shrubs for streetscaping.

  6. Multiscale remote sensing analysis to monitor riparian and upland semiarid vegetation

    Science.gov (United States)

    Nguyen, Uyen

    Index (NDVI) average values in the adjacent uplands also decreased over thirty years and were correlated with the previous year's annual precipitation. Hence an increase in ET in the uplands did not appear to be responsible for the decrease in river flows in this study, leaving increased regional groundwater pumping as a feasible alternative explanation for decreased flows and deterioration of the riparian forest. The second research objective was to develop a new method of classification using very high-resolution aerial photo to map riparian vegetation at the species level in the Colorado River Ecosystem, Grand Canyon area, Arizona. Ground surveys have showed an obvious trend in which non-native saltcedar (Tamarix spp.) has replaced native vegetation over time. Our goal was to develop a quantitative mapping procedure to detect changes in vegetation as the ecosystem continues to respond to hydrological and climate changes. Vegetation mapping for the Colorado River Ecosystem needed an updated database map of the area covered by riparian vegetation and an indicator of species composition in the river corridor. The objective of this research was to generate a new riparian vegetation map at species level using a supervised image classification technique for the purpose of patch and landscape change detection. A new classification approach using multispectral images allowed us to successfully identify and map riparian species coverage the over whole Colorado River Ecosystem, Grand Canyon area. The new map was an improvement over the initial 2002 map since it reduced fragmentation from mixed riparian vegetation areas. The most dominant tree species in the study areas is saltcedar (Tamarix spp.). The overall accuracy is 93.48% and the kappa coefficient is 0.88. The reference initial inventory map was created using 2002 images to compare and detect changes through 2009. The third objective of my research focused on using multiplatform of remote sensing and ground calibration

  7. Using NDVI to assess vegetative land cover change in central Puget Sound.

    Science.gov (United States)

    Morawitz, Dana F; Blewett, Tina M; Cohen, Alex; Alberti, Marina

    2006-03-01

    We used the Normalized Difference Vegetation Index (NDVI) in the rapidly growing Puget Sound region over three 5-year time blocks between 1986-1999 at three spatial scales in 42 Watershed Administrative Units (WAUs) to assess changes in the amounts and patterns of green vegetation. On average, approximately 20% of the area in each WAU experienced significant NDVI change over each 5-year time block. Cumulative NDVI change over 15 years (summing change over each 5-year time block) was an average of approximately 60% of each WAU, but was as high as 100% in some. At the regional scale, seasonal weather patterns and green-up from logging were the primary drivers of observed increases in NDVI values. At the WAU scale, anthropogenic factors were important drivers of both positive and negative NDVI change. For example, population density was highly correlated with negative NDVI change over 15 years (r = 0.66, P < 0.01), as was road density (r = 0.71, P < 0.01). At the smallest scale (within 3 case study WAUs) land use differences such as preserving versus harvesting forest lands drove vegetation change. We conclude that large areas within most watersheds are continually and heavily impacted by the high levels of human use and development over short time periods. Our results indicate that varying patterns and processes can be detected at multiple scales using changes in NDVIa values.

  8. Monitoring crop leaf area index time variation from higher resolution remotely sensed data

    International Nuclear Information System (INIS)

    Jiao, Sihong

    2014-01-01

    The leaf area index (LAI) is significant for research on global climate change and ecological environment. China HJ-1 satellite has a revisit cycle of four days, providing CCD data (HJ-1 CCD) with a resolution of 30 m. However, the HJ-1 CCD is incapable of obtaining observations at multiple angles. This is problematic because single angle observations provide insufficient data for determining the LAI. This article proposes a new method for determining LAI using HJ-1 CCD data. The proposed method uses background knowledge of dynamic land surface processes that are extracted from MODerate resolution Imaging Spectroradiometer (MODIS) LAI 1-km resolution data. To process the uncertainties that arise from using two data sources with different spatial resolutions, the proposed method is implemented in a dynamitic Bayesian network scheme by integrating a LAI dynamic process model and a canopy reflectance model with remotely sensed data. Validation results showed that the determination coefficient between estimated and measured LAI was 0.791, and the RMSE was 0.61. This method can enhance the accuracy of the retrieval results while retaining the time series variation characteristics of the vegetation LAI. The results suggest that this algorithm can be widely applied to determining high-resolution leaf area indices using data from China HJ-1 satellite even if information from single angle observations are insufficient for quantitative application

  9. Urban vegetation and income segregation in drylands: a synthesis of seven metropolitan regions in the southwestern United States

    International Nuclear Information System (INIS)

    Jenerette, G Darrel; Buyantuev, Alexander; Miller, Greg; Pataki, Diane E; Gillespie, Thomas W; Pincetl, Stephanie

    2013-01-01

    To better understand how urbanization affects the amount and timing of urban vegetation in drylands we investigated remotely sensed vegetation patterns across seven large metropolitan regions in the southwestern United States. We asked (1) how low density urban land cover differed from adjacent wildland grass, herb, and shrub land covers in both the amount of vegetation and the length of the growing season, (2) how neighborhood income affected patterns of vegetation within low density urban cover, and (3) how cities differed from one another in their vegetation patterns. We found that urbanization generally has a strong influence on vegetation compared to adjacent wildlands. In four of the metropolitan regions the cumulative enhanced vegetation index (EVI) and growing season length in low density developments were higher than grass, herb, and shrub land covers. Within all metropolitan regions, there was a significant socioeconomic effect where higher income areas had a higher cumulative EVI than lower income areas. The large differences in urban vegetation among cities were related to precipitation and total domestic water use. These findings help to identify how urbanization influences vegetation, with implications for the availability of ecosystem services and requirements for irrigation in hot dryland cities. (letter)

  10. Drought Forecasting with Vegetation Temperature Condition Index Using ARIMA Models in the Guanzhong Plain

    Directory of Open Access Journals (Sweden)

    Miao Tian

    2016-08-01

    Full Text Available This paper works on the agricultural drought forecasting in the Guanzhong Plain of China using Autoregressive Integrated Moving Average (ARIMA models based on the time series of drought monitoring results of Vegetation Temperature Condition Index (VTCI. About 90 VTCI images derived from Advanced Very High Resolution Radiometer (AVHRR data were selected to develop the ARIMA models from the erecting stage to the maturity stage of winter wheat (early March to late May in each year at a ten-day interval of the years from 2000 to 2009. We take the study area overlying on the administration map around the study area, and divide the study area into 17 parts where at least one weather station is located in each part. The pixels where the 17 weather stations are located are firstly chosen and studied for their fitting models, and then the best models for all pixels of the whole area are determined. According to the procedures for the models’ development, the selected best models for the 17 pixels are identified and the forecast is done with three steps. The forecasting results of the ARIMA models were compared with the monitoring ones. The results show that with reference to the categorized VTCI drought monitoring results, the categorized forecasting results of the ARIMA models are in good agreement with the monitoring ones. The categorized drought forecasting results of the ARIMA models are more severity in the northeast of the Plain in April 2009, which are in good agreements with the monitoring ones. The absolute errors of the AR(1 models are lower than the SARIMA models, both in the frequency distributions and in the statistic results. However, the ability of SARIMA models to detect the changes of the drought situation is better than the AR(1 models. These results indicate that the ARIMA models can better forecast the category and extent of droughts and can be applied to forecast droughts in the Plain.

  11. Dealing with Variations over Space and Time in Urban Vegetation-Air Quality Assessment

    Science.gov (United States)

    Tan, P. Y.

    2017-12-01

    Studies on role of urban vegetation ameliorate poor air quality frequently encountered in urban areas should aim to answer a pertinent question: what is the net impact of urban vegetation in improving public health directly or indirectly through removal of air pollutants? Answers to this question need to consider that role of urban vegetation in air quality improvement is not just dependent on physical and physiological processes mediated by plants, it is also highly dependent on atmospheric processes. The roles of these two components thus need to be separated. This uncertainty is further complicated by heterogeneity of air quality over spatial scales and fluctuations in air quality over time. Singapore is used to illustrate these complexities. Between seasons, the main external source of atmospheric pollutants is aerosols from biomass burning in plantations in surrounding SE Asian countries, and air quality is highly dependent on wind directions dictated by monsoon systems. When air quality does deteriorate from transboundary pollution, there are also spatial differences within the city, as air pollutant levels differ in different regions. Rainfall from monsoons and other rain-bearing weather systems over Singapore also dictate the relative amounts of wet and dry deposition and the persistence of particulate matter deposited on vegetation surfaces. For locally generated air pollutants, diurnal fluctuations of anthropogenic activities, such as vehicular emissions between peak and non-peak hours, should also lead to fluctuations over the day. Not only does air quality vary from region to region, air quality within a vertical transect in the urban canopy layer also differs due to urban morphology and urban elements. A pedestrian along a treed street may experience poorer air quality than one living on highrise building, despite proximity to vegetation. There are thus interactions between climate, weather and urban context, which lead to spatial heterogeneity over

  12. Estimating vegetation vulnerability to detect areas prone to land degradation in the Mediterranean basin

    Science.gov (United States)

    Imbrenda, Vito; Coluzzi, Rosa; D'Emilio, Mariagrazia; Lanfredi, Maria; Simoniello, Tiziana

    2013-04-01

    Vegetation is one of the key components to study land degradation vulnerability because of the complex interactions and feedbacks that link it to soil. In the Mediterranean region, degradation phenomena are due to a mix of predisposing factors (thin soil horizons, low soil organic matter, increasing aridity, etc.) and bad management practices (overgrazing, deforestation, intensification of agriculture, tourism development). In particular, in areas threatened by degradation processes but still covered by vegetation, large scale soil condition evaluation is a hard task and the detection of stressed vegetation can be useful to identify on-going soil degradation phenomena and to reduce their impacts through interventions for recovery/rehabilitation. In this context the use of satellite time series can increase the efficacy and completeness of the land degradation assessment, providing precious information to understand vegetation dynamics. In order to estimate vulnerability levels in Basilicata (a Mediterranean region of Southern Italy) in the framework of PRO-LAND project (PO-FESR Basilicata 2007-2013), we crossed information on potential vegetation vulnerability with information on photosynthetic activity dynamics. Potential vegetation vulnerability represents the vulnerability related to the type of present cover in terms of fire risk, erosion protection, drought resistance and plant cover distribution. It was derived from an updated land cover map by separately analyzing each factor, and then by combining them to obtain concise information on the possible degradation exposure. The analysis of photosynthetic activity dynamics provides information on the status of vegetation, that is fundamental to discriminate the different vulnerability levels within the same land cover, i.e. the same potential vulnerability. For such a purpose, we analyzed a time series (2000-2010) of a satellite vegetation index (MODIS NDVI) with 250m resolution, available as 16-day composite

  13. Effect of imaging time on the values of the sacroiliac index

    International Nuclear Information System (INIS)

    Dodig, D.; Domljan, Z.; Popovic, S.; Simonovic, I.; Zagreb Univ.

    1988-01-01

    Quantitative scintigraphy of the sacroiliac joints was performed in a group of normal subjects and a group of subjects with unilateral and bilateral sacroiliitis. The aim of the study was to determine whether the time intervals of imaging had any effect on the values of the sacroiliac index. Imaging was performed every 30 min up to 300 min and the indices were calculated at the time intervals mentioned. We found that the values of the sacroiliac index increased in the group of normal subjects until 150 min after the application of the radiopharmaceutical, and that in the group of subjects who had sacroiliitis they increased until 210 min. The results show that the time interval optimal to quantitative sacroiliac joint imaging is at least 3 1/2 h after administration of the radiopharmaceutical. (orig.)

  14. Monitoring the Effects of Forest Restoration Treatments on Post-Fire Vegetation Recovery with MODIS Multitemporal Data

    Directory of Open Access Journals (Sweden)

    Willem J. D. van Leeuwen

    2008-03-01

    Full Text Available This study examines how satellite based time-series vegetation greenness data and phenological measurements can be used to monitor and quantify vegetation recovery after wildfire disturbances and examine how pre-fire fuel reduction restoration treatments impact fire severity and impact vegetation recovery trajectories. Pairs of wildfire affected sites and a nearby unburned reference site were chosen to measure the post-disturbance recovery in relation to climate variation. All site pairs were chosen in forested uplands in Arizona and were restricted to the area of the Rodeo-Chediski fire that occurred in 2002. Fuel reduction treatments were performed in 1999 and 2001. The inter-annual and seasonal vegetation dynamics before, during, and after wildfire events can be monitored using a time series of biweekly composited MODIS NDVI (Moderate Resolution Imaging Spectroradiometer - Normalized Difference Vegetation Index data. Time series analysis methods included difference metrics, smoothing filters, and fitting functions that were applied to extract seasonal and inter-annual change and phenological metrics from the NDVI time series data from 2000 to 2007. Pre- and post-fire Landsat data were used to compute the Normalized Burn Ratio (NBR and examine burn severity at the selected sites. The phenological metrics (pheno-metrics included the timing and greenness (i.e. NDVI for the start, peak and end of the growing season as well as proxy measures for the rate of green-up and senescence and the annual vegetation productivity. Pre-fire fuel reduction treatments resulted in lower fire severity, which reduced annual productivity much less than untreated areas within the Rodeo-Chediski fire perimeter. The seasonal metrics were shown to be useful for estimating the rate of post-fire disturbance recovery and the timing of phenological greenness phases. The use of satellite time series NDVI data and derived pheno-metrics show potential for tracking vegetation

  15. Analysis on Temporal-Spatial Changes of Vegetation Cverrge in Farming-Pastoral Ecotone of Inner Mongolia

    Science.gov (United States)

    Yan, X.; Li, J.; Yang, Z.

    2018-04-01

    Chen Barag Banner is located in the typical farming-pastoral ecotone of Inner Mongolia, and it is also the core area of Hulunbuir steppe. Typical agricultural and pastoral staggered production mode so that the vegetation growth of the region not only determines the local ecological environment, and animal husbandry production, but also have a significant impact on the whole Hulunbuir ecological security and economic development. Therefore, it is necessary to monitor the change of vegetation in this area. Based on 17 MODIS Normalized Difference Vegetation Index (NDVI) images, the authors reconstructed the dynamic change characteristics of Fraction vegetation coverage (FVC) in Chen Barag Banner from 2000 to 2016. In this paper, first at all, Pixel Decomposition Models was introduced to inversion FVC, and the time series of vegetation coverage was reconstructed. Then we analyzed the temporal-spatial changes of FVC by employing transition matrix. Finally, through image analyzing and processing, the results showed that the vegetation coverage in the study area was influenced by effectors including climate, topography and human actives. In the past 17 years, the overall effect of vegetation coverage showed a downward trend of fluctuation. The average vegetation coverage decreased from 58.81 % in 2000 to 48.14 % in 2016, and the area of vegetation cover degradation accounts for 40.09 % of the total change area. Therefore, the overall degradation trend was obvious.

  16. Interannual variations and trends in global land surface phenology derived from enhanced vegetation index during 1982-2010

    Science.gov (United States)

    Zhang, Xiaoyang; Tan, Bin; Yu, Yunyue

    2014-05-01

    Land surface phenology is widely retrieved from satellite observations at regional and global scales, and its long-term record has been demonstrated to be a valuable tool for reconstructing past climate variations, monitoring the dynamics of terrestrial ecosystems in response to climate impacts, and predicting biological responses to future climate scenarios. This study detected global land surface phenology from the advanced very high resolution radiometer (AVHRR) and the Moderate Resolution Imaging Spectroradiometer (MODIS) data from 1982 to 2010. Based on daily enhanced vegetation index at a spatial resolution of 0.05 degrees, we simulated the seasonal vegetative trajectory for each individual pixel using piecewise logistic models, which was then used to detect the onset of greenness increase (OGI) and the length of vegetation growing season (GSL). Further, both overall interannual variations and pixel-based trends were examined across Koeppen's climate regions for the periods of 1982-1999 and 2000-2010, respectively. The results show that OGI and GSL varied considerably during 1982-2010 across the globe. Generally, the interannual variation could be more than a month in precipitation-controlled tropical and dry climates while it was mainly less than 15 days in temperature-controlled temperate, cold, and polar climates. OGI, overall, shifted early, and GSL was prolonged from 1982 to 2010 in most climate regions in North America and Asia while the consistently significant trends only occurred in cold climate and polar climate in North America. The overall trends in Europe were generally insignificant. Over South America, late OGI was consistent (particularly from 1982 to 1999) while either positive or negative GSL trends in a climate region were mostly reversed between the periods of 1982-1999 and 2000-2010. In the Northern Hemisphere of Africa, OGI trends were mostly insignificant, but prolonged GSL was evident over individual climate regions during the last 3

  17. Remote sensing of vegetation dynamics in drylands

    DEFF Research Database (Denmark)

    Tian, Feng; Brandt, Martin Stefan; Liu, Yi Y.

    2016-01-01

    Monitoring long-term biomass dynamics in drylands is of great importance for many environmental applications including land degradation and global carbon cycle modeling. Biomass has extensively been estimated based on the normalized difference vegetation index (NDVI) as a measure of the vegetatio...

  18. Assessing the Influence of Precipitation Variability on the Vegetation Dynamics of the Mediterranean Rangelands using NDVI and Machine Learning

    Science.gov (United States)

    Daliakopoulos, Ioannis; Tsanis, Ioannis

    2017-04-01

    Mitigating the vulnerability of Mediterranean rangelands against degradation is limited by our ability to understand and accurately characterize those impacts in space and time. The Normalized Difference Vegetation Index (NDVI) is a radiometric measure of the photosynthetically active radiation absorbed by green vegetation canopy chlorophyll and is therefore a good surrogate measure of vegetation dynamics. On the other hand, meteorological indices such as the drought assessing Standardised Precipitation Index (SPI) are can be easily estimated from historical and projected datasets at the global scale. This work investigates the potential of driving Random Forest (RF) models with meteorological indices to approximate NDVI-based vegetation dynamics. A sufficiently large number of RF models are trained using random subsets of the dataset as predictors, in a bootstrapping approach to account for the uncertainty introduced by the subset selection. The updated E-OBS-v13.1 dataset of the ENSEMBLES EU FP6 program provides observed monthly meteorological input to estimate SPI over the Mediterranean rangelands. RF models are trained to depict vegetation dynamics using the latest version (3g.v1) of the third generation GIMMS NDVI generated from NOAA's Advanced Very High Resolution Radiometer (AVHRR) sensors. Analysis is conducted for the period 1981-2015 at a gridded spatial resolution of 25 km. Preliminary results demonstrate the potential of machine learning algorithms to effectively mimic the underlying physical relationship of drought and Earth Observation vegetation indices to provide estimates based on precipitation variability.

  19. Evaluation and cross-comparison of vegetation indices for crop monitoring from sentinel-2 and worldview-2 images

    Science.gov (United States)

    Psomiadis, Emmanouil; Dercas, Nicholas; Dalezios, Nicolas R.; Spyropoulos, Nikolaos V.

    2017-10-01

    Farmers throughout the world are constantly searching for ways to maximize their returns. Remote Sensing applications are designed to provide farmers with timely crop monitoring and production information. Such information can be used to identify crop vigor problems. Vegetation indices (VIs) derived from satellite data have been widely used to assess variations in the physiological state and biophysical properties of vegetation. However, due to the various sensor characteristics, there are differences among VIs derived from multiple sensors for the same target. Therefore, multi-sensor VI capability and effectiveness are critical but complicated issues in the application of multi-sensor vegetation observations. Various factors such as the atmospheric conditions during acquisition, sensor and geometric characteristics, such as viewing angle, field of view, and sun elevation influence direct comparability of vegetation indicators among different sensors. In the present study, two experimental areas were used which are located near the villages Nea Lefki and Melia of Larissa Prefecture in Thessaly Plain area, containing a wheat and a cotton crop, respectively. Two satellite systems with different spatial resolution, WorldView-2 (W2) and Sentinel-2 (S2) with 2 and 10 meters pixel size, were used. Normalized Difference Vegetation Index (NDVI) and Leaf Area Index (LAI) were calculated and a statistical comparison of the VIs was made to designate their correlation and dependency. Finally, several other innovative indices were calculated and compared to evaluate their effectiveness in the detection of problematic plant growth areas.

  20. Generic index of aquatic vegetation (IVAM) for a rapid assessment of ecological quality of Spanish rivers: taxonomic resolution and application to Castilla-La Mancha region; Indice Generico de Vegetacion Acuatica (IVAM): Propuesta de evaluacion rapida del estado ecologico de los rios ibericos en aplicacion de la Directiva Marco del Agua

    Energy Technology Data Exchange (ETDEWEB)

    Moreno, J. L.; Navarro, C.; Hera, J. de las

    2005-07-01

    The Water Framework Directive proposes the use of aquatic flora as a valid bio indicator for assessing the ecological status of European rivers. Due to the lack of an aquatic vegetation index for Spanish rivers, we present an index to assess trophic status or eutrophication in rivers and streams. Thus, we calculated tolerance scores and indicator values for tax from nutrient levels. the index is called IVAM (Macroscopic Aquatic Vegetation Index). The index takes into account either macrophyte or microphytes (the latter making up macroscopic growth forms) including briophytes. The IVAM showed the best correlation with nutrients besides other quality indices, indicating a solid tool to assess trophic status or eutrophication. (Author) 15 refs.

  1. Vegetation Dynamics in the Upper Guinean Forest Region of West Africa from 2001 to 2015

    Directory of Open Access Journals (Sweden)

    Zhihua Liu

    2016-12-01

    Full Text Available The Upper Guinea Forest (UGF region of West Africa is one of the most climatically marginal and human-impacted tropical forest regions in the world. Research on the patterns and drivers of vegetation change is critical for developing strategies to sustain ecosystem services in the region and to understand how climate and land use change will affect other tropical forests around the globe. We compared six spectral indices calculated from the 2001–2015 MODIS optical-infrared reflectance data with manually-interpreted measurements of woody vegetation cover from high resolution imagery. The tasseled cap wetness (TCW index was found to have the strongest association with woody vegetation cover, whereas greenness indices, such as the enhanced vegetation index (EVI, had relatively weak associations with woody cover. Trends in woody vegetation cover measured with the TCW index were analyzed using Mann–Kendall statistics and were contrasted with trends in vegetation greenness measured with EVI. In the drier West Sudanian Savanna and Guinean Forest-Savanna Mosaic ecoregions, EVI trends were primarily positive, and TCW trends were primarily negative, suggesting that woody vegetation cover was decreasing, while herbaceous vegetation cover is increasing. In the wettest tropical forests in the Western Guinean Lowland Forest ecoregion, declining trends in both TCW and EVI were indicative of widespread forest degradation resulting from human activities. Across all ecoregions, declines in woody cover were less prevalent in protected areas where human activities were restricted. Multiple lines of evidence suggested that human land use and resource extraction, rather than climate trends or short-term climatic anomalies, were the predominant drivers of recent vegetation change in the UGF region of West Africa.

  2. Large-scale assessment of soil erosion in Africa: satellites help to jointly account for dynamic rainfall and vegetation cover

    Science.gov (United States)

    Vrieling, Anton; Hoedjes, Joost C. B.; van der Velde, Marijn

    2015-04-01

    Efforts to map and monitor soil erosion need to account for the erratic nature of the soil erosion process. Soil erosion by water occurs on sloped terrain when erosive rainfall and consequent surface runoff impact soils that are not well-protected by vegetation or other soil protective measures. Both rainfall erosivity and vegetation cover are highly variable through space and time. Due to data paucity and the relative ease of spatially overlaying geographical data layers into existing models like USLE (Universal Soil Loss Equation), many studies and mapping efforts merely use average annual values for erosivity and vegetation cover as input. We first show that rainfall erosivity can be estimated from satellite precipitation data. We obtained average annual erosivity estimates from 15 yr of 3-hourly TRMM Multi-satellite Precipitation Analysis (TMPA) data (1998-2012) using intensity-erosivity relationships. Our estimates showed a positive correlation (r = 0.84) with long-term annual erosivity values of 37 stations obtained from literature. Using these TMPA erosivity retrievals, we demonstrate the large interannual variability, with maximum annual erosivity often exceeding two to three times the mean value, especially in semi-arid areas. We then calculate erosivity at a 10-daily time-step and combine this with vegetation cover development for selected locations in Africa using NDVI - normalized difference vegetation index - time series from SPOT VEGETATION. Although we do not integrate the data at this point, the joint analysis of both variables stresses the need for joint accounting for erosivity and vegetation cover for large-scale erosion assessment and monitoring.

  3. Vegetation index methods for estimating evapotranspiration by remote sensing

    Science.gov (United States)

    Glenn, Edward P.; Nagler, Pamela L.; Huete, Alfredo R.

    2010-01-01

    Evapotranspiration (ET) is the largest term after precipitation in terrestrial water budgets. Accurate estimates of ET are needed for numerous agricultural and natural resource management tasks and to project changes in hydrological cycles due to potential climate change. We explore recent methods that combine vegetation indices (VI) from satellites with ground measurements of actual ET (ETa) and meteorological data to project ETa over a wide range of biome types and scales of measurement, from local to global estimates. The majority of these use time-series imagery from the Moderate Resolution Imaging Spectrometer on the Terra satellite to project ET over seasons and years. The review explores the theoretical basis for the methods, the types of ancillary data needed, and their accuracy and limitations. Coefficients of determination between modeled ETa and measured ETa are in the range of 0.45–0.95, and root mean square errors are in the range of 10–30% of mean ETa values across biomes, similar to methods that use thermal infrared bands to estimate ETa and within the range of accuracy of the ground measurements by which they are calibrated or validated. The advent of frequent-return satellites such as Terra and planed replacement platforms, and the increasing number of moisture and carbon flux tower sites over the globe, have made these methods feasible. Examples of operational algorithms for ET in agricultural and natural ecosystems are presented. The goal of the review is to enable potential end-users from different disciplines to adapt these methods to new applications that require spatially-distributed ET estimates.

  4. A seasonal comparison of deposition velocities and retention half-times for Cs-134 and Ce-141 on cool desert vegetation

    International Nuclear Information System (INIS)

    Millard, Gloria C.; Fraley, Leslie Jr.; Markham, O.D.

    1978-01-01

    Due to a scarcity of reliable deposition velocity estimates for radionuclides (particularly those in the submicron range) pooled estimates have been used to predict population doses resulting from atmospheric releases of radioactive particulates. The use of these estimates has led to large uncertainties in whole body dose estimates. Deposition velocities and retention half-times were therefore determined for submicron aerosols of 141 Ce (biologically inactive) and 134 Cs (biologically active) on sagebrush dominated desert vegetation in SE Idaho. Approximately 250 mCi (9.3 GBq) of each radionuclide were released over stands of Artemisia tridentata (big sagebrush) and bottlebrush grass (Sitanion hystrix) during three stages of plant development - spring vegetative growth, seed development, and plant dormancy. Air filters and vegetation samples were collected immediately following each release for use in deposition velocity calculations. Vegetation sampling was continued for a period of three months to obtain retention data. Deposition velocity values were 0.20 cm/s for sagebrush and 0.025 cm/s for grass. The loss of activity on the vegetation seemed to best fit a two component exponential loss function. Short component half-times were 1 to 2 days for both species. Long component half-times were two to three weeks for the shrub species and one to two weeks for the grass species. No significant difference was observed between nuclides. (author)

  5. Estimation of Global Vegetation Productivity from Global LAnd Surface Satellite Data

    Directory of Open Access Journals (Sweden)

    Tao Yu

    2018-02-01

    Full Text Available Accurately estimating vegetation productivity is important in research on terrestrial ecosystems, carbon cycles and climate change. Eight-day gross primary production (GPP and annual net primary production (NPP are contained in MODerate Resolution Imaging Spectroradiometer (MODIS products (MOD17, which are considered the first operational datasets for monitoring global vegetation productivity. However, the cloud-contaminated MODIS leaf area index (LAI and Fraction of Photosynthetically Active Radiation (FPAR retrievals may introduce some considerable errors to MODIS GPP and NPP products. In this paper, global eight-day GPP and eight-day NPP were first estimated based on Global LAnd Surface Satellite (GLASS LAI and FPAR products. Then, GPP and NPP estimates were validated by FLUXNET GPP data and BigFoot NPP data and were compared with MODIS GPP and NPP products. Compared with MODIS GPP, a time series showed that estimated GLASS GPP in our study was more temporally continuous and spatially complete with smoother trajectories. Validated with FLUXNET GPP and BigFoot NPP, we demonstrated that estimated GLASS GPP and NPP achieved higher precision for most vegetation types.

  6. Vegetation study in support of the design and optimization of vegetative soil covers, Sandia National Laboratories, Albuquerque, New Mexico.

    Energy Technology Data Exchange (ETDEWEB)

    Peace, Gerald (Jerry) L.; Goering, Timothy James (GRAM inc., Albuquerque, NM); Knight, Paul J. (Marron and Associates, Albuquerque, NM); Ashton, Thomas S. (Marron and Associates, Albuquerque, NM)

    2004-11-01

    A vegetation study was conducted in Technical Area 3 at Sandia National Laboratories, Albuquerque, New Mexico in 2003 to assist in the design and optimization of vegetative soil covers for hazardous, radioactive, and mixed waste landfills at Sandia National Laboratories/New Mexico and Kirtland Air Force Base. The objective of the study was to obtain site-specific, vegetative input parameters for the one-dimensional code UNSAT-H and to identify suitable, diverse native plant species for use on vegetative soil covers that will persist indefinitely as a climax ecological community with little or no maintenance. The identification and selection of appropriate native plant species is critical to the proper design and long-term performance of vegetative soil covers. Major emphasis was placed on the acquisition of representative, site-specific vegetation data. Vegetative input parameters measured in the field during this study include root depth, root length density, and percent bare area. Site-specific leaf area index was not obtained in the area because there was no suitable platform to measure leaf area during the 2003 growing season due to severe drought that has persisted in New Mexico since 1999. Regional LAI data was obtained from two unique desert biomes in New Mexico, Sevilletta Wildlife Refuge and Jornada Research Station.

  7. Multi-scale enhancement of climate prediction over land by improving the model sensitivity to vegetation variability

    Science.gov (United States)

    Alessandri, A.; Catalano, F.; De Felice, M.; Hurk, B. V. D.; Doblas-Reyes, F. J.; Boussetta, S.; Balsamo, G.; Miller, P. A.

    2017-12-01

    Here we demonstrate, for the first time, that the implementation of a realistic representation of vegetation in Earth System Models (ESMs) can significantly improve climate simulation and prediction across multiple time-scales. The effective sub-grid vegetation fractional coverage vary seasonally and at interannual time-scales in response to leaf-canopy growth, phenology and senescence. Therefore it affects biophysical parameters such as the surface resistance to evapotranspiration, albedo, roughness lenght, and soil field capacity. To adequately represent this effect in the EC-Earth ESM, we included an exponential dependence of the vegetation cover on the Leaf Area Index.By comparing two sets of simulations performed with and without the new variable fractional-coverage parameterization, spanning from centennial (20th Century) simulations and retrospective predictions to the decadal (5-years), seasonal (2-4 months) and weather (4 days) time-scales, we show for the first time a significant multi-scale enhancement of vegetation impacts in climate simulation and prediction over land. Particularly large effects at multiple time scales are shown over boreal winter middle-to-high latitudes over Canada, West US, Eastern Europe, Russia and eastern Siberia due to the implemented time-varying shadowing effect by tree-vegetation on snow surfaces. Over Northern Hemisphere boreal forest regions the improved representation of vegetation-cover consistently correct the winter warm biases, improves the climate change sensitivity, the decadal potential predictability as well as the skill of forecasts at seasonal and weather time-scales. Significant improvements of the prediction of 2m temperature and rainfall are also shown over transitional land surface hot spots. Both the potential predictability at decadal time-scale and seasonal-forecasts skill are enhanced over Sahel, North American Great Plains, Nordeste Brazil and South East Asia, mainly related to improved performance in

  8. Assessing Riparian Vegetation Condition and Function in Disturbed Sites of the Arid Northwestern Mexico

    Directory of Open Access Journals (Sweden)

    Lara Cornejo-Denman

    2018-01-01

    Full Text Available Transformation or modification of vegetation distribution and structure in arid riparian ecosystems can lead to the loss of ecological function. Mexico has 101,500,000 ha of arid lands, however there is a general lack of information regarding how arid riparian ecosystems are being modified. To assess these modifications, we use eight sites in the San Miguel River (central Sonora to analyze (1 riparian vegetation composition, structure and distribution using field sampling and remote sensing data from Unmanned Aerial Vehicles (UAV; (2 productivity (proxies, using vegetation indices derived from satellite data; and (3 variability posed by riparian vegetation and vegetation adjacent to riparian habitats. The development of a simple yet informative Anthropogenic-disturbance Index (ADI allowed us to classify and describe each study site. We found sharp differences in vegetation composition and structure between sites due to the absence/presence of obligate-riparian species. We also report significant difference between EVI (Enhanced Vegetation Index values for the dry season among vegetation types that develop near the edges of the river but differ in composition, suggesting that land cover changes form obligate-riparian to facultative-riparian species can lead to a loss in potential productivity. Finally, our tests suggest that sites with higher disturbance present lower photosynthetic activity.

  9. Synergies of carvacrol and 1,8-cineole to inhibit bacteria associated with minimally processed vegetables.

    Science.gov (United States)

    de Sousa, Jossana Pereira; de Azerêdo, Geíza Alves; de Araújo Torres, Rayanne; da Silva Vasconcelos, Margarida Angélica; da Conceição, Maria Lúcia; de Souza, Evandro Leite

    2012-03-15

    This study assessed the occurrence of an enhancing inhibitory effect of the combined application of carvacrol and 1,8-cineole against bacteria associated with minimally processed vegetables using the determination of Fractional Inhibitory Concentration (FIC) index, time-kill assay in vegetable broth and application in vegetable matrices. Their effects, individually and in combination, on the sensory characteristics of the vegetables were also determined. Carvacrol and 1,8-cineole displayed Minimum Inhibitory Concentration (MIC) in a range of 0.6-2.5 and 5-20 μL/mL, respectively, against the organisms studied. FIC indices of the combined application of the compounds were 0.25 against Listeria monocytogenes, Aeromonas hydrophila and Pseudomonas fluorescens, suggesting a synergic interaction. Application of carvacrol and 1,8-cineole alone (MIC) or in a mixture (1/8 MIC+1/8 MIC or 1/4 MIC+1/4 MIC) in vegetable broth caused a significant decrease (pvegetable broth and in experimentally inoculated fresh-cut vegetables. A similar efficacy was observed in the reduction of naturally occurring microorganisms in vegetables. Sensory evaluation revealed that the scores of the most-evaluated attributes fell between "like slightly" and "neither like nor dislike." The combination of carvacrol and 1,8-cineole at sub-inhibitory concentrations could constitute an interesting approach to sanitizing minimally processed vegetables. Copyright © 2011 Elsevier B.V. All rights reserved.

  10. Intensity of competition in the market of greenhouse vegetables

    Directory of Open Access Journals (Sweden)

    Oleg Ivanovich Botkin

    2012-03-01

    Full Text Available This paper reviews the competitive environment of the market greenhouse vegetables. Revealed specific features of the industry, determining the level of intensity of competition in the market greenhouse vegetables. Classified factors internal and external environment, identify indicators that affect the state of the market. The factors that determine the intensity of competition in the market greenhouse vegetables.The main competitors on the Russian market of greenhouse production.Identified indicators of the intensity level of competition, in particular: the level of monopolization of the market greenhouse vegetables, the level of concentration of production in the industry, the generalized index of the intensity of the competitive environment.Shows a comparative analysis of competitors’ market greenhouse vegetables in Udmurtia.Revealed competitive advantages which can help local producers to reduce the pressure of competition and intra-industry to occupy a leading position in the Russian market of greenhouse vegetable production.The dynamics of economic performance of Russian producers. Ways of improving the competitiveness of enterprises for the production of greenhouse vegetables

  11. Gauging policy-driven large-scale vegetation restoration programmes under a changing environment: Their effectiveness and socio-economic relationships.

    Science.gov (United States)

    Li, Ting; Lü, Yihe; Fu, Bojie; Comber, Alexis J; Harris, Paul; Wu, Lianhai

    2017-12-31

    Large-scale ecological restoration has been widely accepted globally as an effective strategy for combating environmental crises and to facilitate sustainability. Assessing the effectiveness of ecological restoration is vital for researchers, practitioners, and policy-makers. However, few practical tools are available to perform such tasks, particularly for large-scale restoration programmes in complex socio-ecological systems. By taking a "before and after" design, this paper formulates a composite index (E j ) based on comparing the trends of vegetation cover and vegetation productivity to assess ecological restoration effectiveness. The index reveals the dynamic and spatially heterogenic process of vegetation restoration across different time periods, which can be informative for ecological restoration management at regional scales. Effectiveness together with its relationship to socio-economic factors is explored via structural equation modeling for three time periods. The results indicate that the temporal scale is a crucial factor in representing restoration effectiveness, and that the effects of socio-economic factors can also vary with time providing insight for improving restoration effectiveness. A dual-track strategy, which promotes the development of tertiary industry in absorbing the rural labor force together with improvements in agricultural practices, is proposed as a promising strategy for enhancing restoration effectiveness. In this process, timely and long-term ecological restoration monitoring is advocated, so that the success and sustainability of such programmes is ensured, together with more informative decision making where socio-ecological interactions at differing temporal scales are key concerns. Copyright © 2017 Elsevier B.V. All rights reserved.

  12. Quantifying the Impacts of Environmental Factors on Vegetation Dynamics over Climatic and Management Gradients of Central Asia

    Directory of Open Access Journals (Sweden)

    Olena Dubovyk

    2016-07-01

    Full Text Available Currently there is a lack of quantitative information regarding the driving factors of vegetation dynamics in post-Soviet Central Asia. Insufficient knowledge also exists concerning vegetation variability across sub-humid to arid climatic gradients as well as vegetation response to different land uses, from natural rangelands to intensively irrigated croplands. In this study, we analyzed the environmental drivers of vegetation dynamics in five Central Asian countries by coupling key vegetation parameter “overall greenness” derived from Moderate Resolution Imaging Spectroradiometer (MODIS Normalized Difference Vegetation Index (NDVI time series data, with its possible factors across various management and climatic gradients. We developed nine generalized least-squares random effect (GLS-RE models to analyze the relative impact of environmental factors on vegetation dynamics. The obtained results quantitatively indicated the extensive control of climatic factors on managed and unmanaged vegetation cover across Central Asia. The most diverse vegetation dynamics response to climatic variables was observed for “intensively managed irrigated croplands”. Almost no differences in response to these variables were detected for managed non-irrigated vegetation and unmanaged (natural vegetation across all countries. Natural vegetation and rainfed non-irrigated crop dynamics were principally associated with temperature and precipitation parameters. Variables related to temperature had the greatest relative effect on irrigated croplands and on vegetation cover within the mountainous zone. Further research should focus on incorporating the socio-economic factors discussed here in a similar analysis.

  13. Preservation of Postharvest Quality of Leafy Amaranth (Amaranthus spp. Vegetables Using Evaporative Cooling

    Directory of Open Access Journals (Sweden)

    Jane Ambuko

    2017-01-01

    Full Text Available Leafy vegetables are very highly perishable and must be utilized immediately after harvest. Their fast deterioration is attributed to various biological and environmental factors with temperature playing a central role. Evaporative cooling is a low-cost temporary storage technology that offers smallholder vegetable farmers an alternative to expensive cold rooms. The present study sought to determine the effectiveness of evaporative cooling using zero energy brick cooler (ZEBC and evaporative charcoal cooler (ECC, to preserve the postharvest quality of leafy amaranth vegetables. Freshly harvested vegetables were separated into bundles weighing 300 grams and stored under ZEBC, ECC, and ambient room conditions (control. Real time changes in temperature and relative humidity (RH as well as changes in quality attributes (physiological weight loss (PWL, wilting index, hue angle, and vitamin C were determined during the storage period. The temperature difference between the ZEBC and ECC versus the ambient air ranged between 4 and 10°C. Significantly higher RH (80–100% was recorded in both evaporative cooling chambers. At the end of storage, higher PWL (47.6% was recorded at ambient room conditions compared to 10.5 and 6.7% under ZEBC and ECC, respectively. A rapid decline in vitamin C (51% was reported in vegetables stored at ambient room conditions. Overall, there was better vegetable quality preservation under ECC and ZEBC.

  14. A FRAMEWORK OF CHANGE DETECTION BASED ON COMBINED MORPHOLOGICA FEATURES AND MULTI-INDEX CLASSIFICATION

    Directory of Open Access Journals (Sweden)

    S. Li

    2017-09-01

    Full Text Available Remote sensing images are particularly well suited for analysis of land cover change. In this paper, we present a new framework for detection of changing land cover using satellite imagery. Morphological features and a multi-index are used to extract typical objects from the imagery, including vegetation, water, bare land, buildings, and roads. Our method, based on connected domains, is different from traditional methods; it uses image segmentation to extract morphological features, while the enhanced vegetation index (EVI, the differential water index (NDWI are used to extract vegetation and water, and a fragmentation index is used to the correct extraction results of water. HSV transformation and threshold segmentation extract and remove the effects of shadows on extraction results. Change detection is performed on these results. One of the advantages of the proposed framework is that semantic information is extracted automatically using low-level morphological features and indexes. Another advantage is that the proposed method detects specific types of change without any training samples. A test on ZY-3 images demonstrates that our framework has a promising capability to detect change.

  15. a Framework of Change Detection Based on Combined Morphologica Features and Multi-Index Classification

    Science.gov (United States)

    Li, S.; Zhang, S.; Yang, D.

    2017-09-01

    Remote sensing images are particularly well suited for analysis of land cover change. In this paper, we present a new framework for detection of changing land cover using satellite imagery. Morphological features and a multi-index are used to extract typical objects from the imagery, including vegetation, water, bare land, buildings, and roads. Our method, based on connected domains, is different from traditional methods; it uses image segmentation to extract morphological features, while the enhanced vegetation index (EVI), the differential water index (NDWI) are used to extract vegetation and water, and a fragmentation index is used to the correct extraction results of water. HSV transformation and threshold segmentation extract and remove the effects of shadows on extraction results. Change detection is performed on these results. One of the advantages of the proposed framework is that semantic information is extracted automatically using low-level morphological features and indexes. Another advantage is that the proposed method detects specific types of change without any training samples. A test on ZY-3 images demonstrates that our framework has a promising capability to detect change.

  16. Vegetation Changes in the Permafrost Regions of the Qinghai-Tibetan Plateau from 1982-2012: Different Responses Related to Geographical Locations and Vegetation Types in High-Altitude Areas.

    Directory of Open Access Journals (Sweden)

    Zhiwei Wang

    Full Text Available The Qinghai-Tibetan Plateau (QTP contains the largest permafrost area in a high-altitude region in the world, and the unique hydrothermal environments of the active layers in this region have an important impact on vegetation growth. Geographical locations present different climatic conditions, and in combination with the permafrost environments, these conditions comprehensively affect the local vegetation activity. Therefore, the responses of vegetation to climate change in the permafrost region of the QTP may be varied differently by geographical location and vegetation condition. In this study, using the latest Global Inventory Modeling and Mapping Studies (GIMMS Normalized Difference Vegetation Index (NDVI product based on turning points (TPs, which were calculated using a piecewise linear model, 9 areas within the permafrost region of the QTP were selected to investigate the effect of geographical location and vegetation type on vegetation growth from 1982 to 2012. The following 4 vegetation types were observed in the 9 selected study areas: alpine swamp meadow, alpine meadow, alpine steppe and alpine desert. The research results show that, in these study areas, TPs mainly appeared in 2000 and 2001, and almost 55.1% and 35.0% of the TPs were located in 2000 and 2001. The global standardized precipitation evapotranspiration index (SPEI and 7 meteorological variables were selected to analyze their correlations with NDVI. We found that the main correlative variables to vegetation productivity in study areas from 1982 to 2012 were precipitation, surface downward long-wave radiation and temperature. Furthermore, NDVI changes exhibited by different vegetation types within the same study area followed similar trends. The results show that regional effects rather than vegetation type had a larger impact on changes in vegetation growth in the permafrost regions of the QTP, indicating that climatic factors had a larger impact in the permafrost

  17. Advances in Remote Sensing for Vegetation Dynamics and Agricultural Management

    Science.gov (United States)

    Tucker, Compton; Puma, Michael

    2015-01-01

    Spaceborne remote sensing has led to great advances in the global monitoring of vegetation. For example, the NASA Global Inventory Modeling and Mapping Studies (GIMMS) group has developed widely used datasets from the Advanced Very High Resolution Radiometer (AVHRR) sensors as well as the Moderate Resolution Imaging Spectroradiometer (MODIS) map imagery and normalized difference vegetation index datasets. These data are valuable for analyzing vegetation trends and variability at the regional and global levels. Numerous studies have investigated such trends and variability for both natural vegetation (e.g., re-greening of the Sahel, shifts in the Eurasian boreal forest, Amazonian drought sensitivity) and crops (e.g., impacts of extremes on agricultural production). Here, a critical overview is presented on recent developments and opportunities in the use of remote sensing for monitoring vegetation and crop dynamics.

  18. Global Food Security Index Studies and Satellite Information

    Science.gov (United States)

    Medina, T. A.; Ganti-Agrawal, S.; Joshi, D.; Lakhankar, T.

    2017-12-01

    Food yield is equal to the total crop harvest per unit cultivated area. During the elapsed time of germination and frequent harvesting, both human and climate related effects determine a country's' contribution towards global food security. Each country across the globe's annual income per capita was collected to then determine nine countries for further studies. For a location to be chosen, its income per capita needed to be considered poor, uprising or wealthy. Both physical land cover and regional climate helped categorize potential parameters thought to be studied. Once selected, Normalized Difference Vegetation Index (NDVI) data was collected for Ethiopia, Liberia, Indonesia, United States, Norway, Russia, Kuwait and Saudi Arabia over the recent 16 years for approximately every 16 days starting from early in the year 2000. Software languages such as Geographic Information System (GIS), MatLab and Excel were used to determine how population size, income and deforestation directly determines agricultural yields. Because of high maintenance requirements for large harvests when forest areas are cleared, they often have a reduction in soil quality, requiring fertilizer use to produce sufficient crop yields. Total area and vegetation index of each country is to be studied, to determine crop and deforestation percentages. To determine how deforestation impacts future income and crop yield predictions of each country studied. By using NDVI results a parameter is to be potentially found that will help define an index, to create an equation that will determine a country's annual income and ability to provide for their families and themselves.

  19. The greening of the McGill Paleoclimate Model. Part I: Improved land surface scheme with vegetation dynamics

    Energy Technology Data Exchange (ETDEWEB)

    Wang, Yi; Mysak, Lawrence A.; Wang, Zhaomin [McGill University, Department of Atmospheric and Oceanic Sciences, Global Environmental and Climate Change Centre (GEC3), Montreal, QC (Canada); Brovkin, Victor [Potsdam Institute for Climate Impact Research (PIK), Potsdam (Germany)

    2005-04-01

    The formulation of a new land surface scheme (LSS) with vegetation dynamics for coupling to the McGill Paleoclimate Model (MPM) is presented. This LSS has the following notable improvements over the old version: (1) parameterization of deciduous and evergreen trees by using the model's climatology and the output of the dynamic global vegetation model, VECODE (Brovkin et al. in Ecological Modelling 101:251-261 (1997), Global Biogeochemical Cycles 16(4):1139, (2002)); (2) parameterization of tree leaf budburst and leaf drop by using the model's climatology; (3) parameterization of the seasonal cycle of the grass leaf area index; (4) parameterization of the seasonal cycle of tree leaf area index by using the time-dependent growth of the leaves; (5) calculation of land surface albedo by using vegetation-related parameters, snow depth and the model's climatology. The results show considerable improvement of the model's simulation of the present-day climate as compared with that simulated in the original physically-based MPM. In particular, the strong seasonality of terrestrial vegetation and the associated land surface albedo variations are in good agreement with several satellite observations of these quantities. The application of this new version of the MPM (the ''green'' MPM) to Holocene millennial-scale climate changes is described in a companion paper, Part II. (orig.)

  20. Consistency of Vegetation Index Seasonality Across the Amazon Rainforest

    Science.gov (United States)

    Maeda, Eduardo Eiji; Moura, Yhasmin Mendes; Wagner, Fabien; Hilker, Thomas; Lyapustin, Alexei I.; Wang, Yujie; Chave, Jerome; Mottus, Matti; Aragao, Luiz E.O.C.; Shimabukuro, Yosio

    2016-01-01

    Vegetation indices (VIs) calculated from remotely sensed reflectance are widely used tools for characterizing the extent and status of vegetated areas. Recently, however, their capability to monitor the Amazon forest phenology has been intensely scrutinized. In this study, we analyze the consistency of VIs seasonal patterns obtained from two MODIS products: the Collection 5 BRDF product (MCD43) and the Multi-Angle Implementation of Atmospheric Correction algorithm (MAIAC). The spatio-temporal patterns of the VIs were also compared with field measured leaf litterfall, gross ecosystem productivity and active microwave data. Our results show that significant seasonal patterns are observed in all VIs after the removal of view-illumination effects and cloud contamination. However, we demonstrate inconsistencies in the characteristics of seasonal patterns between different VIs and MODIS products. We demonstrate that differences in the original reflectance band values form a major source of discrepancy between MODIS VI products. The MAIAC atmospheric correction algorithm significantly reduces noise signals in the red and blue bands. Another important source of discrepancy is caused by differences in the availability of clear-sky data, as the MAIAC product allows increased availability of valid pixels in the equatorial Amazon. Finally, differences in VIs seasonal patterns were also caused by MODIS collection 5 calibration degradation. The correlation of remote sensing and field data also varied spatially, leading to different temporal offsets between VIs, active microwave and field measured data. We conclude that recent improvements in the MAIAC product have led to changes in the characteristics of spatio-temporal patterns of VIs seasonality across the Amazon forest, when compared to the MCD43 product. Nevertheless, despite improved quality and reduced uncertainties in the MAIAC product, a robust biophysical interpretation of VIs seasonality is still missing.

  1. Consistency of vegetation index seasonality across the Amazon rainforest

    Science.gov (United States)

    Maeda, Eduardo Eiji; Moura, Yhasmin Mendes; Wagner, Fabien; Hilker, Thomas; Lyapustin, Alexei I.; Wang, Yujie; Chave, Jérôme; Mõttus, Matti; Aragão, Luiz E. O. C.; Shimabukuro, Yosio

    2016-10-01

    Vegetation indices (VIs) calculated from remotely sensed reflectance are widely used tools for characterizing the extent and status of vegetated areas. Recently, however, their capability to monitor the Amazon forest phenology has been intensely scrutinized. In this study, we analyze the consistency of VIs seasonal patterns obtained from two MODIS products: the Collection 5 BRDF product (MCD43) and the Multi-Angle Implementation of Atmospheric Correction algorithm (MAIAC). The spatio-temporal patterns of the VIs were also compared with field measured leaf litterfall, gross ecosystem productivity and active microwave data. Our results show that significant seasonal patterns are observed in all VIs after the removal of view-illumination effects and cloud contamination. However, we demonstrate inconsistencies in the characteristics of seasonal patterns between different VIs and MODIS products. We demonstrate that differences in the original reflectance band values form a major source of discrepancy between MODIS VI products. The MAIAC atmospheric correction algorithm significantly reduces noise signals in the red and blue bands. Another important source of discrepancy is caused by differences in the availability of clear-sky data, as the MAIAC product allows increased availability of valid pixels in the equatorial Amazon. Finally, differences in VIs seasonal patterns were also caused by MODIS collection 5 calibration degradation. The correlation of remote sensing and field data also varied spatially, leading to different temporal offsets between VIs, active microwave and field measured data. We conclude that recent improvements in the MAIAC product have led to changes in the characteristics of spatio-temporal patterns of VIs seasonality across the Amazon forest, when compared to the MCD43 product. Nevertheless, despite improved quality and reduced uncertainties in the MAIAC product, a robust biophysical interpretation of VIs seasonality is still missing.

  2. Effects of Cereal, Fruit and Vegetable Fibers on Human Fecal Weight and Transit Time: A Comprehensive Review of Intervention Trials

    Directory of Open Access Journals (Sweden)

    Jan de Vries

    2016-03-01

    Full Text Available Cereal fibers are known to increase fecal weight and speed transit time, but far less data are available on the effects of fruits and vegetable fibers on regularity. This study provides a comprehensive review of the impact of these three fiber sources on regularity in healthy humans. We identified English-language intervention studies on dietary fibers and regularity and performed weighted linear regression analyses for fecal weight and transit time. Cereal and vegetable fiber groups had comparable effects on fecal weight; both contributed to it more than fruit fibers. Less fermentable fibers increased fecal weight to a greater degree than more fermentable fibers. Dietary fiber did not change transit time in those with an initial time of <48 h. In those with an initial transit time ≥48 h, transit time was reduced by approximately 30 min per gram of cereal, fruit or vegetable fibers, regardless of fermentability. Cereal fibers have been studied more than any other kind in relation to regularity. This is the first comprehensive review comparing the effects of the three major food sources of fiber on bowel function and regularity since 1993.

  3. Effects of Cereal, Fruit and Vegetable Fibers on Human Fecal Weight and Transit Time: A Comprehensive Review of Intervention Trials.

    Science.gov (United States)

    de Vries, Jan; Birkett, Anne; Hulshof, Toine; Verbeke, Kristin; Gibes, Kernon

    2016-03-02

    Cereal fibers are known to increase fecal weight and speed transit time, but far less data are available on the effects of fruits and vegetable fibers on regularity. This study provides a comprehensive review of the impact of these three fiber sources on regularity in healthy humans. We identified English-language intervention studies on dietary fibers and regularity and performed weighted linear regression analyses for fecal weight and transit time. Cereal and vegetable fiber groups had comparable effects on fecal weight; both contributed to it more than fruit fibers. Less fermentable fibers increased fecal weight to a greater degree than more fermentable fibers. Dietary fiber did not change transit time in those with an initial time of <48 h. In those with an initial transit time ≥48 h, transit time was reduced by approximately 30 min per gram of cereal, fruit or vegetable fibers, regardless of fermentability. Cereal fibers have been studied more than any other kind in relation to regularity. This is the first comprehensive review comparing the effects of the three major food sources of fiber on bowel function and regularity since 1993.

  4. Multi-scale enhancement of climate prediction over land by increasing the model sensitivity to vegetation variability in EC-Earth

    Science.gov (United States)

    Alessandri, Andrea; Catalano, Franco; De Felice, Matteo; Van Den Hurk, Bart; Doblas Reyes, Francisco; Boussetta, Souhail; Balsamo, Gianpaolo; Miller, Paul A.

    2017-08-01

    The EC-Earth earth system model has been recently developed to include the dynamics of vegetation. In its original formulation, vegetation variability is simply operated by the Leaf Area Index (LAI), which affects climate basically by changing the vegetation physiological resistance to evapotranspiration. This coupling has been found to have only a weak effect on the surface climate modeled by EC-Earth. In reality, the effective sub-grid vegetation fractional coverage will vary seasonally and at interannual time-scales in response to leaf-canopy growth, phenology and senescence. Therefore it affects biophysical parameters such as the albedo, surface roughness and soil field capacity. To adequately represent this effect in EC-Earth, we included an exponential dependence of the vegetation cover on the LAI. By comparing two sets of simulations performed with and without the new variable fractional-coverage parameterization, spanning from centennial (twentieth century) simulations and retrospective predictions to the decadal (5-years), seasonal and weather time-scales, we show for the first time a significant multi-scale enhancement of vegetation impacts in climate simulation and prediction over land. Particularly large effects at multiple time scales are shown over boreal winter middle-to-high latitudes over Canada, West US, Eastern Europe, Russia and eastern Siberia due to the implemented time-varying shadowing effect by tree-vegetation on snow surfaces. Over Northern Hemisphere boreal forest regions the improved representation of vegetation cover tends to correct the winter warm biases, improves the climate change sensitivity, the decadal potential predictability as well as the skill of forecasts at seasonal and weather time-scales. Significant improvements of the prediction of 2 m temperature and rainfall are also shown over transitional land surface hot spots. Both the potential predictability at decadal time-scale and seasonal-forecasts skill are enhanced over

  5. ANALYSIS ON TEMPORAL-SPATIAL CHANGES OF VEGETATION CVERRGE IN FARMING-PASTORAL ECOTONE OF INNER MONGOLIA

    Directory of Open Access Journals (Sweden)

    X. Yan

    2018-04-01

    Full Text Available Chen Barag Banner is located in the typical farming-pastoral ecotone of Inner Mongolia, and it is also the core area of Hulunbuir steppe. Typical agricultural and pastoral staggered production mode so that the vegetation growth of the region not only determines the local ecological environment, and animal husbandry production, but also have a significant impact on the whole Hulunbuir ecological security and economic development. Therefore, it is necessary to monitor the change of vegetation in this area. Based on 17 MODIS Normalized Difference Vegetation Index (NDVI images, the authors reconstructed the dynamic change characteristics of Fraction vegetation coverage(FVC)in Chen Barag Banner from 2000 to 2016. In this paper, first at all, Pixel Decomposition Models was introduced to inversion FVC, and the time series of vegetation coverage was reconstructed. Then we analyzed the temporal-spatial changes of FVC by employing transition matrix. Finally, through image analyzing and processing, the results showed that the vegetation coverage in the study area was influenced by effectors including climate, topography and human actives. In the past 17 years, the overall effect of vegetation coverage showed a downward trend of fluctuation. The average vegetation coverage decreased from 58.81 % in 2000 to 48.14 % in 2016, and the area of vegetation cover degradation accounts for 40.09 % of the total change area. Therefore, the overall degradation trend was obvious.

  6. Modeling Travel Time Reliability of Road Network Considering Connected Vehicle Guidance Characteristics Indexes

    Directory of Open Access Journals (Sweden)

    Jiangfeng Wang

    2017-01-01

    Full Text Available Travel time reliability (TTR is one of the important indexes for effectively evaluating the performance of road network, and TTR can effectively be improved using the real-time traffic guidance information. Compared with traditional traffic guidance, connected vehicle (CV guidance can provide travelers with more timely and accurate travel information, which can further improve the travel efficiency of road network. Five CV characteristics indexes are selected as explanatory variables including the Congestion Level (CL, Penetration Rate (PR, Compliance Rate (CR, release Delay Time (DT, and Following Rate (FR. Based on the five explanatory variables, a TTR model is proposed using the multilogistic regression method, and the prediction accuracy and the impact of characteristics indexes on TTR are analyzed using a CV guidance scenario. The simulation results indicate that 80% of the RMSE is concentrated within the interval of 0 to 0.0412. The correlation analysis of characteristics indexes shows that the influence of CL, PR, CR, and DT on the TTR is significant. PR and CR have a positive effect on TTR, and the average improvement rate is about 77.03% and 73.20% with the increase of PR and CR, respectively, while CL and DT have a negative effect on TTR, and TTR decreases by 31.21% with the increase of DT from 0 to 180 s.

  7. NOAA JPSS Visible Infrared Imaging Radiometer Suite (VIIRS) Vegetation Health and Drought Products (VHDP) from NDE

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The VIIRS Vegetation Health and Drought Products (VHDP) from NDE algorithm provides weekly estimates of the Vegetation Condition Index (VCI), Temperature Condition...

  8. Evaluation and attribution of vegetation contribution to seasonal climate predictability

    Science.gov (United States)

    Catalano, Franco; Alessandri, Andrea; De Felice, Matteo

    2015-04-01

    The land surface model of EC-Earth has been modified to include dependence of vegetation densities on the Leaf Area Index (LAI), based on the Lambert-Beer formulation. Effective vegetation fractional coverage can now vary at seasonal and interannual time-scales and therefore affect biophysical parameters such as the surface roughness, albedo and soil field capacity. The modified model is used to perform a real predictability seasonal hindcast experiment. LAI is prescribed using a recent observational dataset based on the third generation GIMMS and MODIS satellite data. Hindcast setup is: 7 months forecast length, 2 start dates (1st May and 1st November), 10 members, 28 years (1982-2009). The effect of the realistic LAI prescribed from observation is evaluated with respect to a control experiment where LAI does not vary. Hindcast results demonstrate that a realistic representation of vegetation significantly improves the forecasts of temperature and precipitation. The sensitivity is particularly large for temperature during boreal winter over central North America and Central Asia. This may be attributed in particular to the effect of the high vegetation component on the snow cover. Summer forecasts are improved in particular for precipitation over Europe, Sahel, North America, West Russia and Nordeste. Correlation improvements depends on the links between targets (temperature and precipitation) and drivers (surface heat fluxes, albedo, soil moisture, evapotranspiration, moisture divergence) which varies from region to region.

  9. ESTRUTUTURA DA COMUNIDADE VEGETAL ARBÓREO-ARBUSTIVA DE UM SISTEMA AGROSSILVIPASTORIL, EM SOBRAL - CE

    Directory of Open Access Journals (Sweden)

    MÔNICA MATOSO CAMPANHA

    2011-01-01

    Full Text Available "Caatinga", dominant vegetation in Brazilian semiarid, has suffered severe degradation process, triggered, among other reasons, by the traditional agricultural and extractive activities. The need to conserve the environment and natural resources in agricultural and forestry activities, led to search for alternatives to conventional production. In this context, agroforestry systems, that integrate trees with crops and livestock, are an alternative operating sustainably. With the aim of studying the potential for preservation tree species of the "Caatinga" in an agrosilvopasture system in semiarid, in Sobral-CE, was evaluated the relatives density, frequency and dominance, the importance value index and the Shannon e Wiener index, of the woody component of this system. It was found that the vegetation management practices of trees and shrubs used in the system decrease density, and interfered in height and diameter distribution of individuals in relation to the original vegetation of the Caatinga. However, these practices were effective in preserving the wealth of flora species of trees and shrubs, similar to the area of native vegetation reserve. Cordia oncocalyx was the species with the highest number of individuals in the system, also showing highest importance value, followed by Mimosa caesalpiniifolia. The family Leguminosae was the most representative. The Shannon index shows that this agrosilvopasture system has the potential to promote an intermediate level of conservation among the "Caatinga" vegetation remnants and disturbed areas in this biome.

  10. An Enhanced TIMESAT Algorithm for Estimating Vegetation Phenology Metrics from MODIS Data

    Science.gov (United States)

    Tan, Bin; Morisette, Jeffrey T.; Wolfe, Robert E.; Gao, Feng; Ederer, Gregory A.; Nightingale, Joanne; Pedelty, Jeffrey A.

    2012-01-01

    An enhanced TIMESAT algorithm was developed for retrieving vegetation phenology metrics from 250 m and 500 m spatial resolution Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation indexes (VI) over North America. MODIS VI data were pre-processed using snow-cover and land surface temperature data, and temporally smoothed with the enhanced TIMESAT algorithm. An objective third derivative test was applied to define key phenology dates and retrieve a set of phenology metrics. This algorithm has been applied to two MODIS VIs: Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI). In this paper, we describe the algorithm and use EVI as an example to compare three sets of TIMESAT algorithm/MODIS VI combinations: a) original TIMESAT algorithm with original MODIS VI, b) original TIMESAT algorithm with pre-processed MODIS VI, and c) enhanced TIMESAT and pre-processed MODIS VI. All retrievals were compared with ground phenology observations, some made available through the National Phenology Network. Our results show that for MODIS data in middle to high latitude regions, snow and land surface temperature information is critical in retrieving phenology metrics from satellite observations. The results also show that the enhanced TIMESAT algorithm can better accommodate growing season start and end dates that vary significantly from year to year. The TIMESAT algorithm improvements contribute to more spatial coverage and more accurate retrievals of the phenology metrics. Among three sets of TIMESAT/MODIS VI combinations, the start of the growing season metric predicted by the enhanced TIMESAT algorithm using pre-processed MODIS VIs has the best associations with ground observed vegetation greenup dates.

  11. Testing the Potential of Vegetation Indices for Land Use/cover Classification Using High Resolution Data

    Science.gov (United States)

    Karakacan Kuzucu, A.; Bektas Balcik, F.

    2017-11-01

    Accurate and reliable land use/land cover (LULC) information obtained by remote sensing technology is necessary in many applications such as environmental monitoring, agricultural management, urban planning, hydrological applications, soil management, vegetation condition study and suitability analysis. But this information still remains a challenge especially in heterogeneous landscapes covering urban and rural areas due to spectrally similar LULC features. In parallel with technological developments, supplementary data such as satellite-derived spectral indices have begun to be used as additional bands in classification to produce data with high accuracy. The aim of this research is to test the potential of spectral vegetation indices combination with supervised classification methods and to extract reliable LULC information from SPOT 7 multispectral imagery. The Normalized Difference Vegetation Index (NDVI), the Ratio Vegetation Index (RATIO), the Soil Adjusted Vegetation Index (SAVI) were the three vegetation indices used in this study. The classical maximum likelihood classifier (MLC) and support vector machine (SVM) algorithm were applied to classify SPOT 7 image. Catalca is selected region located in the north west of the Istanbul in Turkey, which has complex landscape covering artificial surface, forest and natural area, agricultural field, quarry/mining area, pasture/scrubland and water body. Accuracy assessment of all classified images was performed through overall accuracy and kappa coefficient. The results indicated that the incorporation of these three different vegetation indices decrease the classification accuracy for the MLC and SVM classification. In addition, the maximum likelihood classification slightly outperformed the support vector machine classification approach in both overall accuracy and kappa statistics.

  12. Assessment of Real-Time Compaction Quality Test Indexes for Rockfill Material Based on Roller Vibratory Acceleration Analysis

    Directory of Open Access Journals (Sweden)

    Tianbo Hua

    2018-01-01

    Full Text Available Compaction quality is directly related to the structure and seepage stability of a rockfill dam. To timely and accurately test the compaction quality of the rockfill material, four real-time test indexes were chosen to characterize the soil compaction degree based on the analysis of roller vibratory acceleration, including acceleration peak value (ap, acceleration root mean square value (arms, crest factor value (CF, and compaction meter value (CMV. To determine which of these indexes is the most appropriate, a two-part field compaction experiment was conducted using a vibratory roller in different filling zones of the dam body. Data on rolling parameters, real-time test indexes, and compaction quality indexes were collected to perform statistical regression analyses. Combined with the spectrum analysis of the acceleration signal, it was found that the CF index best characterizes the compaction degree of the rockfill material among the four indexes. Furthermore, the quantitative relations between the real-time index and compaction quality index were established to determine the control criterion of CF, which can instruct the site work of compaction quality control in the rockfill rolling process.

  13. [Simulation of vegetation indices optimizing under retrieval of vegetation biochemical parameters based on PROSPECT + SAIL model].

    Science.gov (United States)

    Wu, Ling; Liu, Xiang-Nan; Zhou, Bo-Tian; Liu, Chuan-Hao; Li, Lu-Feng

    2012-12-01

    This study analyzed the sensitivities of three vegetation biochemical parameters [chlorophyll content (Cab), leaf water content (Cw), and leaf area index (LAI)] to the changes of canopy reflectance, with the effects of each parameter on the wavelength regions of canopy reflectance considered, and selected three vegetation indices as the optimization comparison targets of cost function. Then, the Cab, Cw, and LAI were estimated, based on the particle swarm optimization algorithm and PROSPECT + SAIL model. The results showed that retrieval efficiency with vegetation indices as the optimization comparison targets of cost function was better than that with all spectral reflectance. The correlation coefficients (R2) between the measured and estimated values of Cab, Cw, and LAI were 90.8%, 95.7%, and 99.7%, and the root mean square errors of Cab, Cw, and LAI were 4.73 microg x cm(-2), 0.001 g x cm(-2), and 0.08, respectively. It was suggested that to adopt vegetation indices as the optimization comparison targets of cost function could effectively improve the efficiency and precision of the retrieval of biochemical parameters based on PROSPECT + SAIL model.

  14. Use of vegetation health data for estimation of aus rice yield in bangladesh.

    Science.gov (United States)

    Rahman, Atiqur; Roytman, Leonid; Krakauer, Nir Y; Nizamuddin, Mohammad; Goldberg, Mitch

    2009-01-01

    Rice is a vital staple crop for Bangladesh and surrounding countries, with interannual variation in yields depending on climatic conditions. We compared Bangladesh yield of aus rice, one of the main varieties grown, from official agricultural statistics with Vegetation Health (VH) Indices [Vegetation Condition Index (VCI), Temperature Condition Index (TCI) and Vegetation Health Index (VHI)] computed from Advanced Very High Resolution Radiometer (AVHRR) data covering a period of 15 years (1991-2005). A strong correlation was found between aus rice yield and VCI and VHI during the critical period of aus rice development that occurs during March-April (weeks 8-13 of the year), several months in advance of the rice harvest. Stepwise principal component regression (PCR) was used to construct a model to predict yield as a function of critical-period VHI. The model reduced the yield prediction error variance by 62% compared with a prediction of average yield for each year. Remote sensing is a valuable tool for estimating rice yields well in advance of harvest and at a low cost.

  15. Use of Vegetation Health Data for Estimation of Aus Rice Yield in Bangladesh

    Directory of Open Access Journals (Sweden)

    Mohammad Nizamuddin

    2009-04-01

    Full Text Available Rice is a vital staple crop for Bangladesh and surrounding countries, with interannual variation in yields depending on climatic conditions. We compared Bangladesh yield of aus rice, one of the main varieties grown, from official agricultural statistics with Vegetation Health (VH Indices [Vegetation Condition Index (VCI, Temperature Condition Index (TCI and Vegetation Health Index (VHI] computed from Advanced Very High Resolution Radiometer (AVHRR data covering a period of 15 years (1991–2005. A strong correlation was found between aus rice yield and VCI and VHI during the critical period of aus rice development that occurs during March-April (weeks 8–13 of the year, several months in advance of the rice harvest. Stepwise principal component regression (PCR was used to construct a model to predict yield as a function of critical-period VHI. The model reduced the yield prediction error variance by 62% compared with a prediction of average yield for each year. Remote sensing is a valuable tool for estimating rice yields well in advance of harvest and at a low cost.

  16. Body Mass Index: Accounting for Full Time Sedentary Occupation and 24-Hr Self-Reported Time Use

    OpenAIRE

    Tudor-Locke, Catrine; Schuna, John M.; Katzmarzyk, Peter T.; Liu, Wei; Hamrick, Karen S.; Johnson, William D.

    2014-01-01

    Objectives We used linked existing data from the 2006–2008 American Time Use Survey (ATUS), the Current Population Survey (CPS, a federal survey that provides on-going U.S. vital statistics, including employment rates) and self-reported body mass index (BMI) to answer: How does BMI vary across full time occupations dichotomized as sedentary/non-sedentary, accounting for time spent in sleep, other sedentary behaviors, and light, moderate, and vigorous intensity activities? Methods We classifie...

  17. [Correlationships between the coverage of vegetation and the quality of groundwater in the lower reaches of the Tarim River].

    Science.gov (United States)

    Chen, Yong-jin; Chen, Ya-ning; Liu, Jia-zhen

    2010-03-01

    The variations vegetation coverage is the result of conjunct effects of inner and outer energy of the earth, however, the human activity always makes the coverage of vegetation change a lot. Based on the monitoring data of chemistry of groundwater and the coverage of vegetation from 2002 to 2007 in the lower reaches of Tarim River, relations between vegetation coverage and groundwater chemistry were studied. It is found that vegetation coverage at Sector A was more than 80%, and decreased from sector to sector, the coverage of Sector I was less than 10%. At the same sector, samples near to water source owned high coverage index, and samples far away from the river had low coverage index. The variations of pH in groundwater expressed similar regulation to vegetation coverage, that is, Sectors near the water source had higher pH index comparing than those far away. Regression between groundwater quality and vegetation coverage disclosed that the coverage of Populus euphratica climbed up along with increase of pH in groundwater, change of Tamarix ramosissima coverage expressed an opposite trend to the Populus euphratica with the same environmental factors. This phenomenon can interpret spatial distribution of Populus euphratica and Tamarix ramosissima in lower reaches of the Tarim River.

  18. Impacts of the seasonal distribution of rainfall on vegetation productivity across the Sahel

    Science.gov (United States)

    Zhang, Wenmin; Brandt, Martin; Tong, Xiaoye; Tian, Qingjiu; Fensholt, Rasmus

    2018-01-01

    Climate change in drylands has caused alterations in the seasonal distribution of rainfall including increased heavy-rainfall events, longer dry spells, and a shifted timing of the wet season. Yet the aboveground net primary productivity (ANPP) in drylands is usually explained by annual-rainfall sums, disregarding the influence of the seasonal distribution of rainfall. This study tested the importance of rainfall metrics in the wet season (onset and cessation of the wet season, number of rainy days, rainfall intensity, number of consecutive dry days, and heavy-rainfall events) for growing season ANPP. We focused on the Sahel and northern Sudanian region (100-800 mm yr-1) and applied daily satellite-based rainfall estimates (CHIRPS v2.0) and growing-season-integrated normalized difference vegetation index (NDVI; MODIS) as a proxy for ANPP over the study period: 2001-2015. Growing season ANPP in the arid zone (100-300 mm yr-1) was found to be rather insensitive to variations in the seasonal-rainfall metrics, whereas vegetation in the semi-arid zone (300-700 mm yr-1) was significantly impacted by most metrics, especially by the number of rainy days and timing (onset and cessation) of the wet season. We analysed critical breakpoints for all metrics to test if vegetation response to changes in a given rainfall metric surpasses a threshold beyond which vegetation functioning is significantly altered. It was shown that growing season ANPP was particularly negatively impacted after > 14 consecutive dry days and that a rainfall intensity of ˜ 13 mm day-1 was detected for optimum growing season ANPP. We conclude that the number of rainy days and the timing of the wet season are seasonal-rainfall metrics that are decisive for favourable vegetation growth in the semi-arid Sahel and need to be considered when modelling primary productivity from rainfall in the drylands of the Sahel and elsewhere.

  19. Acculturation, Income and Vegetable Consumption Behaviors Among Latino Adults in the U.S.: A Mediation Analysis with the Bootstrapping Technique.

    Science.gov (United States)

    López, Erick B; Yamashita, Takashi

    2017-02-01

    This study examined whether household income mediates the relationship between acculturation and vegetable consumption among Latino adults in the U.S. Data from the 2009 to 2010 National Health and Nutrition Examination Survey were analyzed. Vegetable consumption index was created based on the frequencies of five kinds of vegetables intake. Acculturation was measured with the degree of English language use at home. Path model with bootstrapping technique was employed for mediation analysis. A significant partial mediation relationship was identified. Greater acculturation [95 % bias corrected bootstrap confident interval (BCBCI) = (0.02, 0.33)] was associated with the higher income and in turn, greater vegetable consumption. At the same time, greater acculturation was associated with lower vegetable consumption [95 % BCBCI = (-0.88, -0.07)]. Findings regarding the income as a mediator of the acculturation-dietary behavior relationship inform unique intervention programs and policy changes to address health disparities by race/ethnicity.

  20. CROP SPECIES RECOGNITION AND DISCRIMINATION PADDY-RICE-GROWINGFIELDS FROM REAPED-FIELDS BY THE RADAR VEGETATION INDEX (RVI OF ALOS-2/PALSAR2

    Directory of Open Access Journals (Sweden)

    Y. Yamada

    2016-06-01

    Full Text Available The Japanese ALOS-2 satellite was launched on May 24th, 2014. It has the L-band SAR, PALSAR-2. Kim,Y. and van Zyl, J.J. proposed a kind of Radar Vegetation Index (RVI as RVI = 8 * σ0hv / (σ0hh + σ0vv + 2* σ0hv by L-band full-polarimetric radar data. Kim, Y. and Jackson, T.J., et al. applied the equation into rice and soybean by multi-frequency polarimetric scatterometer above 4.16 meters from the ground. Their report showed the L-band was the most promising wave length for estimating LAI and NDVI from RVI. The author tried to apply the analysis to the actual paddy field areas, both Inashiki region and Miyagi region in the eastern main island, “Honshu”, areas of Japan by ALOS-2/PALSAR-2 full-polarimetry data in the summer season, the main crop growing time, of 2015. Judging from conventional methods, it will be possible to discriminate paddy rice growing fields from reaped fields or the other crops growing fields by the PALSAR-2 data. But the RVI value is vaguely related to such land use or biomass at the present preliminary experiment. The continuous research by the additional PALSAR-2 full-polarimetry data should be desired.

  1. Accumulation and health risk of heavy metals in vegetables from harmless and organic vegetable production systems of China.

    Science.gov (United States)

    Chen, Yong; Hu, Wenyou; Huang, Biao; Weindorf, David C; Rajan, Nithya; Liu, Xiaoxiao; Niedermann, Silvana

    2013-12-01

    Heavy metal accumulation in vegetables is a growing concern for public health. Limited studies have elucidated the heavy metal accumulation characteristics and health risk of different vegetables produced in different facilities such as greenhouses and open-air fields and under different management modes such as harmless and organic. Given the concern over the aforementioned factors related to heavy metal accumulation, this study selected four typical greenhouse vegetable production bases, short-term harmless greenhouse vegetable base (SHGVB), middle-term harmless greenhouse vegetable base (MHGVB), long-term harmless greenhouse vegetable base (LHGVB), and organic greenhouse vegetable base (OGVB), in Nanjing City, China to study heavy metal accumulation in different vegetables and their associated health risks. Results showed that soils and vegetables from SHGVB and OGVB apparently accumulated fewer certain heavy metals than those from other bases, probably due to fewer planting years and special management, respectively. Greenhouse conditions significantly increased certain soil heavy metal concentrations relative to open-air conditions. However, greenhouse conditions did not significantly increase concentrations of As, Cd, Cu, Hg, and Zn in leaf vegetables. In fact, under greenhouse conditions, Pb accumulation was effectively reduced. The main source of soil heavy metals was the application of large amounts of low-grade fertilizer. There was larger health risk for producers' children to consume vegetables from the three harmless vegetable bases than those of residents' children. The hazard index (HI) over a large area exceeded 1 for these two kinds of children in the MHGVB and LHGVB. There was also a slight risk in the SHGVB for producers' children solely. However, the HI of the whole area of the OGVB for two kinds of children was below 1, suggesting low risk of heavy metal exposure through the food chain. Notably, the contribution rate of Cu and Zn to the HI were

  2. Sensitivity of vegetation indices and gross primary production of tallgrass prairie to severe drought

    Energy Technology Data Exchange (ETDEWEB)

    Wagle, Pradeep; Xiao, Xiangming; Torn, Margaret S.; Cook, David R.; Matamala, Roser; Fischer, Marc L.; Jin, Cui; Dong, Jinwei; Biradar, Chandrashekhar

    2014-09-01

    Drought affects vegetation photosynthesis and growth.Many studies have used the normalized difference vegetation index (NDVI), which is calculated as the normalized ratio between near infrared and red spectral bands in satellite images, to evaluate the response of vegetation to drought. In this study, we examined the impacts of drought on three vegetation indices (NDVI, enhanced vegetation index, EVI, and land surface water index, LSWI) and CO2 flux from three tallgrass prairie eddy flux tower sites in the U.S. Gross primary production (GPP) was also modeled using a satellite-based Vegetation Photosynthesis Model (VPM), and the modeled GPP (GPPVPM) was compared with the GPP (GPPEC) derived from eddy covariance measurements. Precipitation at two sites in Oklahoma was 30% below the historical mean in both years of the study period (2005–2006), while the site in Illinois did not experience drought in the 2005–2007 study period. The EVI explained the seasonal dynamics of GPP better than did NDVI. The LSWI dropped below zero during severe droughts in the growing season, showing its potential to track drought. The result shows that GPP was more sensitive to drought than were vegetation indices, and EVI and LSWI were more sensitive than NDVI. We developed a modified function (Wscalar), calculated as a function of LSWI, to account for the effect of severe droughts on GPP in VPM. The GPPVPM from the modified VPM accounted for the rapid reduction in GPP during severe droughts and the seasonal dynamics of GPPVPM agreed reasonably well with GPPEC. Our analysis shows that 8-day averaged values (temperature, vapor-pressure deficit) do not reflect the short-term extreme climate events well, suggesting that satellite based models may need to be run at daily or hourly scales, especially under unfavorable climatic conditions.

  3. Yield estimation using SPOT-VEGETATION products: A case study of wheat in European countries

    NARCIS (Netherlands)

    Kowalik, W.; Dabrowska-Zielinska, K.; Meroni, M.; Raczka, T.U.; Wit, de A.J.W.

    2014-01-01

    In the period 1999-2009 ten-day SPOT-VEGETATION products of the Normalized Difference Vegetation Index (NDVI) and Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) at 1 km spatial resolution were used in order to estimate and forecast the wheat yield over Europe. The products were

  4. Satellite remote sensing for estimating leaf area index, FPAR and primary production. A literature review

    International Nuclear Information System (INIS)

    Boresjoe Bronge, Laine

    2004-03-01

    Land vegetation is a critical component of several biogeochemical cycles that have become the focus of concerted international research effort. Most ecosystem productivity models, carbon budget models, and global models of climate, hydrology and biogeochemistry require vegetation parameters to calculate land surface photosynthesis, evapotranspiration and net primary production. Therefore, accurate estimates of vegetation parameters are increasingly important in the carbon cycle, the energy balance and in environmental impact assessment studies. The possibility of quantitatively estimating vegetation parameters of importance in this context using satellite data has been explored by numerous papers dealing with the subject. This report gives a summary of the present status and applicability of satellite remote sensing for estimating vegetation productivity by using vegetation index for calculating leaf area index (LAI) and fraction of absorbed photosynthetically active radiation (FPAR). Some possible approaches for use of satellite data for estimating LAI, FPAR and net primary production (NPP) on a local scale are suggested. Recommendations for continued work in the Forsmark and Oskarshamn investigation areas, where vegetation data and NDVI-images based on satellite data have been produced, are also given

  5. Satellite remote sensing for estimating leaf area index, FPAR and primary production. A literature review

    Energy Technology Data Exchange (ETDEWEB)

    Boresjoe Bronge, Laine [SwedPower AB, Stockholm (Sweden)

    2004-03-01

    Land vegetation is a critical component of several biogeochemical cycles that have become the focus of concerted international research effort. Most ecosystem productivity models, carbon budget models, and global models of climate, hydrology and biogeochemistry require vegetation parameters to calculate land surface photosynthesis, evapotranspiration and net primary production. Therefore, accurate estimates of vegetation parameters are increasingly important in the carbon cycle, the energy balance and in environmental impact assessment studies. The possibility of quantitatively estimating vegetation parameters of importance in this context using satellite data has been explored by numerous papers dealing with the subject. This report gives a summary of the present status and applicability of satellite remote sensing for estimating vegetation productivity by using vegetation index for calculating leaf area index (LAI) and fraction of absorbed photosynthetically active radiation (FPAR). Some possible approaches for use of satellite data for estimating LAI, FPAR and net primary production (NPP) on a local scale are suggested. Recommendations for continued work in the Forsmark and Oskarshamn investigation areas, where vegetation data and NDVI-images based on satellite data have been produced, are also given.

  6. Optimizing cloud removal from satellite remotely sensed data for monitoring vegetation dynamics in humid tropical climate

    International Nuclear Information System (INIS)

    Hashim, M; Pour, A B; Onn, C H

    2014-01-01

    Remote sensing technology is an important tool to analyze vegetation dynamics, quantifying vegetation fraction of Earth's agricultural and natural vegetation. In optical remote sensing analysis removing atmospheric interferences, particularly distribution of cloud contaminations, are always a critical task in the tropical climate. This paper suggests a fast and alternative approach to remove cloud and shadow contaminations for Landsat Enhanced Thematic Mapper + (ETM + ) multi temporal datasets. Band 3 and Band 4 from all the Landsat ETM + dataset are two main spectral bands that are very crucial in this study for cloud removal technique. The Normalise difference vegetation index (NDVI) and the normalised difference soil index (NDSI) are two main derivatives derived from the datasets. Change vector analysis is used in this study to seek the vegetation dynamics. The approach developed in this study for cloud optimizing can be broadly applicable for optical remote sensing satellite data, which are seriously obscured with heavy cloud contamination in the tropical climate

  7. Vegetation, population and ecological track as sustainability indicators in Colombia

    International Nuclear Information System (INIS)

    Marquez Calle, German

    2000-01-01

    Biophysical sustainability, namely natural capabilities to sustain human development in Colombia, is explored through environmental indicators based on land cover and demographic variables. Remnant vegetation index (IVR in Spanish) uses cover as a measure of ecosystem functionality. Population pressure index (IPD) applies population density to environmental demand analysis. Footprint index (IHE) relates the inverse of density with sustainability. Environmental criticality index combines IVR and IPD to detect offer/demand unbalances. Results suggest Colombia is sustainable although many places in it could be in danger; this could be related with social and economical features of the country

  8. Studying Vegetation Salinity: From the Field View to a Satellite-Based Perspective

    Directory of Open Access Journals (Sweden)

    Rachel Lugassi

    2017-02-01

    Full Text Available Salinization of irrigated lands in the semi-arid Jezreel Valley, Northern Israel results in soil-structure deterioration and crop damage. We formulated a generic rule for estimating salinity of different vegetation types by studying the relationship between Cl/Na and different spectral slopes in the visible–near infrared–shortwave infrared (VIS–NIR–SWIR spectral range using both field measurements and satellite imagery (Sentinel-2. For the field study, the slope-based model was integrated with conventional partial least squares (PLS analyses. Differences in 14 spectral ranges, indicating changes in salinity levels, were identified across the VIS–NIR–SWIR region (350–2500 nm. Next, two different models were run using PLS regression: (i using spectral slope data across these ranges; and (ii using preprocessed spectral reflectance. The best model for predicting Cl content was based on continuum removal reflectance (R2 = 0.84. Satisfactory correlations were obtained using the slope-based PLS model (R2 = 0.77 for Cl and R2 = 0.63 for Na. Thus, salinity contents in fresh plants could be estimated, despite masking of some spectral regions by water absorbance. Finally, we estimated the most sensitive spectral channels for monitoring vegetation salinity from a satellite perspective. We evaluated the recently available Sentinel-2 imagery’s ability to distinguish variability in vegetation salinity levels. The best estimate of a Sentinel-2-based vegetation salinity index was generated based on a ratio between calculated slopes: the 490–665 nm and 705–1610 nm. This index was denoted as the Sentinel-2-based vegetation salinity index (SVSI (band 4 − band 2/(band 5 + band 11.

  9. The Effect of Vegetation Productivity on Millet Prices in the Informal Markets of Mali, Burkina Faso and Niger

    Energy Technology Data Exchange (ETDEWEB)

    Brown, M.E. [Department of Geography, University of Maryland, NASA Goddard Space Flight Center, Code 923, Greenbelt, MD 20771 (United States); Pinzon, J.E. [Science Systems and Applications Inc., NASA Goddard Space Flight Center, Code 923, Greenbelt, MD (United States); Prince, S.D. [Department of Geography, University of Maryland, College Park, MD (United States)

    2006-09-15

    Systematic evaluation of food security throughout the Sahel has been attempted for nearly two decades. Food security analyses have used both food prices to determine the ability of the population to access food, and satellite-derived vegetation indices that measure vegetation production to establish how much food is available each year. The relationship between these two food security indicators is explored here using correspondence analysis and through the use of Markov chain models. Two sources of quantitative data were used: 8 km normalized difference vegetation index (NDVI) data from the Advanced Very High Resolution Radiometers (AVHRR) carried on the NOAA series of satellites, and monthly millet prices from 445 markets in Mali, Niger and Burkina Faso. The results show that the growing season vegetation production is related to the price of millet at the annual and the seasonal time scales. If the growing season was characterized by erratic, sparse rainfall, it resulted in higher prices, and well-distributed, abundant rainfall resulted in lower prices. The correspondence between vegetation production and millet prices is used to produce maps of millet prices for West Africa.

  10. bacteriological quality of some ready to eat vegetables as retailed ...

    African Journals Online (AJOL)

    DR. AMINU

    Key words: Quality, Vegetable, Aerobic plate count, coliform index. INTRODUCTION ... before consumption (Okigbo, 1990). ... peptone water from which 1ml was transferred to the first test .... Crops for Human Consumption 1996; FDA 1998).

  11. Cooking time but not cooking method affects children's acceptance of Brassica vegetables

    NARCIS (Netherlands)

    Poelman, A.A.M.; Delahunty, C.M.; Graaf, de C.

    2013-01-01

    The home environment potentially presents a simple means to increase acceptance of sensory properties of vegetables by preparation. This research investigated how preparation can effectively impact upon children's acceptance for vegetables. Five- and six-year old children (n = 82, balanced for

  12. Satellite-based hybrid drought monitoring tool for prediction of vegetation condition in Eastern Africa: A case study for Ethiopia

    Science.gov (United States)

    Tadesse, Tsegaye; Demisse, Getachew Berhan; Zaitchik, Ben; Dinku, Tufa

    2014-03-01

    An experimental drought monitoring tool has been developed that predicts the vegetation condition (Vegetation Outlook) using a regression-tree technique at a monthly time step during the growing season in Eastern Africa. This prediction tool (VegOut-Ethiopia) is demonstrated for Ethiopia as a case study. VegOut-Ethiopia predicts the standardized values of the Normalized Difference Vegetation Index (NDVI) at multiple time steps (weeks to months into the future) based on analysis of "historical patterns" of satellite, climate, and oceanic data over historical records. The model underlying VegOut-Ethiopia capitalizes on historical climate-vegetation interactions and ocean-climate teleconnections (such as El Niño and the Southern Oscillation (ENSO)) expressed over the 24 year data record and also considers several environmental characteristics (e.g., land cover and elevation) that influence vegetation's response to weather conditions to produce 8 km maps that depict future general vegetation conditions. VegOut-Ethiopia could provide vegetation monitoring capabilities at local, national, and regional levels that can complement more traditional remote sensing-based approaches that monitor "current" vegetation conditions. The preliminary results of this case study showed that the models were able to predict the vegetation stress (both spatial extent and severity) in drought years 1-3 months ahead during the growing season in Ethiopia. The correlation coefficients between the predicted and satellite-observed vegetation condition range from 0.50 to 0.90. Based on the lessons learned from past research activities and emerging experimental forecast models, future studies are recommended that could help Eastern Africa in advancing knowledge of climate, remote sensing, hydrology, and water resources.

  13. Influence of vegetable coagulant and ripening time on the lipolytic and sensory profile of cheeses made with raw goat milk from Canary breeds.

    Science.gov (United States)

    Rincón, Arturo A; Pino, Verónica; Fresno, María R; Jiménez-Abizanda, Ana I; Álvarez, Sergio; Ayala, Juan H; Afonso, Ana M

    2017-04-01

    Free fatty acids and sensory profiles were obtained for cheeses made with raw goat milk and vegetable coagulant, derived from the cardoon flower ( Cynara cardunculus), at different ripening times (7 and 20 days). A solid-liquid phase extraction method followed by solid-phase extraction and gas chromatography was used. Profiles were also obtained with cheeses made with commercial coagulant, traditional kid rennet paste, and mixture coagulant (vegetable coagulant-kid rennet). The use of vegetable coagulant and vegetable coagulant-kid rennet is common in traditional Protected Designation of Origin cheeses such as " Queso Flor de Guía" and " Queso Media Flor de Guía" (Spain). Contents of short-chain free fatty acids (7.5-22.5 mmol·kg -1 ), medium-chain free fatty acids (0.4-3.7 mmol·kg -1 ), and long-chain free fatty acids (0.2-2.1 mmol·kg -1 ) varied depending on the coagulant type and the ripening time. Vegetable coagulant cheeses present odour intensity and flavour intensity much higher than commercial coagulant cheeses in the sensory analysis for cheeses obtained with seven days of ripening, but the values decrease when increasing the ripening time. Multivariate analysis allowed us to differentiate cheese samples according to the ripening time when using lipolytic profile and according to the coagulant type using the sensory profile.

  14. Comparison of Eight Techniques for Reconstructing Multi-Satellite Sensor Time-Series NDVI Data Sets in the Heihe River Basin, China

    Directory of Open Access Journals (Sweden)

    Liying Geng

    2014-03-01

    Full Text Available More than 20 techniques have been developed to de-noise time-series vegetation index data from different satellite sensors to reconstruct long time-series data sets. Although many studies have compared Normalized Difference Vegetation Index (NDVI noise-reduction techniques, few studies have compared these techniques systematically and comprehensively. This study tested eight techniques for smoothing different vegetation types using different types of multi-temporal NDVI data (Advanced Very High Resolution Radiometer (AVHRR (Global Inventory Modeling and Map Studies (GIMMS and Pathfinder AVHRR Land (PAL, Satellite Pour l’ Observation de la Terre (SPOT VEGETATION (VGT, and Moderate Resolution Imaging Spectroradiometer (MODIS (Terra with the ultimate purpose of determining the best reconstruction technique for each type of vegetation captured with four satellite sensors. These techniques include the modified best index slope extraction (M-BISE technique, the Savitzky-Golay (S-G technique, the mean value iteration filter (MVI technique, the asymmetric Gaussian (A-G technique, the double logistic (D-L technique, the changing-weight filter (CW technique, the interpolation for data reconstruction (IDR technique, and the Whittaker smoother (WS technique. These techniques were evaluated by calculating the root mean square error (RMSE, the Akaike Information Criterion (AIC, and the Bayesian Information Criterion (BIC. The results indicate that the S-G, CW, and WS techniques perform better than the other tested techniques, while the IDR, M-BISE, and MVI techniques performed worse than the other techniques. The best de-noise technique varies with different vegetation types and NDVI data sources. The S-G performs best in most situations. In addition, the CW and WS are effective techniques that were exceeded only by the S-G technique. The assessment results are consistent in terms of the three evaluation indexes for GIMMS, PAL, and SPOT data in the study

  15. Detection of Chlorophyll and Leaf Area Index Dynamics from Sub-weekly Hyperspectral Imagery

    Science.gov (United States)

    Houborg, Rasmus; McCabe, Matthew F.; Angel, Yoseline; Middleton, Elizabeth M.

    2016-01-01

    Temporally rich hyperspectral time-series can provide unique time critical information on within-field variations in vegetation health and distribution needed by farmers to effectively optimize crop production. In this study, a dense time series of images were acquired from the Earth Observing-1 (EO-1) Hyperion sensor over an intensive farming area in the center of Saudi Arabia. After correction for atmospheric effects, optimal links between carefully selected explanatory hyperspectral vegetation indices and target vegetation characteristics were established using a machine learning approach. A dataset of in-situ measured leaf chlorophyll (Chll) and leaf area index (LAI), collected during five intensive field campaigns over a variety of crop types, were used to train the rule-based predictive models. The ability of the narrow-band hyperspectral reflectance information to robustly assess and discriminate dynamics in foliar biochemistry and biomass through empirical relationships were investigated. This also involved evaluations of the generalization and reproducibility of the predictions beyond the conditions of the training dataset. The very high temporal resolution of the satellite retrievals constituted a specifically intriguing feature that facilitated detection of total canopy Chl and LAI dynamics down to sub-weekly intervals. The study advocates the benefits associated with the availability of optimum spectral and temporal resolution spaceborne observations for agricultural management purposes.

  16. Bayesian Nonparametric Mixture Estimation for Time-Indexed Functional Data in R

    Directory of Open Access Journals (Sweden)

    Terrance D. Savitsky

    2016-08-01

    Full Text Available We present growfunctions for R that offers Bayesian nonparametric estimation models for analysis of dependent, noisy time series data indexed by a collection of domains. This data structure arises from combining periodically published government survey statistics, such as are reported in the Current Population Study (CPS. The CPS publishes monthly, by-state estimates of employment levels, where each state expresses a noisy time series. Published state-level estimates from the CPS are composed from household survey responses in a model-free manner and express high levels of volatility due to insufficient sample sizes. Existing software solutions borrow information over a modeled time-based dependence to extract a de-noised time series for each domain. These solutions, however, ignore the dependence among the domains that may be additionally leveraged to improve estimation efficiency. The growfunctions package offers two fully nonparametric mixture models that simultaneously estimate both a time and domain-indexed dependence structure for a collection of time series: (1 A Gaussian process (GP construction, which is parameterized through the covariance matrix, estimates a latent function for each domain. The covariance parameters of the latent functions are indexed by domain under a Dirichlet process prior that permits estimation of the dependence among functions across the domains: (2 An intrinsic Gaussian Markov random field prior construction provides an alternative to the GP that expresses different computation and estimation properties. In addition to performing denoised estimation of latent functions from published domain estimates, growfunctions allows estimation of collections of functions for observation units (e.g., households, rather than aggregated domains, by accounting for an informative sampling design under which the probabilities for inclusion of observation units are related to the response variable. growfunctions includes plot

  17. Environment, vegetation and greenness (NDVI) along the North America and Eurasia Arctic transects

    International Nuclear Information System (INIS)

    Walker, D A; Raynolds, M K; Kuss, P; Kade, A N; Epstein, H E; Frost, G V; Kopecky, M A; Daniëls, F J A; Leibman, M O; Moskalenko, N G; Khomutov, A V; Matyshak, G V; Khitun, O V; Forbes, B C; Bhatt, U S; Vonlanthen, C M; Tichý, L

    2012-01-01

    Satellite-based measurements of the normalized difference vegetation index (NDVI; an index of vegetation greenness and photosynthetic capacity) indicate that tundra environments are generally greening and becoming more productive as climates warm in the Arctic. The greening, however, varies and is even negative in some parts of the Arctic. To help interpret the space-based observations, the International Polar Year (IPY) Greening of the Arctic project conducted ground-based surveys along two >1500 km transects that span all five Arctic bioclimate subzones. Here we summarize the climate, soil, vegetation, biomass, and spectral information collected from the North America Arctic transect (NAAT), which has a more continental climate, and the Eurasia Arctic transect (EAT), which has a more oceanic climate. The transects have broadly similar summer temperature regimes and overall vegetation physiognomy, but strong differences in precipitation, especially winter precipitation, soil texture and pH, disturbance regimes, and plant species composition and structure. The results indicate that summer warmth and NDVI increased more strongly along the more continental transect. (letter)

  18. Mapping gains and losses in woody vegetation across global tropical drylands

    DEFF Research Database (Denmark)

    Tian, Feng; Brandt, Martin Stefan; Liu, Yi Y

    2017-01-01

    MODerate resolution Imaging Spectroradiometer (MODIS) Normalized Difference Vegetation Index (NDVI) data to remove the interannual fluctuations of the woody leaf component. We revealed significant trends (P ... trend in the leaf component (VODleaf modeled from NDVI), indicating pronounced gradual growth/decline in woody vegetation not captured by traditional assessments. The method is validated using a unique record of ground measurements from the semiarid Sahel and shows a strong agreement between changes...

  19. Interactive Vegetation Phenology, Soil Moisture, and Monthly Temperature Forecasts

    Science.gov (United States)

    Koster, R. D.; Walker, G. K.

    2015-01-01

    The time scales that characterize the variations of vegetation phenology are generally much longer than those that characterize atmospheric processes. The explicit modeling of phenological processes in an atmospheric forecast system thus has the potential to provide skill to subseasonal or seasonal forecasts. We examine this possibility here using a forecast system fitted with a dynamic vegetation phenology model. We perform three experiments, each consisting of 128 independent warm-season monthly forecasts: 1) an experiment in which both soil moisture states and carbon states (e.g., those determining leaf area index) are initialized realistically, 2) an experiment in which the carbon states are prescribed to climatology throughout the forecasts, and 3) an experiment in which both the carbon and soil moisture states are prescribed to climatology throughout the forecasts. Evaluating the monthly forecasts of air temperature in each ensemble against observations, as well as quantifying the inherent predictability of temperature within each ensemble, shows that dynamic phenology can indeed contribute positively to subseasonal forecasts, though only to a small extent, with an impact dwarfed by that of soil moisture.

  20. Fire passage on geomorphic fractures in Cerrado: effect on vegetation

    OpenAIRE

    Otacílio Antunes Santana; José Marcelo Imaña Encinas; Flávio Luiz de Souza Silveira

    2017-01-01

    Geomorphic fracture is a natural geologic formation that sometimes forms a deep fissure in the rock with the establishment of soil and vegetation. The objective of this work was to analyze vegetation within geomorphic fractures under the effect of wildfire passage. The biometric variables evaluated before and after fire passage were: diameter, height, leaf area index, timber volume, grass biomass, number of trees and shrubs and of species. Results (in fractures) were compared to adjacent area...

  1. Intake of Raw Fruits and Vegetables Is Associated With Better Mental Health Than Intake of Processed Fruits and Vegetables

    Science.gov (United States)

    Brookie, Kate L.; Best, Georgia I.; Conner, Tamlin S.

    2018-01-01

    Background: Higher intakes of fruits and vegetables, rich in micronutrients, have been associated with better mental health. However, cooking or processing may reduce the availability of these important micronutrients. This study investigated the differential associations between intake of raw fruits and vegetables, compared to processed (cooked or canned) fruits and vegetables, and mental health in young adults. Methods: In a cross-sectional survey design, 422 young adults ages 18–25 (66.1% female) living in New Zealand and the United States completed an online survey that assessed typical consumption of raw vs. cooked/canned/processed fruits and vegetables, negative and positive mental health (depressive symptoms, anxiety, negative mood, positive mood, life satisfaction, and flourishing), and covariates (including socio-economic status, body mass index, sleep, physical activity, smoking, and alcohol use). Results: Controlling for covariates, raw fruit and vegetable intake (FVI) predicted reduced depressive symptoms and higher positive mood, life satisfaction, and flourishing; processed FVI only predicted higher positive mood. The top 10 raw foods related to better mental health were carrots, bananas, apples, dark leafy greens like spinach, grapefruit, lettuce, citrus fruits, fresh berries, cucumber, and kiwifruit. Conclusions: Raw FVI, but not processed FVI, significantly predicted higher mental health outcomes when controlling for the covariates. Applications include recommending the consumption of raw fruits and vegetables to maximize mental health benefits. PMID:29692750

  2. Intake of Raw Fruits and Vegetables Is Associated With Better Mental Health Than Intake of Processed Fruits and Vegetables

    Directory of Open Access Journals (Sweden)

    Kate L. Brookie

    2018-04-01

    Full Text Available Background: Higher intakes of fruits and vegetables, rich in micronutrients, have been associated with better mental health. However, cooking or processing may reduce the availability of these important micronutrients. This study investigated the differential associations between intake of raw fruits and vegetables, compared to processed (cooked or canned fruits and vegetables, and mental health in young adults.Methods: In a cross-sectional survey design, 422 young adults ages 18–25 (66.1% female living in New Zealand and the United States completed an online survey that assessed typical consumption of raw vs. cooked/canned/processed fruits and vegetables, negative and positive mental health (depressive symptoms, anxiety, negative mood, positive mood, life satisfaction, and flourishing, and covariates (including socio-economic status, body mass index, sleep, physical activity, smoking, and alcohol use.Results: Controlling for covariates, raw fruit and vegetable intake (FVI predicted reduced depressive symptoms and higher positive mood, life satisfaction, and flourishing; processed FVI only predicted higher positive mood. The top 10 raw foods related to better mental health were carrots, bananas, apples, dark leafy greens like spinach, grapefruit, lettuce, citrus fruits, fresh berries, cucumber, and kiwifruit.Conclusions: Raw FVI, but not processed FVI, significantly predicted higher mental health outcomes when controlling for the covariates. Applications include recommending the consumption of raw fruits and vegetables to maximize mental health benefits.

  3. Regional and landscape-scale variability of Landsat-observed vegetation dynamics in northwest Siberian tundra

    International Nuclear Information System (INIS)

    Frost, Gerald V; Epstein, Howard E; Walker, Donald A

    2014-01-01

    Widespread increases in Arctic tundra productivity have been documented for decades using coarse-scale satellite observations, but finer-scale observations indicate that changes have been very uneven, with a high degree of landscape- and regional-scale heterogeneity. Here we analyze time-series of the Normalized Difference Vegetation Index (NDVI) observed by Landsat (1984–2012), to assess landscape- and regional-scale variability of tundra vegetation dynamics in the northwest Siberian Low Arctic, a little-studied region with varied soils, landscape histories, and permafrost attributes. We also estimate spatio-temporal rates of land-cover change associated with expansion of tall alder (Alnus) shrublands, by integrating Landsat time-series with very-high-resolution imagery dating to the mid-1960s. We compiled Landsat time-series for eleven widely-distributed landscapes, and performed linear regression of NDVI values on a per-pixel basis. We found positive net NDVI trends (‘greening’) in nine of eleven landscapes. Net greening occurred in alder shrublands in all landscapes, and strong greening tended to correspond to shrublands that developed since the 1960s. Much of the spatial variability of greening within landscapes was linked to landscape physiography and permafrost attributes, while between-landscape variability largely corresponded to differences in surficial geology. We conclude that continued increases in tundra productivity in the region are likely in upland tundra landscapes with fine-textured, cryoturbated soils; these areas currently tend to support discontinuous vegetation cover, but are highly susceptible to rapid increases in vegetation cover, as well as land-cover changes associated with the development of tall shrublands. (paper)

  4. Vegetation and acidification, Chapter 5

    Science.gov (United States)

    David R. DeWalle; James N. Kochenderfer; Mary Beth Adams; Gary W. Miller

    2006-01-01

    In this chapter, the impact of watershed acidification treatments on WS3 at the Fernow Experimental Forest (FEF) and at WS9 on vegetation is presented and summarized in a comprehensive way for the first time. WS7 is used as a vegetative reference basin for WS3, while untreated plots within WS9 are used as a vegetative reference for WS9. Bioindicators of acidification...

  5. Different techniques of multispectral data analysis for vegetation fraction retrieval

    Science.gov (United States)

    Kancheva, Rumiana; Georgiev, Georgi

    2012-07-01

    Vegetation monitoring is one of the most important applications of remote sensing technologies. In respect to farmlands, the assessment of crop condition constitutes the basis of growth, development, and yield processes monitoring. Plant condition is defined by a set of biometric variables, such as density, height, biomass amount, leaf area index, and etc. The canopy cover fraction is closely related to these variables, and is state-indicative of the growth process. At the same time it is a defining factor of the soil-vegetation system spectral signatures. That is why spectral mixtures decomposition is a primary objective in remotely sensed data processing and interpretation, specifically in agricultural applications. The actual usefulness of the applied methods depends on their prediction reliability. The goal of this paper is to present and compare different techniques for quantitative endmember extraction from soil-crop patterns reflectance. These techniques include: linear spectral unmixing, two-dimensional spectra analysis, spectral ratio analysis (vegetation indices), spectral derivative analysis (red edge position), colorimetric analysis (tristimulus values sum, chromaticity coordinates and dominant wavelength). The objective is to reveal their potential, accuracy and robustness for plant fraction estimation from multispectral data. Regression relationships have been established between crop canopy cover and various spectral estimators.

  6. Heavy metals concentration and distribution in soils and vegetation at Korle Lagoon area in Accra, Ghana

    DEFF Research Database (Denmark)

    Fosu-Mensah, Benedicta Yayra; Addae, Emmanuel; Yirenya-Tawiah, Dzidzo

    2017-01-01

    The call for reclamation of land around Korle Lagoon in Accra, Ghana, where burning of E-waste and cultivation of vegetables takes place, make risk assessment of heavy metal contaminations important. This study aimed at evaluating the levels and risk of heavy metal contamination in soils...... and vegetation around the Korle lagoon area in Accra. Geoaccumulation index, enrichment factor and pollution load index were determined to assess the risk of contamination. The levels and distribution of nine heavy metals (Pb, Hg, Cd, As, Zn, Sn, Ni, Cu and Cr) in soil (0 – 20 cm) and common vegetation (Panicum...... was significantly different (p burning of e-waste should be enforced and animals...

  7. a case s ation of heavy metals' health risk index in vegetable unflower

    African Journals Online (AJOL)

    userpc

    ntrol of pollution produce from industries affects both air and soil table Amaranth and Sunflower ... ls, Health risk, Sunflower, and Vegetable Amaranth. ign material into a .... were homogenized by grinding using ceramic coated grinder. All the ...

  8. Changes in vegetation and soil seed bank of meadow after waterlogging caused by Castor fiber

    Directory of Open Access Journals (Sweden)

    Magdalena Franczak

    2015-07-01

    Full Text Available Soil waterlogging is among abiotic stresses that influence species composition and productivity in numerous plant communities. The aim of the study was to find answer to the question of how waterlogging caused by beavers’ activity induces quantitative and qualitative changes of vegetation and soil seed bank levels of variable-moist meadows. An immediate effect of the waterlogging at the level of vegetation was the decline in species richness and a decrease in the values of the biodiversity index. Water stress inhibited growth and development of plants already present and, primarily, impeded recruitment of new individuals of species characteristic of variable-moist meadows, e.g. Cirsium rivulare, Filipendula ulmaria and Lythrum salicaria, which were replaced by Carex acutiformis. Prolonged waterlogging did not induce equally substantial changes in the soil seed bank as in the vegetation. Both in the waterlogged and control patches, slightly decreased species richness and biodiversity index were recorded. After waterlogging withdrawal, the reserves of the soil seed bank were slightly higher than the initial values. The differences were not statistically significant. In the waterlogged patch, the qualitative floristic similarity between taxa identified in the soil seed bank and vegetation cover declined, which was evidenced by the value of Jaccard’s index decreasing from 0.46 to 0.36. A reverse relationship was found in control patch, where the value of the similarity index slightly increased from 0.41 to 0.48.

  9. Markov Chain Modelling for Short-Term NDVI Time Series Forecasting

    Directory of Open Access Journals (Sweden)

    Stepčenko Artūrs

    2016-12-01

    Full Text Available In this paper, the NDVI time series forecasting model has been developed based on the use of discrete time, continuous state Markov chain of suitable order. The normalised difference vegetation index (NDVI is an indicator that describes the amount of chlorophyll (the green mass and shows the relative density and health of vegetation; therefore, it is an important variable for vegetation forecasting. A Markov chain is a stochastic process that consists of a state space. This stochastic process undergoes transitions from one state to another in the state space with some probabilities. A Markov chain forecast model is flexible in accommodating various forecast assumptions and structures. The present paper discusses the considerations and techniques in building a Markov chain forecast model at each step. Continuous state Markov chain model is analytically described. Finally, the application of the proposed Markov chain model is illustrated with reference to a set of NDVI time series data.

  10. Production Guides for Meat and Vegetable Entrees and Desserts Developed for Use in the Frozen Foil Pack Feeding System, F.E. Warren Air Force Base

    Science.gov (United States)

    1976-02-01

    crurbs, dry 2,32 1,053 Note: At. no time shall Nonfat dry milk 2.32 1,053 temperature of uncooked Eggs , whole, beaten 1.31 595 meatballs be over 500 F...Listing 94-99 Meat 94 Dairy, Egg , Condiment 96 Vegetables 98 Production Guide Index 100-103 Meat Entree 100 Vegetable Entree 102 Desserts 103 2...Filling Eggs , whole, beaten 2.75 1,249 6. Combine all filling Cheese, cottage, drained 6.50 2,951 ingredients, mix thoroughly Cheese, grated parmesan

  11. Pruning affects the vegetative balance of the wine grape (Vitis vinifera L.

    Directory of Open Access Journals (Sweden)

    Pedro José Almanza-Merchán

    2014-08-01

    Full Text Available Grape cultivation for wine production at altitudes between 2,200 and 2,600 m a.s.l. started in the department of Boyaca in 1982. Quality wines are produced by the AinKarim Vineyard in Ricaurte High. Wine grapes have to possess suitable organoleptic compounds at harvest in order to guarantee quality grape must that can be converted into wine. Therefore, it is necessary to maintain a suitable ratio the sources and the sinks and to guarantee production, quality and vegetative sustainability over time, conserving the equilibrium and benefiting the productive potential of the vineyard. The aim of this study was to evaluate the productive and vegetative balance effect in the wine grape varieties Cabernet Sauvignon and Sauvignon Blanc in Sutamarchan-Boyaca, considering different pruning types (short, long, and mixed. A bifactorial, completely random statistical design was used. At the time of harvest, the fruit production and pruned wood were evaluated. The long-pruned vines showed the best behavior and the most balanced source/sink relationship,, while Sauvignon Blanc demonstrated a better productive yield. Meanwhile, the short and mixed prunings had the better values for the Ravaz index (balance between fruit production and vegetative growth, indicating that they are more suitable for the conditions of the region, allowing for sustainability during the productive cycles of the wine grapes.

  12. Relationship Between Remotely-sensed Vegetation Indices, Canopy Attributes and Plant Physiological Processes: What Vegetation Indices Can and Cannot Tell Us About the Landscape

    Directory of Open Access Journals (Sweden)

    Stephen G. Nelson

    2008-03-01

    Full Text Available Vegetation indices (VIs are among the oldest tools in remote sensing studies. Although many variations exist, most of them ratio the reflection of light in the red and NIR sections of the spectrum to separate the landscape into water, soil, and vegetation. Theoretical analyses and field studies have shown that VIs are near-linearly related to photosynthetically active radiation absorbed by a plant canopy, and therefore to light-dependent physiological processes, such as photosynthesis, occurring in the upper canopy. Practical studies have used time-series VIs to measure primary production and evapotranspiration, but these are limited in accuracy to that of the data used in ground truthing or calibrating the models used. VIs are also used to estimate a wide variety of other canopy attributes that are used in Soil-Vegetation-Atmosphere Transfer (SVAT, Surface Energy Balance (SEB, and Global Climate Models (GCM. These attributes include fractional vegetation cover, leaf area index, roughness lengths for turbulent transfer, emissivity and albedo. However, VIs often exhibit only moderate, non-linear relationships to these canopy attributes, compromising the accuracy of the models. We use case studies to illustrate the use and misuse of VIs, and argue for using VIs most simply as a measurement of canopy light absorption rather than as a surrogate for detailed features of canopy architecture. Used this way, VIs are compatible with "Big Leaf" SVAT and GCMs that assume that canopy carbon and moisture fluxes have the same relative response to the environment as any single leaf, simplifying the task of modeling complex landscapes.

  13. Relationship Between Remotely-sensed Vegetation Indices, Canopy Attributes and Plant Physiological Processes: What Vegetation Indices Can and Cannot Tell Us About the Landscape

    Science.gov (United States)

    Glenn, Edward P.; Huete, Alfredo R.; Nagler, Pamela L.; Nelson, Stephen G.

    2008-01-01

    Vegetation indices (VIs) are among the oldest tools in remote sensing studies. Although many variations exist, most of them ratio the reflection of light in the red and NIR sections of the spectrum to separate the landscape into water, soil, and vegetation. Theoretical analyses and field studies have shown that VIs are near-linearly related to photosynthetically active radiation absorbed by a plant canopy, and therefore to light-dependent physiological processes, such as photosynthesis, occurring in the upper canopy. Practical studies have used time-series VIs to measure primary production and evapotranspiration, but these are limited in accuracy to that of the data used in ground truthing or calibrating the models used. VIs are also used to estimate a wide variety of other canopy attributes that are used in Soil-Vegetation-Atmosphere Transfer (SVAT), Surface Energy Balance (SEB), and Global Climate Models (GCM). These attributes include fractional vegetation cover, leaf area index, roughness lengths for turbulent transfer, emissivity and albedo. However, VIs often exhibit only moderate, non-linear relationships to these canopy attributes, compromising the accuracy of the models. We use case studies to illustrate the use and misuse of VIs, and argue for using VIs most simply as a measurement of canopy light absorption rather than as a surrogate for detailed features of canopy architecture. Used this way, VIs are compatible with “Big Leaf” SVAT and GCMs that assume that canopy carbon and moisture fluxes have the same relative response to the environment as any single leaf, simplifying the task of modeling complex landscapes. PMID:27879814

  14. Remotely sensed vegetation indices for seasonal crop yields predictions in the Czech Republic

    Science.gov (United States)

    Hlavinka, Petr; Semerádová, Daniela; Balek, Jan; Bohovic, Roman; Žalud, Zdeněk; Trnka, Miroslav

    2015-04-01

    Remotely sensed vegetation indices by satellites are valuable tool for vegetation conditions assessment also in the case of field crops. This study is based on the use of NDVI (Normalized Difference Vegetation Index) and EVI (Enhanced Vegetation Index) derived from MODIS (Moderate Resolution Imaging Spectroradiometer) aboard Terra satellite. Data available from the year 2000 were analyzed and tested for seasonal yields predictions within selected districts of the Czech Republic (Central Europe). Namely the yields of spring barley, winter wheat and oilseed winter rape during the period from 2000 to 2014 were assessed. Observed yields from 14 districts (NUTS 4) were collected and thus 210 seasons were included. Selected districts differ considerably in their soil fertility and terrain configuration and represent transect across various agroclimatic conditions (from warm and dry to relative cool and wet regions). Two approaches were tested: 1) using of composite remotely sensed data (available in 16 day time step) provided by the USGS (https://lpdaac.usgs.gov/); 2) using daily remotely sensed data in combination with originally developed smoothing method. The yields were successfully predicted based on established regression models (remotely sensed data used as independent parameter). Besides others the impact of severe drought episodes within vegetation were identified and yield reductions at district level predicted (even before harvest). As a result the periods with the best relationship between remotely sensed data and yields were identified. The impact of drought conditions as well as normal or above normal yields of field crops could be predicted by proposed method within study region up to 30 days prior to the harvest. It could be concluded that remotely sensed vegetation conditions assessment should be important part of early warning systems focused on drought. Such information should be widely available for various users (decision makers, farmers, etc.) in

  15. Vegetation Structure of Ebony Leaf Monkey (Trachypithecus auratus) Habitat in Kecubung Ulolanang Nature Preservation Central Java-Indonesia

    Science.gov (United States)

    Ervina, Rahmawati; Wasiq, Hidayat Jafron

    2018-02-01

    Kecubung Ulolanang Nature Preservation is ebony leaf monkey's habitats in Central Java Indonesia. Continuously degradation of their population is caused by illegal hunting and habitat degradation that made this species being vulnerable. Habitat conservation is one of important aspects to prevent them from extinction. The purpose of this research was to analyze the vegetation's structure and composition, which was potentially, becomes habitat and food source for the monkeys. Data collected using purposive sampling with line transect method of four different level of vegetation. Data analysis used Important Value Index and Diversity Index. There were 43 species of vegetation at seedling stage, 18 species at sapling stage, 8 species at poles stage and 27 species at trees stage. Species that had the highest important value index at seedling was Stenochlaena palustri , at the sapling was Gnetum gnemon, at pole was Swietenia mahagoni and at tree was Tectona grandis . Species of trees those were potentially to become habitat (food source) for ebony leaf monkey were T. grandis, Dipterocarpus gracilis, Quercus sundaica and Ficus superba. The highest diversity index was at seedling gwoth stage.

  16. The influence of vegetation, mesoclimate and meteorology on urban atmospheric microclimates across a coastal to desert climate gradient.

    Science.gov (United States)

    Crum, Steven M; Shiflett, Sheri A; Jenerette, G Darrel

    2017-09-15

    Many cities are increasing vegetation in part due to the potential for microclimate cooling. However, the magnitude of vegetation cooling and sensitivity to mesoclimate and meteorology are uncertain. To improve understanding of the variation in vegetation's influence on urban microclimates we asked: how do meso- and regional-scale drivers influence the magnitude and timing of vegetation-based moderation on summertime air temperature (T a ), relative humidity (RH) and heat index (HI) across dryland cities? To answer this question we deployed a network of 180 temperature sensors in summer 2015 over 30 high- and 30 low-vegetated plots in three cities across a coastal to inland to desert climate gradient in southern California, USA. In a followup study, we deployed a network of temperature and humidity sensors in the inland city. We found negative T a and HI and positive RH correlations with vegetation intensity. Furthermore, vegetation effects were highest in evening hours, increasing across the climate gradient, with reductions in T a and increases in RH in low-vegetated plots. Vegetation increased temporal variability of T a , which corresponds with increased nighttime cooling. Increasing mean T a was associated with higher spatial variation in T a in coastal cities and lower variation in inland and desert cities, suggesting a climate dependent switch in vegetation sensitivity. These results show that urban vegetation increases spatiotemporal patterns of microclimate with greater cooling in warmer environments and during nighttime hours. Understanding urban microclimate variation will help city planners identify potential risk reductions associated with vegetation and develop effective strategies ameliorating urban microclimate. Published by Elsevier Ltd.

  17. Estimation of rice situation index in Japan using remotely sensed and meteorological data

    International Nuclear Information System (INIS)

    Kaneko, D.

    2006-01-01

    This research aims to develop a remote sensing method for monitoring rice production in Japan. A photosynthesis-based crop production index CPI for rice is proposed that takes into consideration the solar radiation, the effective air temperature, and normalized vegetation index NDVI as a factor representing vegetation biomass. The CPI index incorporates temperature influences such as the effect of temperature on photosynthesis by grain plant leaves, low-temperature effects of sterility, cool summer damage due to delayed growth, and high-temperature injury. These latter factors are significant at around the heading period of rice. The CPI index for rice was modeled at ten monitoring sites in the Kanto, Tohoku, and Hokkaido districts, which occasionally tend to suffer poor harvests as a result of low temperatures. The photosynthesis-based crop production index CPI proposed here can predict the crop situation index of rice by using NDVI, solar radiation at meteorological observatories and air temperature at AMeDAS sites. The method is based on routine observation data, allowing automated monitoring of rice situation index at arbitrary sites in Japan. However, it is possible to further refine the estimation formula for the rice situation index for early monitoring

  18. Contributions of understory and/or overstory vegetations to soil microbial PLFA and nematode diversities in Eucalyptus monocultures.

    Directory of Open Access Journals (Sweden)

    Jie Zhao

    Full Text Available Ecological interactions between aboveground and belowground biodiversity have received many attentions in the recent decades. Although soil biodiversity declined with the decrease of plant diversity, many previous studies found plant species identities were more important than plant diversity in controlling soil biodiversity. This study focused on the responses of soil biodiversity to the altering of plant functional groups, namely overstory and understory vegetations, rather than plant diversity gradient. We conducted an experiment by removing overstory and/or understory vegetation to compare their effects on soil microbial phospholipid fatty acid (PLFA and nematode diversities in eucalyptus monocultures. Our results indicated that both overstory and understory vegetations could affect soil microbial PLFA and nematode diversities, which manifested as the decrease in Shannon-Wiener diversity index (H' and Pielou evenness index (J and the increase in Simpson dominance index (λ after vegetation removal. Soil microclimate change explained part of variance of soil biodiversity indices. Both overstory and understory vegetations positively correlated with soil microbial PLFA and nematode diversities. In addition, the alteration of soil biodiversity might be due to a mixing effect of bottom-up control and soil microclimate change after vegetation removal in the studied plantations. Given the studied ecosystem is common in humid subtropical and tropical region of the world, our findings might have great potential to extrapolate to large scales and could be conducive to ecosystem management and service.

  19. Diet and endometrial cancer: a focus on the role of fruit and vegetable intake, Mediterranean diet and dietary inflammatory index in the endometrial cancer risk.

    Science.gov (United States)

    Ricceri, Fulvio; Giraudo, Maria Teresa; Fasanelli, Francesca; Milanese, Dario; Sciannameo, Veronica; Fiorini, Laura; Sacerdote, Carlotta

    2017-11-13

    Endometrial cancer is the fourth most common cancer in European women. The major risk factors for endometrial cancer are related to the exposure of endometrium to estrogens not opposed to progestogens, that can lead to a chronic endometrial inflammation. Diet may play a role in cancer risk by modulating chronic inflammation. In the framework of a case-control study, we recruited 297 women with newly diagnosed endometrial cancer and 307 controls from Northern Italy. Using logistic regression, we investigated the role of fruit and vegetable intake, adherence to the Mediterranean diet (MD), and the dietary inflammatory index (DII) in endometrial cancer risk. Women in the highest quintile of vegetable intake had a statistically significantly lower endometrial cancer risk (adjusted OR 5th quintile vs 1st quintile: 0.34, 95% CI 0.17-0.68). Women with high adherence to the MD had a risk of endometrial cancer that was about half that of women with low adherence to the MD (adjusted OR: 0.51, 95% CI 0.39-0.86). A protective effect was detected for all the lower quintiles of DII, with the highest protective effect seen for the lowest quintile (adjusted OR 5th quintile vs 1st quintile: 3.28, 95% CI 1.30-8.26). These results suggest that high vegetable intake, adherence to the MD, and a low DII are related to a lower endometrial cancer risk, with several putative connected biological mechanisms that strengthen the biological plausibility of this association.

  20. Remotely Sensed Northern Vegetation Response to Changing Climate: Growing Season and Productivity Perspective

    Science.gov (United States)

    Ganguly, S.; Park, Taejin; Choi, Sungho; Bi, Jian; Knyazikhin, Yuri; Myneni, Ranga

    2016-01-01

    Vegetation growing season and maximum photosynthetic state determine spatiotemporal variability of seasonal total gross primary productivity of vegetation. Recent warming induced impacts accelerate shifts on growing season and physiological status over Northern vegetated land. Thus, understanding and quantifying these changes are very important. Here, we first investigate how vegetation growing season and maximum photosynthesis state are evolved and how such components contribute on inter-annual variation of seasonal total gross primary productivity. Furthermore, seasonally different response of northern vegetation to changing temperature and water availability is also investigated. We utilized both long-term remotely sensed data to extract larger scale growing season metrics (growing season start, end and duration) and productivity (i.e., growing season summed vegetation index, GSSVI) for answering these questions. We find that regionally diverged growing season shift and maximum photosynthetic state contribute differently characterized productivity inter-annual variability and trend. Also seasonally different response of vegetation gives different view of spatially varying interaction between vegetation and climate. These results highlight spatially and temporally varying vegetation dynamics and are reflective of biome-specific responses of northern vegetation to changing climate.

  1. Broad-Scale Environmental Conditions Responsible for Post-Fire Vegetation Dynamics

    Directory of Open Access Journals (Sweden)

    Stuart E. Marsh

    2010-11-01

    Full Text Available Ecosystem response to disturbance is influenced by environmental conditions at a number of scales. Changes in climate have altered fire regimes across the western United States, and have also likely altered spatio-temporal patterns of post-fire vegetation regeneration. Fire occurrence data and a vegetation index (NDVI derived from the NOAA Advanced Very High Resolution Radiometer (AVHRR were used to monitor post-fire vegetation from 1989 to 2007. We first investigated differences in post-fire rates of vegetation regeneration between ecoregions. We then related precipitation, temperature, and elevation records at four temporal scales to rates of post-fire vegetation regeneration to ascertain the influence of climate on post-fire vegetation dynamics. We found that broad-scale climate factors are an important influence on post-fire vegetation regeneration. Most notably, higher rates of post-fire regeneration occurred with warmer minimum temperatures. Increases in precipitation also resulted in higher rates of post-fire vegetation growth. While explanatory power was slight, multiple statistical approaches provided evidence for real ecological drivers of post-fire regeneration that should be investigated further at finer scales. The sensitivity of post-disturbance vegetation dynamics to climatic drivers has important ramifications for the management of ecosystems under changing climatic conditions. Shifts in temperature and precipitation regimes are likely to result in changes in post-disturbance dynamics, which could represent important feedbacks into the global climate system.

  2. Mapping farmland abandonment and recultivation across Europe using MODIS NDVI time series

    DEFF Research Database (Denmark)

    Estel, Stephan; Kuemmerle, Tobias; Alcántara, Camilo

    2015-01-01

    for recultivation hinges on incomplete knowledge about the spatial patterns of fallow and abandoned farmland, especially at broad geographic scales. Our goals were to develop a methodology to map active and fallow land using MODIS Normalized Differenced Vegetation Index (NDVI) time series and to provide the first...

  3. Arid landscape dynamics along a precipitation gradient: addressing vegetation - landscape structure - resource interactions at different time scales

    NARCIS (Netherlands)

    Buis, E.

    2008-01-01

    This research is entitled ‘Arid landscape dynamics along a precipitation gradient: addressing
    vegetation – landscape structure – resource interactions at different time scales’ with as subtitle
    ‘A case study for the Northern Negev Desert of Israel’. Landscape dynamics describes the

  4. Integrated analysis of climate, soil, topography and vegetative growth in Iberian viticultural regions.

    Science.gov (United States)

    Fraga, Helder; Malheiro, Aureliano C; Moutinho-Pereira, José; Cardoso, Rita M; Soares, Pedro M M; Cancela, Javier J; Pinto, Joaquim G; Santos, João A

    2014-01-01

    The Iberian viticultural regions are convened according to the Denomination of Origin (DO) and present different climates, soils, topography and management practices. All these elements influence the vegetative growth of different varieties throughout the peninsula, and are tied to grape quality and wine type. In the current study, an integrated analysis of climate, soil, topography and vegetative growth was performed for the Iberian DO regions, using state-of-the-art datasets. For climatic assessment, a categorized index, accounting for phenological/thermal development, water availability and grape ripening conditions was computed. Soil textural classes were established to distinguish soil types. Elevation and aspect (orientation) were also taken into account, as the leading topographic elements. A spectral vegetation index was used to assess grapevine vegetative growth and an integrated analysis of all variables was performed. The results showed that the integrated climate-soil-topography influence on vine performance is evident. Most Iberian vineyards are grown in temperate dry climates with loamy soils, presenting low vegetative growth. Vineyards in temperate humid conditions tend to show higher vegetative growth. Conversely, in cooler/warmer climates, lower vigour vineyards prevail and other factors, such as soil type and precipitation acquire more important roles in driving vigour. Vines in prevailing loamy soils are grown over a wide climatic diversity, suggesting that precipitation is the primary factor influencing vigour. The present assessment of terroir characteristics allows direct comparison among wine regions and may have great value to viticulturists, particularly under a changing climate.

  5. Normalized difference vegetation index for the South American continent used as a climatic variability indicator

    International Nuclear Information System (INIS)

    Liu, W.T.; Massambani, O.; Festa, M.

    1992-01-01

    The NOAA AVHRR GAC data set was used to produce Normalized Difference Vegetation Index (NDVI) maps for the South American Continent covering the period from August 1, 1981 to June 30, 1987. A 15-day maximum value composite procedure was used to partially eliminate the cloud contamination and atmospheric attenuation. Monthly evolution of NDVI for a dry and a wet year within the period studied was used to estimate the area covered by NDVI value less than 0.223, This value was used as an indicator of the drought area and the delineation of the Low rainfall areas in the continent. It was observed a well defined regional dependence of the drought area variability for the Northeast, Southwest and Northwest continent and also for the Amazon region. It is shown a relative estimation of the area coverage with NDVI less than 0.223 for the years 1982/83 and 1984/85. The dynamics of the drought area evolution in the continent is discussed. It is also presented a diagnosis of regional variability of the continental distribution of drought area from 1981 to 1987 for the months of May and September. This information is also used to discuss its relationship with the EL-Nino-Southern Oscillation (ENSO) and the South American Precipitation patterns during this period. It is suggested that the use of NDVI image to identify the dynamics of the drought induced by low rainfall may provide us valuable information to study the large scale climatic variation

  6. Ecosystems past: prehistory of California vegetation

    Science.gov (United States)

    C.I. Millar; W.B. Woolfenden

    2016-01-01

    The history of California's vegetation, from origins in the Mesozoic through Quaternary is outlined. Climatic and geologic history and the processes driving changes in vegetation over time are also described. 

  7. Contribution of Dynamic Vegetation Phenology to Decadal Climate Predictability

    NARCIS (Netherlands)

    Weiss, M.; Miller, P.A.; Hurk, van den B.J.J.M.; Noije, van T.; Stefanescu, S.; Haarsma, R.; Ulft, van L.H.; Hazeleger, W.; Sager, Le P.; Smith, B.; Schurgers, G.

    2014-01-01

    In this study, the impact of coupling and initializing the leaf area index from the dynamic vegetation model Lund-Potsdam-Jena General Ecosystem Simulator (LPJ-GUESS) is analyzed on skill of decadal predictions in the fully coupled atmosphere-land-ocean-sea ice model, the European Consortium Earth

  8. Impact of vegetation feedback at subseasonal & seasonal timescales on precipitation over North America

    Science.gov (United States)

    Kim, Y.; Wang, G.

    2006-05-01

    Soil moisture-vegetation-precipitation feedbacks tend to enhance soil moisture memory in some areas of the globe, which contributes to the subseasonal and seasonal climate prediction skill. In this study, the impact of vegetation on precipitation over North America is investigated using a coupled land-atmosphere model CAM3- CLM3. The coupled model has been modified to include a predictive vegetation phenology scheme and validated against the MODIS data. Vegetation phenology is modeled by updating the leaf area index (LAI) daily in response to cumulative and concurrent hydrometeorological conditions. First, driven with the climatological SST, a large group of 5-member ensembles of simulations from the late spring and summer to the end of year are generated with the different initial conditions of soil moisture. The impact of initial soil moisture anomalies on subsequent precipitation is examined with the predictive vegetation phenology scheme disabled/enabled ("SM"/"SM_Veg" ensembles). The simulated climate differences between "SM" and "SM_Veg" ensembles represent the role of vegetation in soil moisture-vegetation- precipitation feedback. Experiments in this study focus on how the response of precipitation to initial soil moisture anomalies depends on their characteristics, including the timing, magnitude, spatial coverage and vertical depth, and further how it is modified by the interactive vegetation. Our results, for example, suggest that the impact of late spring soil moisture anomalies is not evident in subsequent precipitation until early summer when local convective precipitation dominates. With the summer wet soil moisture anomalies, vegetation tends to enhance the positive feedback between soil moisture and precipitation, while vegetation tends to suppress such positive feedback with the late spring anomalies. Second, the impact of vegetation feedback is investigated by driving the model with the inter-annually varying monthly SST (1983-1994). With the

  9. Sources of Popular Literature Online: New York Times Information Bank and the Magazine Index.

    Science.gov (United States)

    Kelly, Alex M.; Slade, Rod

    1979-01-01

    A comparison of the Magazine Index (MI) and the New York Times Information Bank (IB) showed the two data bases have little in common, mainly due to differences in focus, indexing, vocabulary, use online, and output. For business and government users, IB is the best choice; for more general and academic purposes, MI provides access to more…

  10. Dry deposition of radionuclides on leafy vegetables

    International Nuclear Information System (INIS)

    Heuberger, H.; Tschiersch, J.; Shinonaga, T.; Bunzl, K.; Pliml, A.; Dietl, F.; Keusch, M.

    2004-01-01

    The dry deposition of gaseous elemental radio-iodine and particulate radio-caesium on mature leafy vegetable was studied in chamber experiments. The simultaneous exposition of endive, head lettuce, red oak leaf lettuce and spinach (spring leafy vegetable) rsp. curly kale, white cabbage and spinach (summer leafy vegetable) was performed under homogeneous and controlled conditions. The sample collective of each species was such large that for the expected variation of the results a statistically firm analysis was possible. Significant differences were observed for the 131 I deposition on spring vegetable: the deposition on spinach was roughly 3times that on leaf lettuce, 4times that on endive and 9times that on head lettuce. For 134 Cs, there was no significant difference between spinach and leaf lettuce, about twice the amount was deposited on both species as on endive and 3times as on head lettuce. All summer vegetables showed differences in deposition. For lodine, the deposition on spinach was roughly 3times (6times) that on curly kale and 35times (100times) that on white cabbage in the 2 experiments. For caesium, the deposition to curly kale was highest, about twice that on spinach and 35times (80times) that on white cabbage. The deposition velocity could be estimated, in average it was about 8times higher for 131 I than for 134 Cs. The influence of the particle size on the deposition velocity was small in the considered size range. Washing could reduce the contamination by about 10% for 131 I and 45% for 134 Cs. (orig.)

  11. Heavy metals in intensive greenhouse vegetable production systems along Yellow Sea of China

    DEFF Research Database (Denmark)

    Hu, Wenyou; Huang, Biao; Tian, Kang

    2017-01-01

    Recently, greenhouse vegetable production (GVP) has grown rapidly and counts a large proportion of vegetable production in China. In this study, the accumulation, health risk and threshold values of selected heavy metals were evaluated systematically. A total of 120 paired soil and vegetable...... relatively high concentrations and transfer factors of heavy metals. The accumulation of heavy metals in soils was affected by soil pH and soil organic matter. The calculated hazard quotients (HQ) of the heavy metals by vegetable consumption decreased in the order of leafy > rootstalk > fruit vegetables...... with hazard index (HI) values of 0.61, 0.33 and 0.26, respectively. The HI values were all below 1, which indicates that there is a low risk of greenhouse vegetable consumption. Soil threshold values (STVs) of heavy metals in GVP system were established according to the health risk assessment. The relatively...

  12. Learning to eat vegetables in early life: the role of timing, age and individual eating traits.

    Directory of Open Access Journals (Sweden)

    Samantha J Caton

    Full Text Available Vegetable intake is generally low among children, who appear to be especially fussy during the pre-school years. Repeated exposure is known to enhance intake of a novel vegetable in early life but individual differences in response to familiarisation have emerged from recent studies. In order to understand the factors which predict different responses to repeated exposure, data from the same experiment conducted in three groups of children from three countries (n = 332 aged 4-38 m (18.9±9.9 m were combined and modelled. During the intervention period each child was given between 5 and 10 exposures to a novel vegetable (artichoke puree in one of three versions (basic, sweet or added energy. Intake of basic artichoke puree was measured both before and after the exposure period. Overall, younger children consumed more artichoke than older children. Four distinct patterns of eating behaviour during the exposure period were defined. Most children were "learners" (40% who increased intake over time. 21% consumed more than 75% of what was offered each time and were labelled "plate-clearers". 16% were considered "non-eaters" eating less than 10 g by the 5th exposure and the remainder were classified as "others" (23% since their pattern was highly variable. Age was a significant predictor of eating pattern, with older pre-school children more likely to be non-eaters. Plate-clearers had higher enjoyment of food and lower satiety responsiveness than non-eaters who scored highest on food fussiness. Children in the added energy condition showed the smallest change in intake over time, compared to those in the basic or sweetened artichoke condition. Clearly whilst repeated exposure familiarises children with a novel food, alternative strategies that focus on encouraging initial tastes of the target food might be needed for the fussier and older pre-school children.

  13. Combining vegetation index and model inversion methods for theextraction of key vegetation biophysical parameters using Terra and Aqua MODIS reflectance data

    DEFF Research Database (Denmark)

    Houborg, Rasmus Møller; Søgaard, Henrik; Bøgh, Eva

    2007-01-01

    for the inversion of a canopy reflectance model using Terra and Aqua MODIS multi-spectral, multi-temporal, and multi-angle reflectance observations to aid the determination of vegetation-specific physiological and structural canopy parameters. Land cover and site-specific inversion modeling was applied...

  14. Vegetation fire proneness in Europe

    Science.gov (United States)

    Pereira, Mário; Aranha, José; Amraoui, Malik

    2015-04-01

    Fire selectivity has been studied for vegetation classes in terms of fire frequency and fire size in a few European regions. This analysis is often performed along with other landscape variables such as topography, distance to roads and towns. These studies aims to assess the landscape sensitivity to forest fires in peri-urban areas and land cover changes, to define landscape management guidelines and policies based on the relationships between landscape and fires in the Mediterranean region. Therefore, the objectives of this study includes the: (i) analysis of the spatial and temporal variability statistics within Europe; and, (ii) the identification and characterization of the vegetated land cover classes affected by fires; and, (iii) to propose a fire proneness index. The datasets used in the present study comprises: Corine Land Cover (CLC) maps for 2000 and 2006 (CLC2000, CLC2006) and burned area (BA) perimeters, from 2000 to 2013 in Europe, provided by the European Forest Fire Information System (EFFIS). The CLC is a part of the European Commission programme to COoRdinate INformation on the Environment (Corine) and it provides consistent, reliable and comparable information on land cover across Europe. Both the CLC and EFFIS datasets were combined using geostatistics and Geographical Information System (GIS) techniques to access the spatial and temporal evolution of the types of shrubs and forest affected by fires. Obtained results confirms the usefulness and efficiency of the land cover classification scheme and fire proneness index which allows to quantify and to compare the propensity of vegetation classes and countries to fire. As expected, differences between northern and southern Europe are notorious in what concern to land cover distribution, fire incidence and fire proneness of vegetation cover classes. This work was supported by national funds by FCT - Portuguese Foundation for Science and Technology, under the project PEst-OE/AGR/UI4033/2014 and by

  15. Response of vegetation indices to changes in three measures of leaf water stress

    Science.gov (United States)

    Cohen, Warren B.

    1991-01-01

    The responses of vegetation indices to changes in water stress were evaluated in two separate laboratory experiments. In one experiment the normalized difference vegetation index (NDVI), the near-IR to red ratio (near-IR/red), the Infrared Index (II), and the Moisture Stress Index (MSI) were more highly correlated to leaf water potential in lodgepole pine branches than were the Leaf Water Content Index (LWCI), the mid-IR ratio (Mid-IR), or any of the single Thematic Mapper (TM) bands. In the other experiment, these six indices and the TM Tasseled Cap brightness, greenness, and wetness indices responded to changes in leaf relative water content (RWC) differently than they responded to changes in leaf water content (WC) of three plant species, and the responses were dependent on how experimental replicates were pooled. With no pooling, the LWCI was the most highly correlated index to both RWC and WC among replications, followed by the II, MSI, and wetness. Only the LWCI was highly correlated to RWC and WC when replications were pooled within species. With among species pooling the LWCI was the only index highly correlated with RWC, while the II, MSI, Mid-IR, and wetness were most highly correlated with WC.

  16. Environmental quality of a semi-natural area of the Po Valley (northern Italy): aspects of soil and vegetation.

    Science.gov (United States)

    Manfredi, Paolo; Giupponi, Luca; Cassinari, Chiara; Trevisan, Marco

    2014-05-01

    This work, originating in the preliminary analyses of a Life project and co-financed by the European Union ("Environmental recovery of degraded soils and desertified by a new treatment technology for land reconstruction", Life 10 ENV IT 400 "New Life"; http://www.lifeplusecosistemi.eu), aims to evaluate the environmental quality of a semi-natural area of the Po Valley (northern Italy) by analysing the characteristics of soil and vegetation. The area of study is located in the municipal territory of Piacenza (Emilia-Romagna, Italy) along the eastern shores of the river Trebbia and is made up of the closed landfill of Solid Urban Waste of Borgotrebbia (active from 1972 to 1985) and of the neighbouring areas (in North-South order: riverside area, northern borders of the landfill, landfill disposal, southern borders and cultivated corn fields). For each area pedological and vegetational analyses were carried out and in particular, as regards the soil, various chemical-physical analyses were done among which: pH, organic carbon, total nitrogen, salinity, exchangeable bases and granulometry. The ground vegetation data were collected using phytosociological relevés according to the method of the Zurich-Montpellier Sigmatist School, (Braun-Blanquet, 1964). For the analysis of the environmental quality of each area, the floristic-vegetation indexes system was applied as proposed by Taffetani & Rismondo (2009) (updated by Rismondo et al., 2011) conveniently created for analysing the ecological functionality of the agro-ecosystems. The results obtained by such applications drew attention to a dynamic vegetation mass in the landfill which, despite a value of the floristic biodiversity index (IFB) comparable to that of the borders, shows a much lower value of the maturity index (IM). This is due to the elevated percentage of annual species (index of the therophytic component = 52.78%) belonging to the phytosociological class Stellarietea mediae Tüxen, Lohmeyer & Preising ex

  17. Variation of MODIS reflectance and vegetation indices with viewing geometry and soybean development

    Directory of Open Access Journals (Sweden)

    Fábio M. Breunig

    2012-06-01

    Full Text Available Directional effects introduce a variability in reflectance and vegetation index determination, especially when large field-of-view sensors are used (e.g., Moderate Resolution Imaging Spectroradiometer - MODIS. In this study, we evaluated directional effects on MODIS reflectance and four vegetation indices (Normalized Difference Vegetation Index - NDVI; Enhanced Vegetation Index - EVI; Normalized Difference Water Index - NDWI1640 and NDWI2120 with the soybean development in two growing seasons (2004-2005 and 2005-2006. To keep the reproductive stage for a given cultivar as a constant factor while varying viewing geometry, pairs of images obtained in close dates and opposite view angles were analyzed. By using a non-parametric statistics with bootstrapping and by normalizing these indices for angular differences among viewing directions, their sensitivities to directional effects were studied. Results showed that the variation in MODIS reflectance between consecutive phenological stages was generally smaller than that resultant from viewing geometry for closed canopies. The contrary was observed for incomplete canopies. The reflectance of the first seven MODIS bands was higher in the backscattering. Except for the EVI, the other vegetation indices had larger values in the forward scattering direction. Directional effects decreased with canopy closure. The NDVI was lesser affected by directional effects than the other indices, presenting the smallest differences between viewing directions for fixed phenological stages.Efeitos direcionais introduzem variabilidade na reflectância e na determinação de índices de vegetação, especialmente quando sensores de amplo campo de visada são usados (p.ex., Moderate Resolution Imaging Spectroradiometer - MODIS. Neste estudo, nós avaliamos os efeitos direcionais sobre a reflectância e quatro índices de vegetação (Normalized Difference Vegetation Index - NDVI; Enhanced Vegetation Index - EVI; Normalized

  18. Assessing the risks of trace elements in environmental materials under selected greenhouse vegetable production systems of China

    International Nuclear Information System (INIS)

    Chen, Yong; Huang, Biao; Hu, Wenyou; Weindorf, David C.; Liu, Xiaoxiao; Niedermann, Silvana

    2014-01-01

    The risk assessment of trace elements of different environmental media in conventional and organic greenhouse vegetable production systems (CGVPS and OGVPS) can reveal the influence of different farming philosophy on the trace element accumulations and their effects on human health. These provide important basic data for the environmental protection and human health. This paper presents trace element accumulation characteristics of different land uses; reveals the difference of soil trace element accumulation both with and without consideration of background levels; compares the trace element uptake by main vegetables; and assesses the trace element risks of soils, vegetables, waters and agricultural inputs, using two selected greenhouse vegetable systems in Nanjing, China as examples. Results showed that greenhouse vegetable fields contained significant accumulations of Zn in CGVPS relative to rice–wheat rotation fields, open vegetable fields, and geochemical background levels, and this was the case for organic matter in OGVPS. The comparative analysis of the soil medium in two systems with consideration of geochemical background levels and evaluation of the geo-accumulation pollution index achieved a more reasonable comparison and accurate assessment relative to the direct comparison analysis and the evaluation of the Nemerow pollution index, respectively. According to the Chinese food safety standards and the value of the target hazard quotient or hazard index, trace element contents of vegetables were safe for local residents in both systems. However, the spatial distribution of the estimated hazard index for producers still presented certain specific hotspots which may cause potential risk for human health in CGVPS. The water was mainly influenced by nitrogen, especially for CGVPS, while the potential risk of Cd and Cu pollution came from sediments in OGVPS. The main inputs for trace elements were fertilizers which were relatively safe based on relevant

  19. Assessing the risks of trace elements in environmental materials under selected greenhouse vegetable production systems of China

    Energy Technology Data Exchange (ETDEWEB)

    Chen, Yong [Key Laboratory of Soil Environment and Pollution Remediation, Institute of Soil Science, Chinese Academy of Sciences, Nanjing 210008 (China); University of Chinese Academy of Sciences, Beijing 100049 (China); Huang, Biao, E-mail: bhuang@issas.ac.cn [Key Laboratory of Soil Environment and Pollution Remediation, Institute of Soil Science, Chinese Academy of Sciences, Nanjing 210008 (China); University of Chinese Academy of Sciences, Beijing 100049 (China); Hu, Wenyou [Key Laboratory of Soil Environment and Pollution Remediation, Institute of Soil Science, Chinese Academy of Sciences, Nanjing 210008 (China); University of Chinese Academy of Sciences, Beijing 100049 (China); Weindorf, David C.; Liu, Xiaoxiao [Department of Plant and Soil Science, Texas Tech University, Lubbock, TX (United States); Niedermann, Silvana [Department of Environmental Systems Science, Institute of Agricultural Science, ETH Zurich, 8092 Zurich (Switzerland)

    2014-02-01

    The risk assessment of trace elements of different environmental media in conventional and organic greenhouse vegetable production systems (CGVPS and OGVPS) can reveal the influence of different farming philosophy on the trace element accumulations and their effects on human health. These provide important basic data for the environmental protection and human health. This paper presents trace element accumulation characteristics of different land uses; reveals the difference of soil trace element accumulation both with and without consideration of background levels; compares the trace element uptake by main vegetables; and assesses the trace element risks of soils, vegetables, waters and agricultural inputs, using two selected greenhouse vegetable systems in Nanjing, China as examples. Results showed that greenhouse vegetable fields contained significant accumulations of Zn in CGVPS relative to rice–wheat rotation fields, open vegetable fields, and geochemical background levels, and this was the case for organic matter in OGVPS. The comparative analysis of the soil medium in two systems with consideration of geochemical background levels and evaluation of the geo-accumulation pollution index achieved a more reasonable comparison and accurate assessment relative to the direct comparison analysis and the evaluation of the Nemerow pollution index, respectively. According to the Chinese food safety standards and the value of the target hazard quotient or hazard index, trace element contents of vegetables were safe for local residents in both systems. However, the spatial distribution of the estimated hazard index for producers still presented certain specific hotspots which may cause potential risk for human health in CGVPS. The water was mainly influenced by nitrogen, especially for CGVPS, while the potential risk of Cd and Cu pollution came from sediments in OGVPS. The main inputs for trace elements were fertilizers which were relatively safe based on relevant

  20. Spatial Modeling of Urban Vegetation and Land Surface Temperature: A Case Study of Beijing

    Directory of Open Access Journals (Sweden)

    Chudong Huang

    2015-07-01

    Full Text Available The coupling relationship between urban vegetation and land surface temperature (LST has been heatedly debated in a variety of environmental studies. This paper studies the urban vegetation information and LST by utilizing a series of remote sensing imagery covering the period from 1990 to 2007. Their coupling relationship is analyzed, in order to provide the basis for ecological planning and environment protection. The results show that the normalized difference vegetation index (NDVI, urban vegetation abundance (UVA and urban forest abundance (UFA are negatively correlated with LST, which means that both urban vegetation and urban forest are capable in decreasing LST. The apparent influence of urban vegetation and urban forest on LST varies with the spatial resolution of the imagery, and peaks at the resolutions ranging from 90 m to 120 m.

  1. Impact of 3D Canopy Structure on Remote Sensing Vegetation Index and Solar Induced Chlorophyll Fluorescence

    Science.gov (United States)

    Zeng, Y.; Berry, J. A.; Jing, L.; Qinhuo, L.

    2017-12-01

    Terrestrial ecosystem plays a critical role in removing CO2 from atmosphere by photosynthesis. Remote sensing provides a possible way to monitor the Gross Primary Production (GPP) at the global scale. Vegetation Indices (VI), e.g., NDVI and NIRv, and Solar Induced Fluorescence (SIF) have been widely used as a proxy for GPP, while the impact of 3D canopy structure on VI and SIF has not be comprehensively studied yet. In this research, firstly, a unified radiative transfer model for visible/near-infrared reflectance and solar induced chlorophyll fluorescence has been developed based on recollision probability and directional escape probability. Then, the impact of view angles, solar angles, weather conditions, leaf area index, and multi-layer leaf angle distribution (LAD) on VI and SIF has been studied. Results suggest that canopy structure plays a critical role in distorting pixel-scale remote sensing signal from leaf-scale scattering. In thin canopy, LAD affects both of the remote sensing estimated GPP and real GPP, while in dense canopy, SIF variations are mainly due to canopy structure, instead of just due to physiology. At the microscale, leaf angle reflects the plant strategy to light on the photosynthesis efficiency, and at the macroscale, a priori knowledge of leaf angle distribution for specific species can improve the global GPP estimation by remote sensing.

  2. Development of a Healthy Eating Index for patients with type 2 diabetes

    Directory of Open Access Journals (Sweden)

    Juliana Peçanha ANTONIO

    2015-10-01

    Full Text Available Objective:This study sought to develop a dietary index for assessment of diet quality aiming for compliance with dietary recommendations for diabetes: The Diabetes Healthy Eating Index.Methods:Cross-sectional study with 201 outpatients with type 2 diabetes (61.4±9.7 years of age; 72.1% were overweight; 12.1±7.7 years of diagnosis; 7.3±1.3% mean HbA1c. Clinical and laboratory evaluations were performed together with 3-day weight diet records. The dietary index developed included 10 components: "diet variety", "fresh fruits", "vegetables", "carbohydrates and fiber sources", "meats and eggs", "dairy products and saturated fatty acids", "oils and fats", "total lipids", "cholesterol", and "transunsaturated fatty acids". The performance of each component was evaluated using the Item Response Theory, and diet quality was scored from 0-100%.Results:Overall, diet quality in this sample was 39.8±14.3% (95%CI=37.8-41.8%, and only 55 patients had a total diet quality score >50%. Good compliance was observed in only four index components: "total lipids", "variety", "fiber sources", and "dairy and saturated fatty acids". The components that differentiated patients with poor dietary quality from those with good dietary quality were "vegetables", "diet variety", "dairy and saturated fatty acids" and "total lipids". The greatest determinants of dietary quality were the components "diet variety", "vegetables", and "total lipids".Conclusion:This dietary index proposed assesses diet quality in compliance with the specific nutritional recommendations for diabetes. In clinical practice, this novel index may be a useful tool for the assessment and management of diet of patients with type 2 diabetes.

  3. Analysis of regional vegetation changes with medium and high resolution imagery

    Science.gov (United States)

    Marcello, J.; Eugenio, F.; Medina, A.

    2012-09-01

    The singular characteristics of the Canarian archipelago (Spain) and, in particular, of the Gran Canaria island have allowed the development of a unique biological richness. Almost half of its territory is protected to preserve the natural environment and, in consequence, the monitoring of vegetated regions plays an important role for regional administrations which aim to develop the corresponding policies for the conservation of such ecosystems. The Normalized Difference Vegetation Index (NDVI) is a common index applied for vegetation studies. It is important to emphasize that NDVI is sensor-dependent, and changes are affected by soil background, irradiance, solar position, atmospheric attenuation, season, hydric situation and climate of the area. So, a fixed threshold cannot be set, even for the same sensor or season, to properly segment vegetated areas. In this context, a robust methodology has been applied to ensure a reliable estimation of changes using the same sensor in multiple dates or different sensors. To that respect, a supervised procedure is presented consisting on the selection of different regions within each image to precisely map each cover with its associated NDVI values and, in consequence, obtain for each individual image the optimal threshold to properly segment vegetation without the need to perform the complex preprocessing required to estimate the ground reflectivity. On the other hand, fires are an important aspect of an ecosystem and their study, a fundamental task to perform a complete assessment of the environmental and economic damage. In our work we have also analyzed in detail the fire occurring during 2007 and precisely assessed the results.

  4. Global vegetation change predicted by the modified Budyko model

    Energy Technology Data Exchange (ETDEWEB)

    Monserud, R.A.; Tchebakova, N.M.; Leemans, R. (US Department of Agriculture, Moscow, ID (United States). Intermountain Research Station, Forest Service)

    1993-09-01

    A modified Budyko global vegetation model is used to predict changes in global vegetation patterns resulting from climate change (CO[sub 2] doubling). Vegetation patterns are predicted using a model based on a dryness index and potential evaporation determined by solving radiation balance equations. Climate change scenarios are derived from predictions from four General Circulation Models (GCM's) of the atmosphere (GFDL, GISS, OSU, and UKMO). All four GCM scenarios show similar trends in vegetation shifts and in areas that remain stable, although the UKMO scenario predicts greater warming than the others. Climate change maps produced by all four GCM scenarios show good agreement with the current climate vegetation map for the globe as a whole, although over half of the vegetation classes show only poor to fair agreement. The most stable areas are Desert and Ice/Polar Desert. Because most of the predicted warming is concentrated in the Boreal and Temperate zones, vegetation there is predicted to undergo the greatest change. Most vegetation classes in the Subtropics and Tropics are predicted to expand. Any shift in the Tropics favouring either Forest over Savanna, or vice versa, will be determined by the magnitude of the increased precipitation accompanying global warming. Although the model predicts equilibrium conditions to which many plant species cannot adjust (through migration or microevolution) in the 50-100 y needed for CO[sub 2] doubling, it is not clear if projected global warming will result in drastic or benign vegetation change. 72 refs., 3 figs., 3 tabs.

  5. Spatial mapping of leaf area index using hyperspectral remote sensing for hydrological applications with a particular focus on canopy interception

    Directory of Open Access Journals (Sweden)

    H. H. Bulcock

    2010-02-01

    Full Text Available The establishment of commercial forestry plantations in natural grassland vegetation, results in increased transpiration and interception which in turn, results in a streamflow reduction. Methods to quantify this impact typically require LAI as an input into the various equations and process models that are applied. The use of remote sensing technology as a tool to estimate leaf area index (LAI for use in estimating canopy interception is described in this paper. Remote sensing provides a potential solution to effectively monitor the spatial and temporal variability of LAI. This is illustrated using Hyperion hyperspectral imagery and three vegetation indices, namely the normalized difference vegetation index (NDVI, soil adjusted vegetation index (SAVI and Vogelmann index 1 to estimate LAI in a catchment afforested with Eucalyptus, Pinus and Acacia genera in the KwaZulu-Natal midlands of South Africa. Of the three vegetation indices used in this study, it was found that the Vogelmann index 1 was the most robust index with an R2 and root mean square error (RMSE values of 0.7 and 0.3 respectively. However, both NDVI and SAVI could be used to estimate the LAI of 12 year old Pinus patula accurately. If the interception component is to be quantified independently, estimates of maximum storage capacity and canopy interception are required. Thus, the spatial distribution of LAI in the catchment is used to estimate maximum canopy storage capacity in the study area.

  6. Derivation of global vegetation biophysical parameters from EUMETSAT Polar System

    Science.gov (United States)

    García-Haro, Francisco Javier; Campos-Taberner, Manuel; Muñoz-Marí, Jordi; Laparra, Valero; Camacho, Fernando; Sánchez-Zapero, Jorge; Camps-Valls, Gustau

    2018-05-01

    This paper presents the algorithm developed in LSA-SAF (Satellite Application Facility for Land Surface Analysis) for the derivation of global vegetation parameters from the AVHRR (Advanced Very High Resolution Radiometer) sensor on board MetOp (Meteorological-Operational) satellites forming the EUMETSAT (European Organization for the Exploitation of Meteorological Satellites) Polar System (EPS). The suite of LSA-SAF EPS vegetation products includes the leaf area index (LAI), the fractional vegetation cover (FVC), and the fraction of absorbed photosynthetically active radiation (FAPAR). LAI, FAPAR, and FVC characterize the structure and the functioning of vegetation and are key parameters for a wide range of land-biosphere applications. The algorithm is based on a hybrid approach that blends the generalization capabilities offered by physical radiative transfer models with the accuracy and computational efficiency of machine learning methods. One major feature is the implementation of multi-output retrieval methods able to jointly and more consistently estimate all the biophysical parameters at the same time. We propose a multi-output Gaussian process regression (GPRmulti), which outperforms other considered methods over PROSAIL (coupling of PROSPECT and SAIL (Scattering by Arbitrary Inclined Leaves) radiative transfer models) EPS simulations. The global EPS products include uncertainty estimates taking into account the uncertainty captured by the retrieval method and input errors propagation. A sensitivity analysis is performed to assess several sources of uncertainties in retrievals and maximize the positive impact of modeling the noise in training simulations. The paper discusses initial validation studies and provides details about the characteristics and overall quality of the products, which can be of interest to assist the successful use of the data by a broad user's community. The consistent generation and distribution of the EPS vegetation products will

  7. Groundwater dependant vegetation identified by remote sensing in the Iberian Peninsula

    Science.gov (United States)

    Gouveia, Célia; Pascoa, Patrícia; Kurz-Besson, Cathy

    2017-04-01

    Groundwater Dependant Ecosystems (GDEs) are defined as ecosystems whose composition, structure, and function depend on the water supplies from groundwater aquifers. Within GDEs, phreatophytes are terrestrial plants relying on groundwater through deep rooting. They can be found worldwide but are mostly adapted to environments facing scarce water availability or recurrent drought periods mainly in semi-arid to arid climate geographical areas, such as the Mediterranean basin. We present a map of the potential distribution of GDEs over the Iberian Peninsula (IP) obtained by remote sensing and identifying hotspots corresponding to the most vulnerable areas for rainfed vegetation facing the risk of desertification. The characterization of GDEs was assessed by remote sensing (RS), using CORINE land-cover information and the Normalized Difference Vegetation Index (NDVI) from VEGETATION recorded between 1998 and 2014 with a resolution of 1km. The methodology based on Gou et al (2015) relied on three approaches to map GDEs over the IP by: i) Detecting vegetation remaining green during the dry periods, since GDEs are more likely to show high NDVI values during summer of dry years; ii) Spotting vegetation with low seasonal changes since GDEs are more prone to have the lowest NDVI standard deviation along an entire year, and iii) Discriminating vegetation with low inter-annual variability since GDEs areas should provide the lowest NDVI changes between extreme wet and dry years. A geospatial analysis was performed to gather the potential area of GDEs (obtained with NDVI), vegetation land cover types (CORINE land cover) and climatic variables (temperature, precipitation and the Standardized Precipitation-Evapotranspiration Index SPEI). This analysis allowed the identification of hotspots of the most vulnerable areas for rainfed vegetation regarding water scarcity over the Iberian Peninsula, where protection measures should be urgently applied to sustain rainfed ecosystem and agro

  8. Vegetation dynamic characteristics and its responses to climate change in Jinghe River watershed of Loess Plateau, China

    Science.gov (United States)

    Chang, F.; Liu, W.; Zhou, H.; Ning, T.; Wang, Y.

    2017-12-01

    The Jinghe River is a second-order tributary of the Yellow River, and located in the middle-south part of the Loess Plateau. The watershed area is 45421km², with the mean annual precipitation (P) being about 508mm and aridity index 2.09. For a long time, soil and water loss in this watershed is severe, resulting in very fragile ecological environment. The GIMMS-normalized vegetation index NDVI is used to reflect condition of vegetation cover, and P and Penman potential evapotranspiration (ET) to represent climate water and heat conditions. The annual actual ET is estimated as the difference between P and runoff (ignoring the change of watershed water storage during each hydrological year, May to April of the following year). These concepts were introduced to discuss the dynamic characteristics of vegetation cover and its response to climate change. Results showed that the mean annual NDVI value was 0.51, showing a stable increasing trend from 2000 with an annual increasing rate of 8.7×10¯³. This result is consistent with the implementation of the project that converts farmland to forests and grassland and has achieved remarkable success in the Loess Plateau since 1999. It also indicates that the positive impact of human activity has been strengthened under the background of climate change. From 1982 to 2012, the annual actual ET was 464mm, accounting for 93.6% of annual P over the same period. The NDVI value of main growing season (5-9 months) is significantly correlated with annual P and annual humid index (ratio of annual P to annual potential ET). Vegetation water consumption is the main part of land surface ET, and the relationship between annual actual ET and NDVI value over the same period is also significant. The NDVI value, P and potential ET variation varied substantially within the Jinghe River watershed, and their relationships in different regions at an inter-annual scale are different. Currently, we are investigating the influence of the changes in

  9. Study Of The Physicochemical Analysis Of Biodiesel Produced From Waste Vegetable Oil.

    Directory of Open Access Journals (Sweden)

    C. O. Okpanachi

    2017-07-01

    Full Text Available The study of the physicochemical analysis of biodiesel produced from waste vegetable oil in Sedi Minna Nigeria was carried out in order to ascertain the quality of the biodiesel produced as regards physical and chemical parameters which include visual appearance colour cloud point flash point and cetane index diesel index kinematic velocity calorific value. Biodiesel is a renewable resource that can replace petroleum diesel which comes from fossil fuels that are limited and will be exhausted in the near future. Biodiesel can be made from the transesterification of vegetable oils animal fat greases and oil crops such as soybean and it is biodegradable. The biodiesel produced was subjected to physicochemical analysis and results of cetane index was established to be 52 the flash point using pensky martens close cup was determine to be 1600C diesel index using IP21 0.3411 kinematic viscosity at 400C to be 4.12 and calorific value of 10867calg. The investigated physicochemical parameters show that the biodiesel produced is suitable for use in diesel engines without modifications and is cheaper to produce compared to petroleum diesel.

  10. Detecting land-cover change using mappable vegetation related indices: A case study from Sinharaja Man and the Biosphere Reserve

    Directory of Open Access Journals (Sweden)

    BD Madurapperuma

    2014-06-01

    Full Text Available This study evaluates multi-year changes of vegetation in the Sinharaja Man and the Biosphere (MAB reserve using mappable vegetation related indices viz., Normalized Difference Vegetation Index (NDVI and Burn Index (BI. Land-cover changes in the Sinharaja MAB reserve were detected using Landsat 7 ETM+ images for 1993, 2001, and 2005. Seven individual bands of each image were converted to new multiband files by layer stacking using ENVI® 4.5. Then the multiband files were re-projected to UTM Zone 44 North, WGS-84 Datum. Each data set was exported to ENVI® EX software package to detect the changes between time steps based on NDVI and BI using an image difference tool. Land-cover data, which were obtained from the DIVA GIS web portal, were compared with Landsat image data. Results of BI showed that the Sinharaja MAB reserve fringe was vulnerable to forest fire. For example, from 1993- 2001, 160 ha identified as burned area. In contrast, from 2001-2005, 79 ha burned, and for the entire period of 1993-2005, 10 ha burned. NDVI resulted in a 962 ha increase of vegetation prime at the western Sinharaja from 2001-2005. In addition, there was a 15 ha decrease in vegetation from 1993-2005. The results were visualized using an embedded 3D render window of Google Earth and 2D view of ArcGIS explorer online. In conclusion, in-situ ground truthing data is needed for the fire-influenced area for implementing sustainable forest resource management at the Sinharaja MAB reserve. Normal 0 false false false EN-GB X-NONE X-NONE

  11. Assessment of vegetation trends in drylands from time series of earth observation data

    NARCIS (Netherlands)

    Fensholt, R.; Horion, S.; Tagesson, T.; Ehammer, A.; Grogan, K.; Tian, F.; Huber, S.; Verbesselt, J.; Prince, S.D.; Tucker, C.J.; Rasmussen, K.

    2015-01-01

    This chapter summarizes approaches to the detection of dryland vegetation change and methods for observing spatio-temporal trends from space. An overview of suitable long-term Earth Observation (EO) based datasets for assessment of global dryland vegetation trends is provided and a status map of

  12. A critical note on the IAGA-endorsed Polar Cap (PC) indices: excessive excursions in the real-time index values

    Science.gov (United States)

    Stauning, Peter

    2018-04-01

    The Polar Cap (PC) indices were approved by the International Association for Geomagnetism and Aeronomy (IAGA) in 2013 and made available at the web portal http://pcindex.org" target="_blank">http://pcindex.org holding prompt (real-time) as well as archival index values. The present note provides the first reported examination of the validity of the IAGA-endorsed method to generate real-time PC index values. It is demonstrated that features of the derivation procedure defined by Janzhura and Troshichev (2011) may cause considerable excursions in the real-time PC index values compared to the final index values. In examples based on occasional downloads of index values, the differences between real-time and final values of PC indices were found to exceed 3 mV m-1, which is a magnitude level that may indicate (or hide) strong magnetic storm activity.

  13. Detection of chlorophyll and leaf area index dynamics from sub-weekly hyperspectral imagery

    KAUST Repository

    Houborg, Rasmus; McCabe, Matthew; Angel, Yoseline; Middleton, Elizabeth M.

    2016-01-01

    Temporally rich hyperspectral time-series can provide unique time critical information on within-field variations in vegetation health and distribution needed by farmers to effectively optimize crop production. In this study, a dense timeseries of images were acquired from the Earth Observing-1 (EO-1) Hyperion sensor over an intensive farming area in the center of Saudi Arabia. After correction for atmospheric effects, optimal links between carefully selected explanatory hyperspectral vegetation indices and target vegetation characteristics were established using a machine learning approach. A dataset of in-situ measured leaf chlorophyll (Chll) and leaf area index (LAI), collected during five intensive field campaigns over a variety of crop types, were used to train the rule-based predictive models. The ability of the narrow-band hyperspectral reflectance information to robustly assess and discriminate dynamics in foliar biochemistry and biomass through empirical relationships were investigated. This also involved evaluations of the generalization and reproducibility of the predictions beyond the conditions of the training dataset. The very high temporal resolution of the satellite retrievals constituted a specifically intriguing feature that facilitated detection of total canopy Chl and LAI dynamics down to sub-weekly intervals. The study advocates the benefits associated with the availability of optimum spectral and temporal resolution spaceborne observations for agricultural management purposes.

  14. Detection of chlorophyll and leaf area index dynamics from sub-weekly hyperspectral imagery

    KAUST Repository

    Houborg, Rasmus

    2016-10-25

    Temporally rich hyperspectral time-series can provide unique time critical information on within-field variations in vegetation health and distribution needed by farmers to effectively optimize crop production. In this study, a dense timeseries of images were acquired from the Earth Observing-1 (EO-1) Hyperion sensor over an intensive farming area in the center of Saudi Arabia. After correction for atmospheric effects, optimal links between carefully selected explanatory hyperspectral vegetation indices and target vegetation characteristics were established using a machine learning approach. A dataset of in-situ measured leaf chlorophyll (Chll) and leaf area index (LAI), collected during five intensive field campaigns over a variety of crop types, were used to train the rule-based predictive models. The ability of the narrow-band hyperspectral reflectance information to robustly assess and discriminate dynamics in foliar biochemistry and biomass through empirical relationships were investigated. This also involved evaluations of the generalization and reproducibility of the predictions beyond the conditions of the training dataset. The very high temporal resolution of the satellite retrievals constituted a specifically intriguing feature that facilitated detection of total canopy Chl and LAI dynamics down to sub-weekly intervals. The study advocates the benefits associated with the availability of optimum spectral and temporal resolution spaceborne observations for agricultural management purposes.

  15. Dietary Patterns and Body Mass Index in Children with Autism and Typically Developing Children

    Science.gov (United States)

    Evans, E. Whitney; Must, Aviva; Anderson, Sarah E.; Curtin, Carol; Scampini, Renee; Maslin, Melissa; Bandini, Linda

    2012-01-01

    To determine whether dietary patterns (juice and sweetened non-dairy beverages, fruits, vegetables, fruits and vegetables, snack foods, and kid's meals) and associations between dietary patterns and body mass index (BMI) differed between 53 children with autism spectrum disorders (ASD) and 58 typically developing children, ages 3-11, multivariate…

  16. A new multiscale approach for monitoring vegetation using remote sensing-based indicators in laboratory, field, and landscape.

    Science.gov (United States)

    Lausch, Angela; Pause, Marion; Merbach, Ines; Zacharias, Steffen; Doktor, Daniel; Volk, Martin; Seppelt, Ralf

    2013-02-01

    Remote sensing is an important tool for studying patterns in surface processes on different spatiotemporal scales. However, differences in the spatiospectral and temporal resolution of remote sensing data as well as sensor-specific surveying characteristics very often hinder comparative analyses and effective up- and downscaling analyses. This paper presents a new methodical framework for combining hyperspectral remote sensing data on different spatial and temporal scales. We demonstrate the potential of using the "One Sensor at Different Scales" (OSADIS) approach for the laboratory (plot), field (local), and landscape (regional) scales. By implementing the OSADIS approach, we are able (1) to develop suitable stress-controlled vegetation indices for selected variables such as the Leaf Area Index (LAI), chlorophyll, photosynthesis, water content, nutrient content, etc. over a whole vegetation period. Focused laboratory monitoring can help to document additive and counteractive factors and processes of the vegetation and to correctly interpret their spectral response; (2) to transfer the models obtained to the landscape level; (3) to record imaging hyperspectral information on different spatial scales, achieving a true comparison of the structure and process results; (4) to minimize existing errors from geometrical, spectral, and temporal effects due to sensor- and time-specific differences; and (5) to carry out a realistic top- and downscaling by determining scale-dependent correction factors and transfer functions. The first results of OSADIS experiments are provided by controlled whole vegetation experiments on barley under water stress on the plot scale to model LAI using the vegetation indices Normalized Difference Vegetation Index (NDVI) and green NDVI (GNDVI). The regression model ascertained from imaging hyperspectral AISA-EAGLE/HAWK (DUAL) data was used to model LAI. This was done by using the vegetation index GNDVI with an R (2) of 0.83, which was

  17. Consumption of fruits and vegetables and probabilistic assessment of the cumulative acute exposure to organophosphorus and carbamate pesticides of schoolchildren in Slovenia.

    Science.gov (United States)

    Blaznik, Urška; Yngve, Agneta; Eržen, Ivan; Hlastan Ribič, Cirila

    2016-02-01

    Adequate consumption of fruits and vegetables is a part of recommendations for a healthy diet. The aim of the present study was to assess acute cumulative dietary exposure to organophosphorus and carbamate pesticides via fruit and vegetable consumption by the population of schoolchildren aged 11-12 years and the level of risk for their health. Cumulative probabilistic risk assessment methodology with the index compound approach was applied. Slovenia, primary schools. Schoolchildren (n 1145) from thirty-one primary schools in Slovenia. Children were part of the PRO GREENS study 2009/10 which assessed 11-year-olds' consumption of fruit and vegetables in ten European countries. The cumulative acute exposure amounted to 8.3 (95% CI 7.7, 10.6) % of the acute reference dose (ARfD) for acephate as index compound (100 µg/kg body weight per d) at the 99.9th percentile for daily intake and to 4.5 (95% CI 3.5, 4.7) % of the ARfD at the 99.9th percentile for intakes during school time and at lunch. Apples, bananas, oranges and lettuce contributed most to the total acute pesticides intake. The estimations showed that acute dietary exposure to organophosphorus and carbamate pesticides is not a health concern for schoolchildren with the assessed dietary patterns of fruit and vegetable consumption.

  18. Analysis of vegetation dynamics using time-series vegetation index data from Earth observation satellites

    Science.gov (United States)

    Rodrigues, Arlete da Silva

    As piroxenas sao um vasto grupo de silicatos minerais encontrados em muitas rochas igneas e metamorficas. Na sua forma mais simples, estes silicatos sao constituidas por cadeias de SiO3 ligando grupos tetrahedricos de SiO4. A formula quimica geral das piroxenas e M2M1T2O6, onde M2 se refere a catioes geralmente em uma coordenacao octaedrica distorcida (Mg2+, Fe2+, Mn2+, Li+, Ca2+, Na+), M1 refere-se a catioes numa coordenacao octaedrica regular (Al3+, Fe3+, Ti4+, Cr3+, V3+, Ti3+, Zr4+, Sc3+, Zn2+, Mg2+, Fe2+, Mn2+), e T a catioes em coordenacao tetrahedrica (Si4+, Al3+, Fe3+). As piroxenas com estrutura monoclinica sao designadas de clinopiroxenes. A estabilidade das clinopyroxenes num espectro de composicoes quimicas amplo, em conjugacao com a possibilidade de ajustar as suas propriedades fisicas e quimicas e a durabilidade quimica, tem gerado um interesse mundial devido a suas aplicacoes em ciencia e tecnologia de materiais. Este trabalho trata do desenvolvimento de vidros e de vitro-cerâmicos baseadas de clinopiroxenas para aplicacoes funcionais. O estudo teve objectivos cientificos e tecnologicos; nomeadamente, adquirir conhecimentos fundamentais sobre a formacao de fases cristalinas e solucoes solidas em determinados sistemas vitro-cerâmicos, e avaliar a viabilidade de aplicacao dos novos materiais em diferentes areas tecnologicas, com especial enfase sobre a selagem em celulas de combustivel de oxido solido (SOFC). Com este intuito, prepararam-se varios vidros e materiais vitro-cerâmicos ao longo das juntas Enstatite (MgSiO3) - diopsidio (CaMgSi2O6) e diopsidio (CaMgSi2O6) - Ca - Tschermak (CaAlSi2O6), os quais foram caracterizados atraves de um vasto leque de tecnicas. Todos os vidros foram preparados por fusao-arrefecimento enquanto os vitro-cerâmicos foram obtidos quer por sinterizacao e cristalizacao de fritas, quer por nucleacao e cristalizacao de vidros monoliticos. Estudaram-se ainda os efeitos de varias substituicoes ionicas em composicoes de diopsidio contendo Al na estrutura, sinterizacao e no comportamento durante a cristalizacao de vidros e nas propriedades dos materiais vitro-cerâmicos, com relevância para a sua aplicacao como selantes em SOFC. Verificou-se que Foi observado que os vidros/vitro-cerâmicos a base de enstatite nao apresentavam as caracteristicas necessarias para serem usados como materiais selantes em SOFC, enquanto as melhores propriedades apresentadas pelos vitro-cerâmicos a base de diopsidio qualificaram-nos para futuros estudos neste tipo de aplicacoes. Para alem de investigar a adequacao dos vitro-cerâmicos a base de clinopyroxene como selantes, esta tese tem tambem como objetivo estudar a influencia dos agentes de nucleacao na nucleacao em volume dos vitro-cerâmicos resultantes a base de diopsidio, de modo a qualifica-los como potenciais materiais hopedeiros de residuos nucleares radioactivos.

  19. Use of middle infrared radiation to estimate the leaf area index of a boreal forest

    Energy Technology Data Exchange (ETDEWEB)

    Boyd, D.S. [Kingston Univ., Surrey (United Kingdom). Centre for Earth and Environmental Science Research, School of Geography; Wicks, T. E.; Curran, P.J. [Southampton Univ., Southampton, Hampshire (United Kingdom). Dept. of Geography

    2000-06-01

    Reflected radiation recorded by satellite sensors is a common procedure to estimate the leaf area index (LAI) of boreal forest. The normalized difference vegetation index (NDVI), derived from measurements of visible and near infrared radiation were commonly used to estimate LAI. But research in tropical forest has shown that LAI is more closely related to radiation of middle infrared wavelengths than that of visible wavelengths. This research calculated a vegetation index (VI3) using radiation from vegetation recorded at near and middle infrared wavelengths. In the case of boreal forest, VI3 and LAI displayed a closer relationship than NDVI and LAI. Also, the use of VI3 explained approximately 76 per cent of the variation in field estimates of LAI, versus approximately 46 per cent for NDVI. The authors concluded that consideration should be given to information provided by middle infrared radiation to estimate the leaf area index of boreal forest. The research area was located in the Southern Study Area (SSA) of the BOReal Ecosystem-Atmospher Study (BOREAS), situated on the southern edge of the Canadian boreal forest, 40 km north of Prince Albert, Saskatchewan. 1 tab., 4 figs., 46 refs.

  20. Development and Interpretation of New Sediment Rating Curve Considering the Effect of Vegetation Cover for Asian Basins

    Directory of Open Access Journals (Sweden)

    Jie Wang

    2013-01-01

    Full Text Available Suspended sediment concentration of a river can provide very important perspective on erosion or soil loss of one river basin ecosystem. The changes of land use and land cover, such as deforestation or afforestation, affect sediment yield process of a catchment through changing the hydrological cycle of the area. A sediment rating curve can describe the average relation between discharge and suspended sediment concentration for a certain location. However, the sediment load of a river is likely to be undersimulated from water discharge using least squares regression of log-transformed variables and the sediment rating curve does not consider temporal changes of vegetation cover. The Normalized Difference Vegetation Index (NDVI can well be used to analyze the status of the vegetation cover well. Thus long time monthly NDVI data was used to detect vegetation change in the past 19 years in this study. Then monthly suspended sediment concentration and discharge from 1988 to 2006 in Laichau station were used to develop one new sediment rating curve and were validated in other Asian basins. The new sediment model can describe the relationship among sediment yield, streamflow, and vegetation cover, which can be the basis for soil conservation and sustainable ecosystem management.

  1. The effect of cooking on the phytochemical content of vegetables

    NARCIS (Netherlands)

    Palermo, M.; Pellegrini, N.; Fogliano, V.

    2014-01-01

    Cooking induces many chemical and physical modifications in foods; among these the phytochemical content can change. Many authors have studied variations in vegetable nutrients after cooking, and great variability in the data has been reported. In this review more than 100 articles from indexed

  2. Evaluation of the data of vegetable covering using fraction images and multitemporal vegetation index, derived of orbital data of moderate resolution of the sensor MODIS

    International Nuclear Information System (INIS)

    Murillo Mejia, Mario Humberto

    2006-01-01

    The objective was to evaluate the data obtained by sensor MODIS onboard the EOS terra satellite land cover units. The study area is the republic of Colombia in South America. The methodology consisted of analyzing the multitemporal (vegetation, soil and shade-water) fraction images and vegetation indices (NDVI) apply the lineal spectral mixture model to products derived from derived images by sensor MODIS data obtained in years 2001 and 2003. The mosaics of the original and the transformed vegetation (soil and shade-water) bands were generated for the whole study area using SPRING 4. 0 software, developed by INPE then these mosaics were segmented, classified, mapped, and edited to obtain a moderate resolution land cover map. The results derived from MODIS analysis were compared with Landsat ETM+ data acquire for a single test site. The results of the project showed the usefulness of MODIS images for large-scale land cover mapping and monitoring studies

  3. Integrated analysis of climate, soil, topography and vegetative growth in Iberian viticultural regions.

    Directory of Open Access Journals (Sweden)

    Helder Fraga

    Full Text Available The Iberian viticultural regions are convened according to the Denomination of Origin (DO and present different climates, soils, topography and management practices. All these elements influence the vegetative growth of different varieties throughout the peninsula, and are tied to grape quality and wine type. In the current study, an integrated analysis of climate, soil, topography and vegetative growth was performed for the Iberian DO regions, using state-of-the-art datasets. For climatic assessment, a categorized index, accounting for phenological/thermal development, water availability and grape ripening conditions was computed. Soil textural classes were established to distinguish soil types. Elevation and aspect (orientation were also taken into account, as the leading topographic elements. A spectral vegetation index was used to assess grapevine vegetative growth and an integrated analysis of all variables was performed. The results showed that the integrated climate-soil-topography influence on vine performance is evident. Most Iberian vineyards are grown in temperate dry climates with loamy soils, presenting low vegetative growth. Vineyards in temperate humid conditions tend to show higher vegetative growth. Conversely, in cooler/warmer climates, lower vigour vineyards prevail and other factors, such as soil type and precipitation acquire more important roles in driving vigour. Vines in prevailing loamy soils are grown over a wide climatic diversity, suggesting that precipitation is the primary factor influencing vigour. The present assessment of terroir characteristics allows direct comparison among wine regions and may have great value to viticulturists, particularly under a changing climate.

  4. Impact of Sensor Degradation on the MODIS NDVI Time Series

    Science.gov (United States)

    Wang, Dongdong; Morton, Douglas Christopher; Masek, Jeffrey; Wu, Aisheng; Nagol, Jyoteshwar; Xiong, Xiaoxiong; Levy, Robert; Vermote, Eric; Wolfe, Robert

    2012-01-01

    Time series of satellite data provide unparalleled information on the response of vegetation to climate variability. Detecting subtle changes in vegetation over time requires consistent satellite-based measurements. Here, the impact of sensor degradation on trend detection was evaluated using Collection 5 data from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensors on the Terra and Aqua platforms. For Terra MODIS, the impact of blue band (Band 3, 470 nm) degradation on simulated surface reflectance was most pronounced at near-nadir view angles, leading to a 0.001-0.004 yr-1 decline in Normalized Difference Vegetation Index (NDVI) under a range of simulated aerosol conditions and surface types. Observed trends in MODIS NDVI over North America were consistentwith simulated results,with nearly a threefold difference in negative NDVI trends derived from Terra (17.4%) and Aqua (6.7%) MODIS sensors during 2002-2010. Planned adjustments to Terra MODIS calibration for Collection 6 data reprocessing will largely eliminate this negative bias in detection of NDVI trends.

  5. Assessment of MODIS-EVI, MODIS-NDVI and VEGETATION-NDVI composite data using agricultural measurements: an example at corn fields in western Mexico.

    Science.gov (United States)

    Chen, Pei-Yu; Fedosejevs, Gunar; Tiscareño-López, Mario; Arnold, Jeffrey G

    2006-08-01

    Although several types of satellite data provide temporal information of the land use at no cost, digital satellite data applications for agricultural studies are limited compared to applications for forest management. This study assessed the suitability of vegetation indices derived from the TERRA-Moderate Resolution Imaging Spectroradiometer (MODIS) sensor and SPOT-VEGETATION (VGT) sensor for identifying corn growth in western Mexico. Overall, the Normalized Difference Vegetation Index (NDVI) composites from the VGT sensor based on bi-directional compositing method produced vegetation information most closely resembling actual crop conditions. The NDVI composites from the MODIS sensor exhibited saturated signals starting 30 days after planting, but corresponded to green leaf senescence in April. The temporal NDVI composites from the VGT sensor based on the maximum value method had a maximum plateau for 80 days, which masked the important crop transformation from vegetative stage to reproductive stage. The Enhanced Vegetation Index (EVI) composites from the MODIS sensor reached a maximum plateau 40 days earlier than the occurrence of maximum leaf area index (LAI) and maximum intercepted fraction of photosynthetic active radiation (fPAR) derived from in-situ measurements. The results of this study showed that the 250-m resolution MODIS data did not provide more accurate vegetation information for corn growth description than the 500-m and 1000-m resolution MODIS data.

  6. NDVI, scale invariance and the modifiable areal unit problem : An assessment of vegetation in the Adelaide Parklands

    NARCIS (Netherlands)

    Nouri, Hamideh; Anderson, Sharolyn; Sutton, Paul; Beecham, Simon; Nagler, Pamela; Jarchow, Christopher J.; Roberts, Dar A.

    2017-01-01

    This research addresses the question as to whether or not the Normalised Difference Vegetation Index (NDVI) is scale invariant (i.e. constant over spatial aggregation) for pure pixels of urban vegetation. It has been long recognized that there are issues related to the modifiable areal unit problem

  7. JUSTIFICATION DIRECTIONS OF DEVELOPMENT OF VEGETABLE PRODUCTION IN DEHKAN FARMS OF THE REPUBLIC OF TAJIKISTAN

    Directory of Open Access Journals (Sweden)

    Mahira Ergasheva

    2015-09-01

    Full Text Available In article directions of development of vegetable production on the basis of an assessment of the growth dynamics of cultivated areas of vegetables in dehkan farms of the Republic of Tajikistan. In particular, factor analysis, index method, and found that the growth of the gross harvest of vegetables mainly driven by growth in acreage and yield growth, and therefore it is justified as the development direction of the necessity of transition to an additive method of management.

  8. Recent shifts in Himalayan vegetation activity trends in response to climatic change and environmental drivers

    Science.gov (United States)

    Mishra, N. B.; Mainali, K. P.

    2016-12-01

    Climatic changes along with anthropogenic disturbances are causing dramatic ecological impacts in mid to high latitude mountain vegetation including in the Himalayas which are ecologically sensitive environments. Given the challenges associated with in situ vegetation monitoring in the Himalayas, remote sensing based quantification of vegetation dynamics can provide essential ecological information on changes in vegetation activity that may consist of alternative sequence of greening and/or browning periods. This study utilized a trend break analysis procedure for detection of monotonic as well as abrupt (either interruption or reversal) trend changes in smoothed normalized difference vegetation index satellite time-series data over the Himalayas. Overall, trend breaks in vegetation greenness showed high spatio-temporal variability in distribution considering elevation, ecoregion and land cover/use stratifications. Interrupted greening was spatially most dominant in all Himalayan ecoregions followed by abrupt browning. Areas showing trend reversal and monotonic trends appeared minority. Trend type distribution was strongly dependent on elevation as majority of greening (with or without interruption) occurred at lower elevation areas at higher elevation were dominantly. Ecoregion based stratification of trend types highlighted some exception to this elevational dependence as high altitude ecoregions of western Himalayas showed significantly less browning compared to the ecoregions in eastern Himalaya. Land cover/use based analysis of trend distribution showed that interrupted greening was most dominant in closed needleleafed forest following by rainfed cropland and mosaic croplands while interrupted browning most dominant in closed to open herbaceous vegetation found at higher elevation areas followed by closed needleleafed forest and closed to open broad leafed evergreen forests. Spatial analysis of trend break timing showed that for majority of areas experiencing

  9. Spatio-temporal monitoring of vegetation phenology in the dry sub-humid region of Nigeria using time series of AVHRR NDVI and TAMSAT datasets

    Science.gov (United States)

    Osunmadewa, Babatunde Adeniyi; Gebrehiwot, Worku Zewdie; Csaplovics, Elmar; Adeofun, Olabinjo Clement

    2018-03-01

    Time series data are of great importance for monitoring vegetation phenology in the dry sub-humid regions where change in land cover has influence on biomass productivity. However few studies have inquired into examining the impact of rainfall and land cover change on vegetation phenology. This study explores Seasonal Trend Analysis (STA) approach in order to investigate overall greenness, peak of annual greenness and timing of annual greenness in the seasonal NDVI cycle. Phenological pattern for the start of season (SOS) and end of season (EOS) was also examined across different land cover types in four selected locations. A significant increase in overall greenness (amplitude 0) and a significant decrease in other greenness trend maps (amplitude 1 and phase 1) was observed over the study period. Moreover significant positive trends in overall annual rainfall (amplitude 0) was found which follows similar pattern with vegetation trend. Variation in the timing of peak of greenness (phase 1) was seen in the four selected locations, this indicate a change in phenological trend. Additionally, strong relationship was revealed by the result of the pixel-wise regression between NDVI and rainfall. Change in vegetation phenology in the study area is attributed to climatic variability than anthropogenic activities.

  10. Spatio-temporal monitoring of vegetation phenology in the dry sub-humid region of Nigeria using time series of AVHRR NDVI and TAMSAT datasets

    Directory of Open Access Journals (Sweden)

    Osunmadewa Babatunde Adeniyi

    2018-03-01

    Full Text Available Time series data are of great importance for monitoring vegetation phenology in the dry sub-humid regions where change in land cover has influence on biomass productivity. However few studies have inquired into examining the impact of rainfall and land cover change on vegetation phenology. This study explores Seasonal Trend Analysis (STA approach in order to investigate overall greenness, peak of annual greenness and timing of annual greenness in the seasonal NDVI cycle. Phenological pattern for the start of season (SOS and end of season (EOS was also examined across different land cover types in four selected locations. A significant increase in overall greenness (amplitude 0 and a significant decrease in other greenness trend maps (amplitude 1 and phase 1 was observed over the study period. Moreover significant positive trends in overall annual rainfall (amplitude 0 was found which follows similar pattern with vegetation trend. Variation in the timing of peak of greenness (phase 1 was seen in the four selected locations, this indicate a change in phenological trend. Additionally, strong relationship was revealed by the result of the pixel-wise regression between NDVI and rainfall. Change in vegetation phenology in the study area is attributed to climatic variability than anthropogenic activities.

  11. Advances in estimation methods of vegetation water content based on optical remote sensing techniques

    Institute of Scientific and Technical Information of China (English)

    2010-01-01

    Quantitative estimation of vegetation water content(VWC) using optical remote sensing techniques is helpful in forest fire as-sessment,agricultural drought monitoring and crop yield estimation.This paper reviews the research advances of VWC retrieval using spectral reflectance,spectral water index and radiative transfer model(RTM) methods.It also evaluates the reli-ability of VWC estimation using spectral water index from the observation data and the RTM.Focusing on two main definitions of VWC-the fuel moisture content(FMC) and the equivalent water thickness(EWT),the retrieval accuracies of FMC and EWT using vegetation water indices are analyzed.Moreover,the measured information and the dataset are used to estimate VWC,the results show there are significant correlations among three kinds of vegetation water indices(i.e.,WSI,NDⅡ,NDWI1640,WI/NDVI) and canopy FMC of winter wheat(n=45).Finally,the future development directions of VWC detection based on optical remote sensing techniques are also summarized.

  12. Study of microbiological background of herbal ingredients and dairy-vegetable compositions

    Directory of Open Access Journals (Sweden)

    D. V. Kharitonov

    2016-01-01

    Full Text Available The rates of microbiological safety of powdery vegetables, vegetable-milk compositions, compound desserts have been studied. No pathogenic germs (incl. salmonella, Escherichia coli, yeast, nonspore-forming bacteria B cereus have been detected in powdery vegetable samples. The number of mesophilic aerobic and facultative anaerobic microorganisms as well as amount of molds does not exceed safety index normalized by the legislation. Proteolytic microorganisms compose the basic microflora of powdery vegetables. Microbiological background of vegetable and milk basis is characterized by the presence of microorganisms differed by different resistance to the medium conditions – рН value, presence of oxygen and high temperatures impact. Enrichment of milk base by vegetable components necessitates to adjust the thermal effect regimes prescribed for milk treatment without additional ingredients. Introduction of vegetable ingredients into milk base is accompanied by polysemantic effect of high temperatures on microorganisms of polycomponent milk – vegetable base. On the one hand introduction of vegetable raw material into milk enhances inhibitory temperature effect on microbial cells due to transition of the medium рН into sour side; on the other hand presence of vegetable raw material particles protects microorganisms against sensitive effect of high temperature. Microflora of vegetable-milk compositions after heat treatment as well as ready-made desserts on their base was presented by spore-forming bacillus the number of which is correlated by their number in the initial raw material. In order to choose the optimal regime of heat treatment all processes running during heat treatment and particularly microbiological and physical-chemical degradation of polysaccharides of vegetables cell structures.

  13. Beyond Precipitation: Physiographic Gradients Dictate the Relative Importance of Environmental Drivers on Savanna Vegetation

    Science.gov (United States)

    Campo-Bescós, Miguel A.; Muñoz-Carpena, Rafael; Kaplan, David A.; Southworth, Jane; Zhu, Likai; Waylen, Peter R.

    2013-01-01

    Background Understanding the drivers of large-scale vegetation change is critical to managing landscapes and key to predicting how projected climate and land use changes will affect regional vegetation patterns. This study aimed to improve our understanding of the role, magnitude and spatial distribution of the key environmental factors driving vegetation change in southern African savanna, and how they vary across physiographic gradients. Methodology/Principal Findings We applied Dynamic Factor Analysis (DFA), a multivariate times series dimension reduction technique to ten years of monthly remote sensing data (MODIS-derived normalized difference vegetation index, NDVI) and a suite of environmental covariates: precipitation, mean and maximum temperature, soil moisture, relative humidity, fire and potential evapotranspiration. Monthly NDVI was described by cyclic seasonal variation with distinct spatiotemporal patterns in different physiographic regions. Results support existing work emphasizing the importance of precipitation, soil moisture and fire on NDVI, but also reveal overlooked effects of temperature and evapotranspiration, particularly in regions with higher mean annual precipitation. Critically, spatial distributions of the weights of environmental covariates point to a transition in the importance of precipitation and soil moisture (strongest in grass-dominated regions with precipitation950 mm). Conclusions/Significance We quantified the combined spatiotemporal effects of an available suite of environmental drivers on NDVI across a large and diverse savanna region. The analysis supports known drivers of savanna vegetation but also uncovers important roles of temperature and evapotranspiration. Results highlight the utility of applying the DFA approach to remote sensing products for regional analyses of landscape change in the context of global environmental change. With the dramatic increase in global change research, this methodology augurs well for

  14. Wiener Index, Diameter, and Stretch Factor of a Weighted Planar Graph in Subquadratic Time

    DEFF Research Database (Denmark)

    Wulff-Nilsen, Christian

    over all pairs of distinct vertices of the ratio between the graph distance and the Euclidean distance between the two vertices). More specifically, we show that the Wiener index and diameter can be found in O(n^2*(log log n)^4/log n) worst-case time and that the stretch factor can be found in O(n^2......We solve three open problems: the existence of subquadratic time algorithms for computing the Wiener index (sum of APSP distances) and the diameter (maximum distance between any vertex pair) of a planar graph with non-negative edge weights and the stretch factor of a plane geometric graph (maximum...

  15. Covering soils and vegetations during decommissioning disposal of a uranium mine

    International Nuclear Information System (INIS)

    Feng Weihua

    2010-01-01

    The disposals of waste ore dumps and tailings are an important part in the decommissioning disposal of uranium mines. Important indexes of the disposal include stabilization, harmlessness, rehabilitation and improvement of the ecological environment. These are closely related with vegetations. Taking example of decommissioning disposal of a uranium mine in Guizhou province, the selection of grasses and effects after covering soils and planting grasses are introduced. It is pointed out that covering soils and vegetations play an important role in decommissioning disposal of uranium mines. (authors)

  16. Relationships between NDVI, canopy structure, and photosynthesis in three California vegetation types

    International Nuclear Information System (INIS)

    Gamon, J.A.; Field, C.B.; Goulden, M.L.; Griffin, K.L.; Hartley, A.E.; Joel, G.; Penuelas, J.; Valentini, R.

    1995-01-01

    In a range of plant species from three Californian vegetation types, we examined the widely used ''normalized difference vegetation index'' (NDVI) and ''simple ratio'' (SR) as indicators of canopy structure, light absorption, and photosynthetic activity. These indices, which are derived from canopy reflectance in the red and near-infrared wavebands, highlighted phenological differences between evergreen and deciduous canopies. They were poor indicators of total canopy biomass due to the varying abundance of non-green standing biomass in these vegetation types. However, in sparse canopies (leaf area index (LAI) apprxeq 0-2), NDVI was a sensitive indicator of canopy structure and chemical content (green biomass, green leaf area index, chlorophyll content, and foliar nitrogen content). At higher canopy green LAI values ( gt 2; typical of dense shrubs and trees), NDVI was relatively insensitive to changes in canopy structure. Compared to SR, NDVI was better correlated with indicators of canopy structure and chemical content, but was equivalent to the logarithm of SR. In agreement with theoretical expectations, both NDVI and SR exhibited near-linear correlations with fractional PAR intercepted by green leaves over a wide range of canopy densities. Maximum daily photosynthetic rates were positively correlated with NDVI and SR in annual grassland and semideciduous shrubs where canopy development and photosynthetic activity were in synchrony. The indices were also correlated with peak springtime canopy photosynthetic rates in evergreens. However, over most of the year, these indices were poor predictors of photosynthetic performance in evergreen species due to seasonal reductions in photosynthetic radiation-use efficiency that occurred without substantial declines in canopy greenness. Our results support the use of these vegetation indices as remote indicators of PAR absorption, and thus potential photosynthetic activity, even in

  17. A new multi-sensor integrated index for drought monitoring

    Science.gov (United States)

    Jiao, W.; Wang, L.; Tian, C.

    2017-12-01

    Drought is perceived as one of the most expensive and least understood natural disasters. The remote-sensing-based integrated drought indices, which integrate multiple variables, could reflect the drought conditions more comprehensively than single drought indices. However, most of current remote-sensing-based integrated drought indices focus on agricultural drought (i.e., deficit in soil moisture), their application in monitoring meteorological drought (i.e., deficit in precipitation) was limited. More importantly, most of the remote-sensing-based integrated drought indices did not take into consideration of the spatially non-stationary nature of the related variables, so such indices may lose essential local details when integrating multiple variables. In this regard, we proposed a new mathematical framework for generating integrated drought index for meteorological drought monitoring. The geographically weighted regression (GWR) model and principal component analysis were used to composite Moderate-resolution Imaging Spectroradiometer (MODIS) based temperature condition index (TCI), the Vegetation Index based on the Universal Pattern Decomposition method (VIUPD) based vegetation condition index (VCI), tropical rainfall measuring mission (TRMM) based Precipitation Condition Index (PCI) and Advanced Microwave Scanning Radiometer-EOS (AMSR-E) based soil moisture condition index (SMCI). We called the new remote-sensing-based integrated drought index geographical-location-based integrated drought index (GLIDI). We examined the utility of the GLIDI for drought monitoring in various climate divisions across the continental United States (CONUS). GLIDI showed high correlations with in-situ drought indices and outperformed most other existing drought indices. The results also indicate that the performance of GLIDI is not affected by environmental factors such as land cover, precipitation, temperature and soil conditions. As such, the GLIDI has considerable potential for

  18. Beyond the Normalized Difference Vegetation Index (NDVI): Developing a Natural Space Index for population-level health research.

    Science.gov (United States)

    Rugel, Emily J; Henderson, Sarah B; Carpiano, Richard M; Brauer, Michael

    2017-11-01

    Natural spaces can provide psychological benefits to individuals, but population-level epidemiologic studies have produced conflicting results. Refining current exposure-assessment methods is necessary to advance our understanding of population health and to guide the design of health-promoting urban forms. The aim of this study was to develop a comprehensive Natural Space Index that robustly models potential exposure based on the presence, form, accessibility, and quality of multiple forms of greenspace (e.g., parks and street trees) and bluespace (e.g., oceans and lakes). The index was developed for greater Vancouver, Canada. Greenness presence was derived from remote sensing (NDVI/EVI); forms were extracted from municipal and private databases; and accessibility was based on restrictions such as private ownership. Quality appraisals were conducted for 200 randomly sampled parks using the Public Open Space Desktop Appraisal Tool (POSDAT). Integrating these measures in GIS, exposure was assessed for 60,242 postal codes using 100- to 1,600-m buffers based on hypothesized pathways to mental health. A single index was then derived using principal component analysis (PCA). Comparing NDVI with alternate approaches for assessing natural space resulted in widely divergent results, with quintile rankings shifting for 22-88% of postal codes, depending on the measure. Overall park quality was fairly low (mean of 15 on a scale of 0-45), with no significant difference seen by neighborhood-level household income. The final PCA identified three main sets of variables, with the first two components explaining 68% of the total variance. The first component was dominated by the percentages of public and private greenspace and bluespace and public greenspace within 250m, while the second component was driven by lack of access to bluespace within 1 km. Many current approaches to modeling natural space may misclassify exposures and have limited specificity. The Natural Space Index

  19. Analyses of GIMMS NDVI Time Series in Kogi State, Nigeria

    Science.gov (United States)

    Palka, Jessica; Wessollek, Christine; Karrasch, Pierre

    2017-10-01

    The value of remote sensing data is particularly evident where an areal monitoring is needed to provide information on the earth's surface development. The use of temporal high resolution time series data allows for detecting short-term changes. In Kogi State in Nigeria different vegetation types can be found. As the major population in this region is living in rural communities with crop farming the existing vegetation is slowly being altered. The expansion of agricultural land causes loss of natural vegetation, especially in the regions close to the rivers which are suitable for crop production. With regard to these facts, two questions can be dealt with covering different aspects of the development of vegetation in the Kogi state, the determination and evaluation of the general development of the vegetation in the study area (trend estimation) and analyses on a short-term behavior of vegetation conditions, which can provide information about seasonal effects in vegetation development. For this purpose, the GIMMS-NDVI data set, provided by the NOAA, provides information on the normalized difference vegetation index (NDVI) in a geometric resolution of approx. 8 km. The temporal resolution of 15 days allows the already described analyses. For the presented analysis data for the period 1981-2012 (31 years) were used. The implemented workflow mainly applies methods of time series analysis. The results show that in addition to the classical seasonal development, artefacts of different vegetation periods (several NDVI maxima) can be found in the data. The trend component of the time series shows a consistently positive development in the entire study area considering the full investigation period of 31 years. However, the results also show that this development has not been continuous and a simple linear modeling of the NDVI increase is only possible to a limited extent. For this reason, the trend modeling was extended by procedures for detecting structural breaks in

  20. Marketing channel choice and marketing timing of peri-urban vegetable growers in Vietnam

    NARCIS (Netherlands)

    Wiersinga, R.C.; Wijk, van M.S.; Luyen, C.H.; Hoi, P.V.

    2007-01-01

    Agriculture is an important sector in the peri-urban area of Hanoi. It supplies 62 to 80% of vegetable consumption, of which 28% comes from Dong Anh district, which borders Hanoi City. Growing vegetables is an important income source for the farmers in Dong Anh as it contributes about 30% to their

  1. Global changes in dryland vegetation dynamics (1988–2008 assessed by satellite remote sensing: comparing a new passive microwave vegetation density record with reflective greenness data

    Directory of Open Access Journals (Sweden)

    N. Andela

    2013-10-01

    Full Text Available Drylands, covering nearly 30% of the global land surface, are characterized by high climate variability and sensitivity to land management. Here, two satellite-observed vegetation products were used to study the long-term (1988–2008 vegetation changes of global drylands: the widely used reflective-based Normalized Difference Vegetation Index (NDVI and the recently developed passive-microwave-based Vegetation Optical Depth (VOD. The NDVI is sensitive to the chlorophyll concentrations in the canopy and the canopy cover fraction, while the VOD is sensitive to vegetation water content of both leafy and woody components. Therefore it can be expected that using both products helps to better characterize vegetation dynamics, particularly over regions with mixed herbaceous and woody vegetation. Linear regression analysis was performed between antecedent precipitation and observed NDVI and VOD independently to distinguish the contribution of climatic and non-climatic drivers in vegetation variations. Where possible, the contributions of fire, grazing, agriculture and CO2 level to vegetation trends were assessed. The results suggest that NDVI is more sensitive to fluctuations in herbaceous vegetation, which primarily uses shallow soil water, whereas VOD is more sensitive to woody vegetation, which additionally can exploit deeper water stores. Globally, evidence is found for woody encroachment over drylands. In the arid drylands, woody encroachment appears to be at the expense of herbaceous vegetation and a global driver is interpreted. Trends in semi-arid drylands vary widely between regions, suggesting that local rather than global drivers caused most of the vegetation response. In savannas, besides precipitation, fire regime plays an important role in shaping trends. Our results demonstrate that NDVI and VOD provide complementary information and allow new insights into dryland vegetation dynamics.

  2. Environmental Drivers of NDVI-Based Vegetation Phenology in Central Asia

    Directory of Open Access Journals (Sweden)

    Jahan Kariyeva

    2011-02-01

    Full Text Available Through the application and use of geospatial data, this study aimed to detect and characterize some of the key environmental drivers contributing to landscape-scale vegetation response patterns in Central Asia. The objectives of the study were to identify the variables driving the year-to-year vegetation dynamics in three regional landscapes (desert, steppe, and mountainous; and to determine if the identified environmental drivers can be used to explain the spatial-temporal variability of these spatio-temporal dynamics over time. It was posed that patterns of change in terrestrial phenology, derived from the 8 km bi-weekly time series of Normalized Difference Vegetation Index (NDVI data acquired by the Advanced Very High Resolution Radiometer (AVHRR satellites (1981–2008, can be explained through a multi-scale analysis of a suite of environmental drivers. Multiple linear stepwise regression analyses were used to test the hypotheses and address the objectives of the study. The annually computed phenological response variables or pheno-metricstime (season start, season length, and an NDVI-based productivity metric were modeled as a function of ten environmental factors relating to soil, topography, and climate. Each of the three studied regional landscapes was shown to be governed by a distinctive suite of environmental drivers. The phenological responses of the steppe landscapes were affected by the year-to-year variation in temperature regimes. The phenology of the mountainous landscapes was influenced primarily by the elevation gradient. The phenological responses of desert landscapes were demonstrated to have the greatest variability over time and seemed to be affected by soil carbon content and year-to-year variation of both temperature regimes and winter precipitation patterns. Amounts and scales of observed phenological variability over time (measured through coefficient of variation for each pheno-metrictime in each of the regional

  3. Comparison of Landsat-8 and Sentinel-2A reflectance and normalized difference vegetation index

    Science.gov (United States)

    Zhang, H.; Roy, D. P.; Yan, L.; Li, Z.; Huang, H.

    2017-12-01

    The moderate spatial resolution satellite data from the polar-orbiting Landsat-8 (launched 2013) and Sentinel-2A (launched 2015) sensors provide 10 m to 30 m multi-spectral global coverage with a better than 5-day revisit. Although a national laboratory traceable cross-calibration comparison of the Landsat-8 Operational Land Imager (OLI) and the Sentinel-2A MultiSpectral Instrument (MSI) was undertaken pre-launch, there are a number of other sensor differences, notably due to spectral, spatial and angular differences. To examine these in a comprehensive way, Landsat-8 and Sentinel-2A data for approximately 20° × 10° of southern Africa acquired in the summer (January to March) and winter (July to September) of 2016 were compared. Only Landsat-8 and Sentinel-2A observations acquired within one-day apart were considered. The sensor data were registered and then each orbit projected into 30 m fixed global Web Enabled Landsat Data (GWELD) tiles defined in the MODIS sinusoidal equal area projection. Only corresponding sensor observations of each 30 m tile pixel that were flagged as cloud and snow-free, unsaturated, and that had no significant change in their one day separation, were compared. Both the Landsat-8 and Sentinel-2A data were atmospherically corrected using the Landsat Surface Reflectance Code (LaSRC) and were also corrected to nadir BRDF adjusted reflectance (NBAR). Top of atmosphere and surface reflectance for the spectrally corresponding visible, near infrared and shortwave infrared OLI and MSI bands, and derived normalized difference vegetation index (NDVI), were compared and their differences quantified using regression analyses. The resulting statistical transformations may be used to improve the consistency between the Landsat-8 OLI and Sentinel-2A MSI data. The importance and sensitivity of the results to correct filtering, atmospheric correction and adjustment to NBAR is demonstrated.

  4. Vegetation Earth System Data Record from DSCOVR EPIC Observations

    Science.gov (United States)

    Knyazikhin, Y.; Song, W.; Yang, B.; Mottus, M.; Rautiainen, M.; Stenberg, P.

    2017-12-01

    The NASA's Earth Polychromatic Imaging Camera (EPIC) onboard NOAA's Deep Space Climate Observatory (DSCOVR) mission was launched on February 11, 2015 to the Sun-Earth Lagrangian L1 point where it began to collect radiance data of the entire sunlit Earth every 65 to 110 min in June 2015. It provides imageries in near backscattering directions with the scattering angle between 168° and 176° at ten ultraviolet to near infrared (NIR) narrow spectral bands centered at 317.5 (band width 1.0) nm, 325.0 (2.0) nm, 340.0 (3.0) nm, 388.0 (3.0) nm, 433.0 (3.0) nm, 551.0 (3.0) nm, 680.0 (3.0) nm, 687.8 (0.8) nm, 764.0 (1.0) nm and 779.5 (2.0) nm. This poster presents current status of the Vegetation Earth System Data Record of global Leaf Area Index (LAI), solar zenith angle dependent Sunlit Leaf Area Index (SLAI), Fraction vegetation absorbed Photosynthetically Active Radiation (FPAR) and Normalized Difference Vegetation Index (NDVI) derived from the DSCOVR EPIC observations. Whereas LAI is a standard product of many satellite missions, the SLAI is a new satellite-derived parameter. Sunlit and shaded leaves exhibit different radiative response to incident Photosynthetically Active Radiation (400-700 nm), which in turn triggers various physiological and physical processes required for the functioning of plants. FPAR, LAI and SLAI are key state parameters in most ecosystem productivity models and carbon/nitrogen cycle. The product at 10 km sinusoidal grid and 65 to 110 min temporal frequency as well as accompanying Quality Assessment (QA) variables will be publicly available from the NASA Langley Atmospheric Science Data Center. The Algorithm Theoretical Basis (ATBD) and product validation strategy are also discussed in this poster.

  5. The 2010 Russian Drought Impact on Satellite Measurements of Solar-Induced Chlorophyll Fluorescence: Insights from Modeling and Comparisons with the Normalized Differential Vegetation Index (NDVI)

    Science.gov (United States)

    Yoshida, Y.; Joiner, J.; Tucker, C.; Berry, J.; Lee, J. -E.; Walker, G.; Reichle, R.; Koster, R.; Lyapustin, A.; Wang, Y.

    2015-01-01

    We examine satellite-based measurements of chlorophyll solar-induced fluorescence (SIF) over the region impacted by the Russian drought and heat wave of 2010. Like the popular Normalized Difference Vegetation Index (NDVI) that has been used for decades to measure photosynthetic capacity, SIF measurements are sensitive to the fraction of absorbed photosynthetically-active radiation (fPAR). However, in addition, SIF is sensitive to the fluorescence yield that is related to the photosynthetic yield. Both SIF and NDVI from satellite data show drought-related declines early in the growing season in 2010 as compared to other years between 2007 and 2013 for areas dominated by crops and grasslands. This suggests an early manifestation of the dry conditions on fPAR. We also simulated SIF using a global land surface model driven by observation-based meteorological fields. The model provides a reasonable simulation of the drought and heat impacts on SIF in terms of the timing and spatial extents of anomalies, but there are some differences between modeled and observed SIF. The model may potentially be improved through data assimilation or parameter estimation using satellite observations of SIF (as well as NDVI). The model simulations also offer the opportunity to examine separately the different components of the SIF signal and relationships with Gross Primary Productivity (GPP).

  6. Enhancement of vegetation-rainfall feedbacks on the Australian summer monsoon by the Madden-Julian Oscillation

    Science.gov (United States)

    Notaro, Michael

    2018-01-01

    A regional climate modeling analysis of the Australian monsoon system reveals a substantial modulation of vegetation-rainfall feedbacks by the Madden Julian Oscillation (MJO), both of which operate at similar sub-seasonal time scales, as evidence that the intensity of land-atmosphere interactions is sensitive to the background atmospheric state. Based on ensemble experiments with imposed modification of northern Australian leaf area index (LAI), the atmospheric responses to LAI anomalies are composited for negative and positive modes of the propagating MJO. In the regional climate model (RCM), northern Australian vegetation feedbacks are characterized by evapotranspiration (ET)-driven rainfall responses, with the moisture feedback mechanism dominating over albedo and roughness feedback mechanisms. During November-April, both Tropical Rainfall Measuring Mission and RCM data reveal MJO's pronounced influence on rainfall patterns across northern Australia, tropical Indian Ocean, Timor Sea, Arafura Sea, and Gulf of Carpentaria, with the MJO dominating over vegetation feedbacks in terms of regulating monsoon rainfall variability. Convectively-active MJO phases support an enhancement of positive vegetation feedbacks on monsoon rainfall. While the MJO imposes minimal regulation of ET responses to LAI anomalies, the vegetation feedback-induced responses in precipitable water, cloud water, and rainfall are greatly enhanced during convectively-active MJO phases over northern Australia, which are characterized by intense low-level convergence and efficient precipitable water conversion. The sub-seasonal response of vegetation-rainfall feedback intensity to the MJO is complex, with significant enhancement of rainfall responses to LAI anomalies in February during convectively-active MJO phases compared to minimal modulation by the MJO during prior and subsequent calendar months.

  7. A normalized difference vegetation index (NDVI) time-series of idle agriculture lands: A preliminary study

    NARCIS (Netherlands)

    Vaiphasa, C.; Piamduaytham, S.; Vaiphasa, T.; Skidmore, A.K.

    2011-01-01

    In this paper, the NDVI time-series collected from the study area between year 2003 and 2005 of all land cover types are plotted and compared. The study area is the agricultural zones in Banphai District, Khonkean, Thailand. The LANDSAT satellite images of different dates were first transformed into

  8. [Monitoring temporal dynamics in leaf area index of the temperate broadleaved deciduous forest in Maoershan region, Northeast China with tower-based radiation measurements.

    Science.gov (United States)

    Liu, Fan; Wang, Chuan Kuan; Wang, Xing Chang

    2016-08-01

    Broadband vegetation indices (BVIs) derived from routine radiation measurements on eddy flux towers have the advantage of high temporal resolutions, and thus have the potential to obtain detailed information of dynamics in canopy leaf area index (LAI). Taking the temperate broadleaved deciduous forest around the Maoershan flux tower in Northeast China as a case, we investigated the controlling factors and smoothing method of four BVI time-series, i.e., broadband norma-lized difference vegetation index (NDVI B ), broadband enhanced vegetation index (EVI B ), the ratio of the near-infrared radiation reflectance to photosynthetically active radiation reflectance (SR NP ), and the ratio of the shortwave radiation reflectance to photosynthetically active radiation reflectance (SR SP ). We compared the seasonal courses of the BVIs with the LAI based on litterfall collection method. The values for each BVI were slightly different among the three calculation methods by Huemmrich, Wilson, and Jenkins, but showed similar seasonal patterns. The diurnal variations in BVIs were mainly influenced by the solar elevation and the angle between the solar elevation and slope, but the BVIs were relatively stable around 12:30. The noise of daily BVI time-series could be effectively smoothed by a threshold of clearness index (K). The seasonal courses of BVIs for each time of day around the noon had similar patterns, but their thresholds of K and the percen-tages of remaining data were different. Therefore, the daily values of BVIs might be optimized based on the smoothing and the proportion of remaining data. The NDVI B was closely correlated linearly with the LAI derived from the litterfall collection method, while the EVI B , SR NP , and SR SP had a logarithmic relationship with the LAI. The NDVI B had the advantage in tracking the seasonal dyna-mics in LAI and extrapolating LAI to a broader scale. Given that most eddy flux towers had equipped with energy balance measurements, a

  9. Vegetation improvement and soil biological quality in the Sahel of ...

    African Journals Online (AJOL)

    The method of Tropical Soil Biology and Fertility (TSBF) was used to assess macro-fauna abundance and diversity in different land use types (cropland, shallow land, degraded land and forest). Four sites were selected, in the Sahelian zone of Burkina Faso, with contrasted Normalized Difference Vegetation Index (NDVI).

  10. Sensor and Methodology for Dielectric Analysis of Vegetal Oils Submitted to Thermal Stress

    Directory of Open Access Journals (Sweden)

    Sergio Luiz Stevan

    2015-10-01

    Full Text Available Vegetable oils used in frying food represent a social problem as its destination. The residual oil can be recycled and returned to the production line, as biodiesel, as soap, or as putty. The state of the residual oil is determined according to their physicochemical characteristics whose values define its economically viable destination. However, the physicochemical analysis requires high costs, time and general cost of transporting. This study presents the use of a capacitive sensor and a quick and inexpensive method to correlate the physicochemical variables to the dielectric constant of the material undergoing oil samples to thermal cycling. The proposed method allows reducing costs in the characterization of residual oil and the reduction in analysis time. In addition, the method allows an assessment of the quality of the vegetable oil during use. The experimental results show the increasing of the dielectric constant with the temperature, which facilitates measurement and classification of the dielectric constant at considerably higher temperatures. The results also confirm a definitive degradation in used oil and a correlation between the dielectric constant of the sample with the results of the physicochemical analysis (iodine value, acid value, viscosity and refractive index.

  11. Sensor and methodology for dielectric analysis of vegetal oils submitted to thermal stress.

    Science.gov (United States)

    Stevan, Sergio Luiz; Paiter, Leandro; Galvão, José Ricardo; Roque, Daniely Vieira; Chaves, Eduardo Sidinei

    2015-10-16

    Vegetable oils used in frying food represent a social problem as its destination. The residual oil can be recycled and returned to the production line, as biodiesel, as soap, or as putty. The state of the residual oil is determined according to their physicochemical characteristics whose values define its economically viable destination. However, the physicochemical analysis requires high costs, time and general cost of transporting. This study presents the use of a capacitive sensor and a quick and inexpensive method to correlate the physicochemical variables to the dielectric constant of the material undergoing oil samples to thermal cycling. The proposed method allows reducing costs in the characterization of residual oil and the reduction in analysis time. In addition, the method allows an assessment of the quality of the vegetable oil during use. The experimental results show the increasing of the dielectric constant with the temperature, which facilitates measurement and classification of the dielectric constant at considerably higher temperatures. The results also confirm a definitive degradation in used oil and a correlation between the dielectric constant of the sample with the results of the physicochemical analysis (iodine value, acid value, viscosity and refractive index).

  12. Enhanced vegetation growth peak and its key mechanisms

    Science.gov (United States)

    Huang, K.; Xia, J.; Wang, Y.; Ahlström, A.; Schwalm, C.; Huntzinger, D. N.; Chen, J.; Cook, R. B.; Fang, Y.; Fisher, J. B.; Jacobson, A. R.; Michalak, A.; Schaefer, K. M.; Wei, Y.; Yan, L.; Luo, Y.

    2017-12-01

    It remains unclear that whether and how the vegetation growth peak has been shifted globally during the past three decades. Here we used two global datasets of gross primary productivity (GPP) and a satellite-derived Normalized Difference Vegetation Index (NDVI) to characterize recent changes in seasonal peak vegetation growth. The attribution of changes in peak growth to their driving factors was examined with several datasets. We demonstrated that the growth peak of global vegetation has been linearly increasing during the past three decades. About 65% of this trend is evenly explained by the expanding croplands (21%), rising atmospheric [CO2] (22%), and intensifying nitrogen deposition (22%). The contribution of expanding croplands to the peak growth trend was substantiated by measurements from eddy-flux towers, sun-induced chlorophyll fluorescence and a global database of plant traits, all of which demonstrated that croplands have a higher photosynthetic capacity than other vegetation types. The contribution of rising atmospheric [CO2] and nitrogen deposition are consistent with the positive response of leaf growth to elevated [CO2] (25%) and nitrogen addition (8%) from 346 manipulated experiments. The positive effect of rising atmospheric [CO2] was also well captured by 15 terrestrial biosphere models. However, most models underestimated the contributions of land-cover change and nitrogen deposition, but overestimated the positive effect of climate change.

  13. Interacting vegetative and thermal contributions to water movement in desert soil

    Science.gov (United States)

    Garcia, C.A.; Andraski, Brian J.; Stonestrom, David A.; Cooper, C.A.; Šimůnek, J.; Wheatcraft, S.W.

    2011-01-01

    Thermally driven water-vapor flow can be an important component of total water movement in bare soil and in deep unsaturated zones, but this process is often neglected when considering the effects of soil–plant–atmosphere interactions on shallow water movement. The objectives of this study were to evaluate the coupled and separate effects of vegetative and thermal-gradient contributions to soil water movement in desert environments. The evaluation was done by comparing a series of simulations with and without vegetation and thermal forcing during a 4.7-yr period (May 2001–December 2005). For vegetated soil, evapotranspiration alone reduced root-zone (upper 1 m) moisture to a minimum value (25 mm) each year under both isothermal and nonisothermal conditions. Variations in the leaf area index altered the minimum storage values by up to 10 mm. For unvegetated isothermal and nonisothermal simulations, root-zone water storage nearly doubled during the simulation period and created a persistent driving force for downward liquid fluxes below the root zone (total net flux ~1 mm). Total soil water movement during the study period was dominated by thermally driven vapor fluxes. Thermally driven vapor flow and condensation supplemented moisture supplies to plant roots during the driest times of each year. The results show how nonisothermal flow is coupled with plant water uptake, potentially influencing ecohydrologic relations in desert environments.

  14. Response of alpine vegetation growth dynamics to snow cover phenology on the Tibetan Plateau

    Science.gov (United States)

    Wang, X.; Wu, C.

    2017-12-01

    Alpine vegetation plays a crucial role in global energy cycles with snow cover, an essential component of alpine land cover showing high sensitivity to climate change. The Tibetan Plateau (TP) has a typical alpine vegetation ecosystem and is rich of snow resources. With global warming, the snow of the TP has undergone significant changes that will inevitably affect the growth of alpine vegetation, but observed evidence of such interaction is limited. In particular, a comprehensive understanding of the responses of alpine vegetation growth to snow cover variability is still not well characterized on TP region. To investigate this, we calculated three indicators, the start (SOS) and length (LOS) of growing season, and the maximum of normalized difference vegetation index (NDVImax) as proxies of vegetation growth dynamics from the Moderate Resolution Imaging Spectroradiometer (MODIS) data for 2000-2015. Snow cover duration (SCD) and melt (SCM) dates were also extracted during the same time frame from the combination of MODIS and the Interactive Multi-sensor Snow and Ice Mapping System (IMS) data. We found that the snow cover phenology had a strong control on alpine vegetation growth dynamics. Furthermore, the responses of SOS, LOS and NDVImax to snow cover phenology varied among plant functional types, eco-geographical zones, and temperature and precipitation gradients. The alpine steppes showed a much stronger negative correlation between SOS and SCD, and also a more evidently positive relationship between LOS and SCD than other types, indicating a longer SCD would lead to an earlier SOS and longer LOS. Most areas showed positive correlation between SOS and SCM, while a contrary response was also found in the warm but drier areas. Both SCD and SCM showed positive correlations with NDVImax, but the relationship became weaker with the increase of precipitation. Our findings provided strong evidences between vegetation growth and snow cover phenology, and changes in

  15. The Effect of Vegetation on Soil Water Infiltration and Retention Capacity by Improving Soil Physiochemical Property in Semi-arid Grassland

    Science.gov (United States)

    A, Y.; Wang, G.

    2017-12-01

    Water shortage is the main limiting factor for semi-arid grassland development. However, the grassland are gradually degraded represented by species conversion, biomass decrease and ecosystem structure simplification under the influence of human activity. Soil water characteristics such as moisture, infiltration and conductivity are critical variables affecting the interactions between soil parameters and vegetation. In this study, Cover, Height, Shannon-Wiener diversity index, Pielou evenness index and Richness index are served as indexes of vegetation productivity and community structure. And saturated hydraulic conductivity (Ks) and soil moisture content are served as indexes of soil water characters. The interaction between vegetation and soil water is investigated through other soil parameters, such as soil organic matter content at different vertical depths and in different degradation area (e.g., initial, transition and degraded plots). The results show that Ks significantly controlled by soil texture other than soil organic matter content. So the influence of vegetation on Ks through increasing soil organic content (SOM) might be slight. However, soil moisture content (SMC) appeared significantly positive relationship with SOM and silt content and negative relationship with sand content at all depth, significantly. This indicated that capacity of soil water storage was influenced both by soil texture and organic matter. In addition, the highest correlation coefficient of SMC was with SOM at the sub-surficial soil layer (20 40 cm). At the depth of 20 40 cm, the soil water content was relatively steady which slightly influenced by precipitation and evaporation. But it significantly influenced by soil organic matter content which related to vegetation. The correlation coefficient between SOM and SMC at topsoil layer (0 20 cm) was lowest (R2=0.36, pwater content not only by soil organic matter content but also the other influential factors, such as the root

  16. A framework for consistent estimation of leaf area index, fraction of absorbed photosynthetically active radiation, and surface albedo from MODIS time-series data

    DEFF Research Database (Denmark)

    Xiao, Zhiqiang; Liang, Shunlin; Wang, Jindi

    2015-01-01

    -series MODerate Resolution Imaging Spectroradiometer (MODIS) surface reflectance data. If the reflectance data showed snow-free areas, an ensemble Kalman filter (EnKF) technique was used to estimate leaf area index (LAI) for a two-layer canopy reflectance model (ACRM) by combining predictions from a phenology...... model and the MODIS surface reflectance data. The estimated LAI values were then input into the ACRM to calculate the surface albedo and the fraction of absorbed photosynthetically active radiation (FAPAR). For snow-covered areas, the surface albedo was calculated as the underlying vegetation canopy...... albedo plus the weighted distance between the underlying vegetation canopy albedo and the albedo over deep snow. The LAI/FAPAR and surface albedo values estimated using this framework were compared with MODIS collection 5 eight-day 1-km LAI/FAPAR products (MOD15A2) and 500-m surface albedo product (MCD43...

  17. Impact of vegetation variability on potential predictability and skill of EC-Earth simulations

    Energy Technology Data Exchange (ETDEWEB)

    Weiss, Martina; Hurk, Bart van den; Haarsma, Reindert; Hazeleger, Wilco [Royal Netherlands Meteorological Institute (KNMI), De Bilt (Netherlands)

    2012-12-15

    Climate models often use a simplified and static representation of vegetation characteristics to determine fluxes of energy, momentum and water vapour between surface and lower atmosphere. In order to analyse the impact of short term variability in vegetation phenology, we use remotely-sensed leaf area index and albedo products to examine the role of vegetation in the coupled land-atmosphere system. Perfect model experiments are carried out to determine the impact of realistic temporal variability of vegetation on potential predictability of evaporation and temperature, as well as model skill of EC-Earth simulations. The length of the simulation period is hereby limited by the availability of satellite products to 2000-2010. While a realistic representation of vegetation positively influences the simulation of evaporation and its potential predictability, a positive impact on 2 m temperature is of smaller magnitude, regionally confined and more pronounced in climatically extreme years. (orig.)

  18. Using MODIS-NDVI for the Modeling of Post-Wildfire Vegetation Response as a Function of Environmental Conditions and Pre-Fire Restoration Treatments

    Directory of Open Access Journals (Sweden)

    Grant M. Casady

    2012-03-01

    Full Text Available Post-fire vegetation response is influenced by the interaction of natural and anthropogenic factors such as topography, climate, vegetation type and restoration practices. Previous research has analyzed the relationship of some of these factors to vegetation response, but few have taken into account the effects of pre-fire restoration practices. We selected three wildfires that occurred in Bandelier National Monument (New Mexico, USA between 1999 and 2007 and three adjacent unburned control areas. We used interannual trends in the Normalized Difference Vegetation Index (NDVI time series data derived from the Moderate Resolution Imaging Spectroradiometer (MODIS to assess vegetation response, which we define as the average potential photosynthetic activity through the summer monsoon. Topography, fire severity and restoration treatment were obtained and used to explain post-fire vegetation response. We applied parametric (Multiple Linear Regressions-MLR and non-parametric tests (Classification and Regression Trees-CART to analyze effects of fire severity, terrain and pre-fire restoration treatments (variable used in CART on post-fire vegetation response. MLR results showed strong relationships between vegetation response and environmental factors (p < 0.1, however the explanatory factors changed among treatments. CART results showed that beside fire severity and topography, pre-fire treatments strongly impact post-fire vegetation response. Results for these three fires show that pre-fire restoration conditions along with local environmental factors constitute key processes that modify post-fire vegetation response.

  19. Development of a vegetable spreadable paste made from sorghum and millet whole grain flour

    Directory of Open Access Journals (Sweden)

    Nora Aimaretti

    2013-06-01

    Full Text Available Introduction: current nutritional guidelines recommend increasing the consumption of products based on whole grain cereals since they are rich in dietary fibers and bioactive components. The technological and sensory properties of these products are still a challenge for the food industry. The aim of the study was increase the availability of whole-grain based products through the development of aspreadable vegetable paste, pâté-type, suitable for the increasing celiac population.Material and Methods: sorghum and millet whole grain flours were obtained. The rest of the ingredients were evaluated and selected according to the characteristics desired for the product. The centesimal composition of the paste as well as its sensory properties and life time were analyzed.Results: the ingredients selected were (in %: margarine (16.7, sugar (1.1, salt (1.1, ascorbic acid (2.0, calcium propionate (0.3, pregelatinized starch (2.7, soy protein (25.1 and xanthan gum (0.5. The life time was followed for 28 days across (i chemical analysis of: humid (55.5-51.3%, p-value = 0.000741, peroxide index (<0.1 meqO2/Kg acid index (4.3-6.2 mgK(OH/g; (ii microbiological counts of: clostridium, Escherichia coli and Salmonella spp (absence, aerobic mesophiles, total coliforms, Staphylococcus aureus and moulds and yeasts which (<100; (iii sensory evaluation (acceptable.Conclusions: a spreadable paste was obtained which was 100% vegetable with organoleptic properties similar to those of a pâté, which can be stored for a period of 28 days.

  20. Understanding climate impacts on vegetation using a spatiotemporal non-linear Granger causality framework

    Science.gov (United States)

    Papagiannopoulou, Christina; Decubber, Stijn; Miralles, Diego; Demuzere, Matthias; Dorigo, Wouter; Verhoest, Niko; Waegeman, Willem

    2017-04-01

    Satellite data provide an abundance of information about crucial climatic and environmental variables. These data - consisting of global records, spanning up to 35 years and having the form of multivariate time series with different spatial and temporal resolutions - enable the study of key climate-vegetation interactions. Although methods which are based on correlations and linear models are typically used for this purpose, their assumptions for linearity about the climate-vegetation relationships are too simplistic. Therefore, we adopt a recently proposed non-linear Granger causality analysis [1], in which we incorporate spatial information, concatenating data from neighboring pixels and training a joint model on the combined data. Experimental results based on global data sets show that considering non-linear relationships leads to a higher explained variance of past vegetation dynamics, compared to simple linear models. Our approach consists of several steps. First, we compile an extensive database [1], which includes multiple data sets for land surface temperature, near-surface air temperature, surface radiation, precipitation, snow water equivalents and surface soil moisture. Based on this database, high-level features are constructed and considered as predictors in our machine-learning framework. These high-level features include (de-trended) seasonal anomalies, lagged variables, past cumulative variables, and extreme indices, all calculated based on the raw climatic data. Second, we apply a spatiotemporal non-linear Granger causality framework - in which the linear predictive model is substituted for a non-linear machine learning algorithm - in order to assess which of these predictor variables Granger-cause vegetation dynamics at each 1° pixel. We use the de-trended anomalies of Normalized Difference Vegetation Index (NDVI) to characterize vegetation, being the target variable of our framework. Experimental results indicate that climate strongly (Granger

  1. Assessing global vegetation activity using spatio-temporal Bayesian modelling

    Science.gov (United States)

    Mulder, Vera L.; van Eck, Christel M.; Friedlingstein, Pierre; Regnier, Pierre A. G.

    2016-04-01

    This work demonstrates the potential of modelling vegetation activity using a hierarchical Bayesian spatio-temporal model. This approach allows modelling changes in vegetation and climate simultaneous in space and time. Changes of vegetation activity such as phenology are modelled as a dynamic process depending on climate variability in both space and time. Additionally, differences in observed vegetation status can be contributed to other abiotic ecosystem properties, e.g. soil and terrain properties. Although these properties do not change in time, they do change in space and may provide valuable information in addition to the climate dynamics. The spatio-temporal Bayesian models were calibrated at a regional scale because the local trends in space and time can be better captured by the model. The regional subsets were defined according to the SREX segmentation, as defined by the IPCC. Each region is considered being relatively homogeneous in terms of large-scale climate and biomes, still capturing small-scale (grid-cell level) variability. Modelling within these regions is hence expected to be less uncertain due to the absence of these large-scale patterns, compared to a global approach. This overall modelling approach allows the comparison of model behavior for the different regions and may provide insights on the main dynamic processes driving the interaction between vegetation and climate within different regions. The data employed in this study encompasses the global datasets for soil properties (SoilGrids), terrain properties (Global Relief Model based on SRTM DEM and ETOPO), monthly time series of satellite-derived vegetation indices (GIMMS NDVI3g) and climate variables (Princeton Meteorological Forcing Dataset). The findings proved the potential of a spatio-temporal Bayesian modelling approach for assessing vegetation dynamics, at a regional scale. The observed interrelationships of the employed data and the different spatial and temporal trends support

  2. Single-Index Additive Vector Autoregressive Time Series Models

    KAUST Repository

    LI, YEHUA

    2009-09-01

    We study a new class of nonlinear autoregressive models for vector time series, where the current vector depends on single-indexes defined on the past lags and the effects of different lags have an additive form. A sufficient condition is provided for stationarity of such models. We also study estimation of the proposed model using P-splines, hypothesis testing, asymptotics, selection of the order of the autoregression and of the smoothing parameters and nonlinear forecasting. We perform simulation experiments to evaluate our model in various settings. We illustrate our methodology on a climate data set and show that our model provides more accurate yearly forecasts of the El Niño phenomenon, the unusual warming of water in the Pacific Ocean. © 2009 Board of the Foundation of the Scandinavian Journal of Statistics.

  3. Application of a regularized model inversion system (REGFLEC) to multi-temporal RapidEye imagery for retrieving vegetation characteristics

    KAUST Repository

    Houborg, Rasmus

    2015-10-14

    Accurate retrieval of canopy biophysical and leaf biochemical constituents from space observations is critical to diagnosing the functioning and condition of vegetation canopies across spatio-temporal scales. Retrieved vegetation characteristics may serve as important inputs to precision farming applications and as constraints in spatially and temporally distributed model simulations of water and carbon exchange processes. However significant challenges remain in the translation of composite remote sensing signals into useful biochemical, physiological or structural quantities and treatment of confounding factors in spectrum-trait relations. Bands in the red-edge spectrum have particular potential for improving the robustness of retrieved vegetation properties. The development of observationally based vegetation retrieval capacities, effectively constrained by the enhanced information content afforded by bands in the red-edge, is a needed investment towards optimizing the benefit of current and future satellite sensor systems. In this study, a REGularized canopy reFLECtance model (REGFLEC) for joint leaf chlorophyll (Chll) and leaf area index (LAI) retrieval is extended to sensor systems with a band in the red-edge region for the first time. Application to time-series of 5 m resolution multi-spectral RapidEye data is demonstrated over an irrigated agricultural region in central Saudi Arabia, showcasing the value of satellite-derived crop information at this fine scale for precision management. Validation against in-situ measurements in fields of alfalfa, Rhodes grass, carrot and maize indicate improved accuracy of retrieved vegetation properties when exploiting red-edge information in the model inversion process. © (2015) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE).

  4. Monitoring temporal Vegetation changes in Lao tropical forests

    International Nuclear Information System (INIS)

    Phompila, Chittana; Lewis, Megan; Clarke, Kenneth; Ostendorf, Bertram

    2014-01-01

    Studies on changes in vegetation are essential for understanding the interaction between humans and the environment. These studies provide key information for land use assessment, terrestrial ecosystem monitoring, carbon flux modelling and impacts of global climate change. The primary purpose of this study was to detect temporal vegetation changes in tropical forests in the southern part of Lao PDR from 2001-2012. The study investigated the annual vegetation phenological response of dominant land cover types across the study area and relationships to seasonal precipitation and temperature. Improved understanding of intra-annual patterns of vegetation variation was useful to detect longer term changes in vegetation. The breaks for additive season and trend (BFAST) approach was implemented to detect changes in these land cover types throughout the 2001-2012 period. We used the enhanced vegetation index (EVI) data from the Moderate Resolution Imaging Spectroradiometer (MODIS) (MOD13Q1 products) and monthly rainfall and temperature data obtained from the Meteorology and Hydrology Department, Ministry of Agriculture-Forestry, published by Lao National Statistical Centre in this research. EVI well documented the annual seasonal growth of vegetation and clearly distinguished the characteristic phenology of four different land use types; native forest, plantation, agriculture and mixed wooded/cleared area. Native forests maintained high EVI throughout the year, while plantations, wooded/cleared areas and agriculture showed greater inter-annual variation, with minimum EVI at the end of the dry season in April and maximum EVI in September-October, around two months after the wet season peak in rainfall. The BFAST analysis detected abrupt temporal changes in vegetation in the tropical forests, especially in a large conversion of mixed wooded/cleared area into plantation. Within the study area from 2001-2012 there has been an overall decreasing trend of vegetation cover for

  5. NDVI-Based analysis on the influence of human activities on vegetation variation on Hainan Island

    Science.gov (United States)

    Luo, Hongxia; Dai, Shengpei; Xie, Zhenghui; Fang, Jihua

    2018-02-01

    Using the Moderate Resolution Imaging Spectroradiometer-normalized difference vegetation index (NDVI) dataset, we analyzed the predicted NDVI values variation and the influence of human activities on vegetation on Hainan Island during 2001-2015. We investigated the roles of human activities in vegetation variation, particularly from 2002 when implemented the Grain-for-Greenprogram on Hainan Island. The trend analysis, linear regression model and residual analysis were used to analyze the data. The results of the study showed that (1) The predicted vegetation on Hainan Island showed an general upward trend with a linear growth rate of 0.0025/10y (phuman activities. (3) In general, human activities had played a positive role in the vegetation increase on Hainan Island, and the residual NDVI trend of this region showed positive outcomes for vegetation variation after implementing ecological engineering projects. However, it indicated a growing risk of vegetation degradation in the coastal region of Hainan Island as a result of rapid urbanization, land reclamation.

  6. Trend shifts in satellite-derived vegetation growth in Central Eurasia, 1982-2013.

    Science.gov (United States)

    Xu, Hao-Jie; Wang, Xin-Ping; Yang, Tai-Bao

    2017-02-01

    Central Eurasian vegetation is critical for the regional ecological security and the global carbon cycle. However, climatic impacts on vegetation growth in Central Eurasia are uncertain. The reason for this uncertainty lies in the fact that the response of vegetation to climate change showed nonlinearity, seasonality and differences among plant functional types. Based on remotely sensed vegetation index and in-situ meteorological data for the years 1982-2013, in conjunction with the latest land cover type product, we analyzed how vegetation growth trend varied across different seasons and evaluated vegetation response to climate variables at regional, biome and pixel scales. We found a persistent increase in the growing season NDVI over Central Eurasia during 1982-1994, whereas this greening trend has stalled since the mid-1990s in response to increased water deficit. The stalled trend in the growing season NDVI was largely attributed by summer and autumn NDVI changes. Enhanced spring vegetation growth after 2002 was caused by rapid spring warming. The response of vegetation to climatic factors varied in different seasons. Precipitation was the main climate driver for the growing season and summer vegetation growth. Changes in temperature and precipitation during winter and spring controlled the spring vegetation growth. Autumn vegetation growth was mainly dependent on the vegetation growth in summer. We found diverse responses of different vegetation types to climate drivers in Central Eurasia. Forests were more responsive to temperature than to precipitation. Grassland and desert vegetation responded more strongly to precipitation than to temperature in summer but more strongly to temperature than to precipitation in spring. In addition, the growth of desert vegetation was more dependent on winter precipitation than that of grasslands. This study has important implications for improving the performance of terrestrial ecosystem models to predict future vegetation

  7. Remote sensing time series analysis for crop monitoring with the SPIRITS software: new functionalities and use examples

    Directory of Open Access Journals (Sweden)

    Felix eRembold

    2015-07-01

    Full Text Available Monitoring crop and natural vegetation conditions is highly relevant, particularly in the food insecure areas of the world. Data from remote sensing image time series at high temporal and medium to low spatial resolution can assist this monitoring as they provide key information about vegetation status in near real-time over large areas. The Software for the Processing and Interpretation of Remotely sensed Image Time Series (SPIRITS is a stand-alone flexible analysis environment created to facilitate the processing and analysis of large image time series and ultimately for providing clear information about vegetation status in various graphical formats to crop production analysts and decision makers. In this paper we present the latest functional developments of SPIRITS and we illustrate recent applications. The main new developments include: HDF5 importer, Image re-projection, additional options for temporal Smoothing and Periodicity conversion, computation of a rainfall-based probability index (Standardized Precipitation Index for drought detection and extension of the Graph composer functionalities.In particular,. The examples of operational analyses are taken from several recent agriculture and food security monitoring reports and bulletins. We conclude with considerations on future SPIRITS developments also in view of the data processing requirements imposed by the coming generation of remote sensing products at high spatial and temporal resolution, such as those provided by the Sentinel sensors of the European Copernicus programme.

  8. Spatio-temporal variations of vegetation indicators in Eastern Siberia under global warming

    Science.gov (United States)

    Varlamova, Eugenia V.; Solovyev, Vladimir S.

    2017-11-01

    Study of spatio-temporal variations of NDVI (Normalized Difference Vegetation Index) and phenological parameters of Eastern Siberia vegetation cover under global warming was carried out on AVHRR/NOAA data (1982-2014). Trend maps of NDVI and annual variations of phenological parameters and NDVI are analyzed. A method based on stable transition of air temperature through +5°C was used to estimate the beginning, end and the length of the growing season. Correlation between NDVI and phenological parameters, surface air temperature and precipitation are discussed.

  9. Bioaccessibility and risk assessment of essential and non-essential elements in vegetables commonly consumed in Swaziland.

    Science.gov (United States)

    Mnisi, Robert Londi; Ndibewu, Peter P; Mafu, Lihle D; Bwembya, Gabriel C

    2017-10-01

    The green leafy vegetables (Mormodica involucrate, Bidens pilosa and Amaranthus spinosus) are economic; seasonal; locally grown and easily available; easy to propagate and store; highly nutritious food substances that form an important component of diets. This study applies a physiology based extraction technique (PBET) to mimic digestion of these vegetables to determine the fraction of essential (Fe and Zn) and non-essential elements (Cd, Cr and Pb) that are made available for absorption after ingestion. Prior to the application of the PBET, the vegetables were cooked adopting indigenous Swazi cooking methods. Cooking mobilized most of the metals out of the vegetable mass, and the final substrate concentrations are: raw > cooked > supernatant for all the metals, and the order of average metal leaching was: Pb (82.2%) >Cr (70.6%) >Zn (67.5%) >Fe (60.2%) >Cd (53.6%). This meant that the bioavailable concentrations are significantly lower than in the original vegetable mass, if only the solid mass is consumed. Bioaccessibility was higher in the gastric tract than in the intestinal phases of the PBET for all the metals in all the vegetables. Risk assessment protocols employed on the non-essential elements (Cr, Cd and Pb) showed that the associated risks of ingesting metal contaminated vegetables are higher for children, than they are for adults, based on the target hazard quotient (THQ) index. However, the overall health risk associated with ingestion of these metals is low, for both children and adults, based on the HR index. Conclusively, this study expounds on the nutritional and risk benefits associated with ingesting naturally grown vegetables. Copyright © 2017 Elsevier Inc. All rights reserved.

  10. [Comparison of precision in retrieving soybean leaf area index based on multi-source remote sensing data].

    Science.gov (United States)

    Gao, Lin; Li, Chang-chun; Wang, Bao-shan; Yang Gui-jun; Wang, Lei; Fu, Kui

    2016-01-01

    With the innovation of remote sensing technology, remote sensing data sources are more and more abundant. The main aim of this study was to analyze retrieval accuracy of soybean leaf area index (LAI) based on multi-source remote sensing data including ground hyperspectral, unmanned aerial vehicle (UAV) multispectral and the Gaofen-1 (GF-1) WFV data. Ratio vegetation index (RVI), normalized difference vegetation index (NDVI), soil-adjusted vegetation index (SAVI), difference vegetation index (DVI), and triangle vegetation index (TVI) were used to establish LAI retrieval models, respectively. The models with the highest calibration accuracy were used in the validation. The capability of these three kinds of remote sensing data for LAI retrieval was assessed according to the estimation accuracy of models. The experimental results showed that the models based on the ground hyperspectral and UAV multispectral data got better estimation accuracy (R² was more than 0.69 and RMSE was less than 0.4 at 0.01 significance level), compared with the model based on WFV data. The RVI logarithmic model based on ground hyperspectral data was little superior to the NDVI linear model based on UAV multispectral data (The difference in E(A), R² and RMSE were 0.3%, 0.04 and 0.006, respectively). The models based on WFV data got the lowest estimation accuracy with R2 less than 0.30 and RMSE more than 0.70. The effects of sensor spectral response characteristics, sensor geometric location and spatial resolution on the soybean LAI retrieval were discussed. The results demonstrated that ground hyperspectral data were advantageous but not prominent over traditional multispectral data in soybean LAI retrieval. WFV imagery with 16 m spatial resolution could not meet the requirements of crop growth monitoring at field scale. Under the condition of ensuring the high precision in retrieving soybean LAI and working efficiently, the approach to acquiring agricultural information by UAV remote

  11. Empirical behavior of a world stock index from intra-day to monthly time scales

    Science.gov (United States)

    Breymann, W.; Lüthi, D. R.; Platen, E.

    2009-10-01

    Most of the papers that study the distributional and fractal properties of financial instruments focus on stock prices or foreign exchange rates. This typically leads to mixed results concerning the distributions of log-returns and some multi-fractal properties of exchange rates, stock prices, and regional indices. This paper uses a well diversified world stock index as the central object of analysis. Such index approximates the growth optimal portfolio, which is demonstrated under the benchmark approach, it is the ideal reference unit for studying basic securities. When denominating this world index in units of a given currency, one measures the movements of the currency against the entire market. This provides a least disturbed observation of the currency dynamics. In this manner, one can expect to disentangle, e.g., the superposition of the two currencies involved in an exchange rate. This benchmark approach to the empirical analysis of financial data allows us to establish remarkable stylized facts. Most important is the observation that the repeatedly documented multi-fractal appearance of financial time series is very weak and much less pronounced than the deviation of the mono-scaling properties from Brownian-motion type scaling. The generalized Hurst exponent H(2) assumes typical values between 0.55 and 0.6. Accordingly, autocorrelations of log-returns decay according to a power law, and the quadratic variation vanishes when going to vanishing observation time step size. Furthermore, one can identify the Student t distribution as the log-return distribution of a well-diversified world stock index for long time horizons when a long enough data series is used for estimation. The study of dependence properties, finally, reveals that jumps at daily horizon originate primarily in the stock market while at 5min horizon they originate in the foreign exchange market. The principal message of the empirical analysis is that there is evidence that a diffusion model

  12. Monitoring Invasive Aquatic Vegetation in Lake Okeechobee, Florida, Using NDVI Derived from Modis Data

    Science.gov (United States)

    Woods, Kate; Brozen, Madeline; Malik, Sadaf; Maki, Angela

    2009-01-01

    Lake Okeechobee, located in southern Florida, encompasses approximately 1,700 sq km and is a vital part of the Lake Okeechobee and Everglades ecosystem. Major cyanobacterial blooms have been documented in Lake Okeechobee since the 1970s and have continued to plague the ecosystem. Similarly, hydrilla, water hyacinth, and water lettuce have been documented in the lake and continue to threaten the ecosystem by their rapid growth. This study examines invasive aquatic vegetation occurrence through the use of the Normalized Difference Vegetation Index (NDVI) calculated on MOD09 surface reflectance imagery. Occurrence during 2008 was analyzed using the Time Series Product Tool (TSPT), a MATLAB-based program developed at John C. Stennis Space Center. This project tracked spatial and temporal variability of cyanobacterial blooms, and overgrowth of water lettuce, water hyacinth, and hydrilla. In addition, this study presents an application of Moderate Resolution Imaging Spectroradiometer (MODIS) data to assist in water quality management.

  13. Impact of Vegetation Cover Fraction Parameterization schemes on Land Surface Temperature Simulation in the Tibetan Plateau

    Science.gov (United States)

    Lv, M.; Li, C.; Lu, H.; Yang, K.; Chen, Y.

    2017-12-01

    The parameterization of vegetation cover fraction (VCF) is an important component of land surface models. This paper investigates the impacts of three VCF parameterization schemes on land surface temperature (LST) simulation by the Common Land Model (CoLM) in the Tibetan Plateau (TP). The first scheme is a simple land cover (LC) based method; the second one is based on remote sensing observation (hereafter named as RNVCF) , in which multi-year climatology VCFs is derived from Moderate-resolution Imaging Spectroradiometer (MODIS) NDVI (Normalized Difference Vegetation Index); the third VCF parameterization scheme derives VCF from the LAI simulated by LSM and clump index at every model time step (hereafter named as SMVCF). Simulated land surface temperature(LST) and soil temperature by CoLM with three VCF parameterization schemes were evaluated by using satellite LST observation and in situ soil temperature observation, respectively, during the period of 2010 to 2013. The comparison against MODIS Aqua LST indicates that (1) CTL produces large biases for both four seasons in early afternoon (about 13:30, local solar time), while the mean bias in spring reach to 12.14K; (2) RNVCF and SMVCF reduce the mean bias significantly, especially in spring as such reduce is about 6.5K. Surface soil temperature observed at 5 cm depth from three soil moisture and temperature monitoring networks is also employed to assess the skill of three VCF schemes. The three networks, crossing TP from West to East, have different climate and vegetation conditions. In the Ngari network, located in the Western TP with an arid climate, there are not obvious differences among three schemes. In Naqu network, located in central TP with a semi-arid climate condition, CTL shows a severe overestimates (12.1 K), but such overestimations can be reduced by 79% by RNVCF and 87% by SMVCF. In the third humid network (Maqu in eastern TP), CoLM performs similar to Naqu. However, at both Naqu and Maqu networks

  14. Wetland habitat disturbance best predicts metrics of an amphibian index of biotic integrity

    Science.gov (United States)

    Stapanian, Martin A.; Micacchion, Mick; Adams, Jean V.

    2015-01-01

    Regression and classification trees were used to identify the best predictors of the five component metrics of the Ohio Amphibian Index of Biotic Integrity (AmphIBI) in 54 wetlands in Ohio, USA. Of the 17 wetland- and surrounding landscape-scale variables considered, the best predictor for all AmphIBI metrics was habitat alteration and development within the wetland. The results were qualitatively similar to the best predictors for a wetland vegetation index of biotic integrity, suggesting that similar management practices (e.g., reducing or eliminating nutrient enrichment from agriculture, mowing, grazing, logging, and removing down woody debris) within the boundaries of the wetland can be applied to effectively increase the quality of wetland vegetation and amphibian communities.

  15. Upscaling from leaf to canopy chlorophyll/carotenoid pigment based vegetation indices reveal phenology of photosynthesis in temperate evergreen and deciduous trees

    Science.gov (United States)

    Wong, C. Y.; Bhathena, Y.; Arain, M. A.; Ensminger, I.

    2017-12-01

    Optically derived vegetation indices have been developed to provide information about plant status including photosynthetic activity. They reflect changes in leaf pigments, which vary seasonally in pigment composition, enabling them to be used as a proxy of photosynthetic phenology. Important pigments in photosynthetic activity are carotenoids and chlorophylls, which are associated with light harvesting and energy dissipation. In temperate forests, which consist of deciduous and evergreen trees, there are difficulties resolving evergreen phenology using the most widely used index, the normalized difference vegetation index (NDVI). NDVI works well in deciduous trees, which exhibit a "visible" phenological process of leaf growth in the spring, and leaf senescence and abscission in the autumn. Evergreen conifers stay green year-round and utilize "invisible" changes of overwintering pigment composition that NDVI cannot resolve, so carotenoid pigment sensitive vegetation indices have been suggested for evergreens. The aim of this study was to evaluate carotenoid based vegetation indices over the chlorophyll sensitive NDVI. For this purpose, we evaluated the greenness index, NDVI, and carotenoid pigment sensitive indices: photochemical reflectance index (PRI) and chlorophyll/carotenoid index (CCI) in red maple, white oak and eastern white pine for two years. We also measured leaf gas exchange and pigment concentrations. We observed that NDVI correlated with photosynthetic activity in deciduous trees, whereas PRI and CCI correlated with photosynthesis across both evergreen and deciduous trees. This pattern was consistent, upscaling from leaf- to canopy-scales indicating that the mechanisms involved in winter acclimation can be resolved at larger spatial scales. PRI and CCI detected seasonal changes in carotenoids and chlorophylls linked to photoprotection and are suitable as a proxy of photosynthetic activity. These findings have implications to improve our use and

  16. Effect of storage temperature and time on the vitamin C contents of selected fruits and vegetables

    International Nuclear Information System (INIS)

    Firdous, S.; Abdullah, N.; Alim-un-Nisa; Ejaz, N.

    2010-01-01

    The vitamin C contents of 5 fruits and 7 vegetables, as a whole and in diced form, were determined by HPLC during cold storage. Results showed a decrease in vitamin C contents during 15 days refrigeration (7 deg. C) as well as freezing at -20 deg. C. It was found that fruits are more stable than vegetables since the rate of degradation of vitamin C was higher in vegetables as compared to fruits, either during freezing or refrigeration. During 15 days freezing, fruits showed a decrease of 41.05 - 51.44%, whereas, this loss augmented to 54.12 - 89.10% in vegetables. In addition to this, it was also observed that fruits and vegetables which have peels are less vulnerable to vitamin C degradation; the ratio of degradation of vitamin C in all the fruits studied and potato was not more than 51.44%. In fruits, apple was more susceptible and in vegetables, potato was more stable to vitamin C degradation. (author)

  17. Deriving crop calendar using NDVI time-series

    Science.gov (United States)

    Patel, J. H.; Oza, M. P.

    2014-11-01

    Agricultural intensification is defined in terms as cropping intensity, which is the numbers of crops (single, double and triple) per year in a unit cropland area. Information about crop calendar (i.e. number of crops in a parcel of land and their planting & harvesting dates and date of peak vegetative stage) is essential for proper management of agriculture. Remote sensing sensors provide a regular, consistent and reliable measurement of vegetation response at various growth stages of crop. Therefore it is ideally suited for monitoring purpose. The spectral response of vegetation, as measured by the Normalized Difference Vegetation Index (NDVI) and its profiles, can provide a new dimension for describing vegetation growth cycle. The analysis based on values of NDVI at regular time interval provides useful information about various crop growth stages and performance of crop in a season. However, the NDVI data series has considerable amount of local fluctuation in time domain and needs to be smoothed so that dominant seasonal behavior is enhanced. Based on temporal analysis of smoothed NDVI series, it is possible to extract number of crop cycles per year and their crop calendar. In the present study, a methodology is developed to extract key elements of crop growth cycle (i.e. number of crops per year and their planting - peak - harvesting dates). This is illustrated by analysing MODIS-NDVI data series of one agricultural year (from June 2012 to May 2013) over Gujarat. Such an analysis is very useful for analysing dynamics of kharif and rabi crops.

  18. Woody plants diversity and type of vegetation in non cultivated plain of Moutourwa, Far-North, Cameroon

    Directory of Open Access Journals (Sweden)

    Gilbert Todou

    2016-12-01

    Full Text Available In order to valorize the wild vegetal resources for the efficient conservation and sustainable use in sahelo-sudanian zone in Cameroon, a study of non cultivated plain of Moutourwa was carry out to assess the floristic richness, the specific diversity and the type of vegetation. The inventory of all trees and shrubs (dbh ? 2.5 cm and the determination of the vegetation cover were done in five linear transects (20 m × 1000 m. In total, 27 families, 54 genera and 75 species were found. Caesalpinaceae is the most abundant family that relative abundance (pi*100 is 34.41%, the most abundant genus was Piliostigma (pi*100 = 30.66% and the most represented species was Piliostigma reticulatum (pi*100 = 29.56%; D = 53.6 stems/ha. The Simpson index (E= 0.89, the Shannon index (H= 3.2 and the equitability index of Pielou (J= 0.74 indicated that there were moderate diversity with more or less equitable species. The wild fruits species were numerous (pi*100 = 32.76%; D = 59.7 stems/ha. A. senegalensis is was the most represented (pi*100 = 9.04 ; D = 16.4 followed by Hexalobus monopetalus (pi*100 = 5.16 ; D = 9.4 and Balanites aegyptiaca (pi*100 = 3.69 ; D = 6.7. These results contribute efficaciously to valorize the wild vegetal resources for efficient conservation and sustainable use. Keywords: Woody plants diversity, conservation, sustainable use, sahelo-sudanian, Moutourwa

  19. An application of plot-scale NDVI in predicting carbon dioxide exchange and leaf area index in heterogeneous subarctic tundra

    Energy Technology Data Exchange (ETDEWEB)

    Dagg, J.; Lafleur, P.

    2010-07-01

    This paper reported on a study that examined the flow of carbon into and out of tundra ecosystems. It is necessary to accurately predict carbon dioxide (CO{sub 2}) exchange in the Tundra because of the impacts of climate change on carbon stored in permafrost. Understanding the relationships between the normalized difference vegetation index (NDVI) and vegetation and CO{sub 2} exchange may explain how small-scale variation in vegetation community extends to remotely sensed estimates of landscape characteristics. In this study, CO{sub 2} fluxes were measured with a portable chamber in a range of Tundra vegetation communities. Biomass and leaf area were measured with destructive harvest, and NDVI was obtained using a hand-held infrared camera. There was a weak correlation between NDVI and leaf area index in some vegetation communities, but a significant correlation between NDVI and biomass, including mosses. NDVI was found to be strongly related to photosynthetic activity and net CO{sub 2} uptake in all vegetation groups. However, NDVI related to ecosystem respiration only in wet sedge. It was concluded that at plot scale, the ability of NDVI to predict ecosystem properties and CO{sub 2} exchange in heterogeneous Tundra vegetation is variable.

  20. An application of plot-scale NDVI in predicting carbon dioxide exchange and leaf area index in heterogeneous subarctic tundra

    International Nuclear Information System (INIS)

    Dagg, J.; Lafleur, P.

    2010-01-01

    This paper reported on a study that examined the flow of carbon into and out of tundra ecosystems. It is necessary to accurately predict carbon dioxide (CO 2 ) exchange in the Tundra because of the impacts of climate change on carbon stored in permafrost. Understanding the relationships between the normalized difference vegetation index (NDVI) and vegetation and CO 2 exchange may explain how small-scale variation in vegetation community extends to remotely sensed estimates of landscape characteristics. In this study, CO 2 fluxes were measured with a portable chamber in a range of Tundra vegetation communities. Biomass and leaf area were measured with destructive harvest, and NDVI was obtained using a hand-held infrared camera. There was a weak correlation between NDVI and leaf area index in some vegetation communities, but a significant correlation between NDVI and biomass, including mosses. NDVI was found to be strongly related to photosynthetic activity and net CO 2 uptake in all vegetation groups. However, NDVI related to ecosystem respiration only in wet sedge. It was concluded that at plot scale, the ability of NDVI to predict ecosystem properties and CO 2 exchange in heterogeneous Tundra vegetation is variable.

  1. Bayesian estimation of seasonal course of canopy leaf area index from hyperspectral satellite data

    Science.gov (United States)

    Varvia, Petri; Rautiainen, Miina; Seppänen, Aku

    2018-03-01

    In this paper, Bayesian inversion of a physically-based forest reflectance model is investigated to estimate of boreal forest canopy leaf area index (LAI) from EO-1 Hyperion hyperspectral data. The data consist of multiple forest stands with different species compositions and structures, imaged in three phases of the growing season. The Bayesian estimates of canopy LAI are compared to reference estimates based on a spectral vegetation index. The forest reflectance model contains also other unknown variables in addition to LAI, for example leaf single scattering albedo and understory reflectance. In the Bayesian approach, these variables are estimated simultaneously with LAI. The feasibility and seasonal variation of these estimates is also examined. Credible intervals for the estimates are also calculated and evaluated. The results show that the Bayesian inversion approach is significantly better than using a comparable spectral vegetation index regression.

  2. WAVEFORM ANALYSIS FOR THE EXTRACTION OF POST-FIRE VEGETATION CHARACTERISTICS

    Directory of Open Access Journals (Sweden)

    F. Pirotti

    2012-08-01

    Full Text Available Full-waveform is becoming increasingly available in today's LiDAR systems and the analysis of the full return signal can provide additional information on the reflecting surfaces. In this paper we present the results of an assessment on full-waveform analysis, as opposed to the more classic discrete return analysis, for discerning vegetation cover classes related to post-fire renovation. In the spring of 2011 an OPTECH ALTM sensor was used to survey an Alpine area of almost 20 km2 in the north of Italy. A forest fire event several years ago burned large patches of vegetation for a total of about 1.5 km2 . The renovation process in the area is varied because of the different interventions ranging from no intervention to the application of re-forestation techniques to accelerate the process of re-establishing protection forest. The LiDAR data was used to divide the study site into areas with different conditions in terms of re-establishment of the natural vegetation condition. The LiDAR survey provided both the full-waveform data in Optech's CSD+DGT (corrected sensor data and NDF+IDX (digitizer data with index file formats, and the discrete return in the LAS format. The method applied to the full-waveform uses canopy volume profiles obtained by modelling, whereas the method applied to discrete return uses point geometry and density indexes. The results of these two methods are assessed by ground truth obtained from sampling and comparison shows that the added information from the full-waveform does give a significant better discrimination of the vegetation cover classes.

  3. Review of Alternative Management Options of Vegetable Crop Residues to Reduce Nitrate Leaching in Intensive Vegetable Rotations

    Directory of Open Access Journals (Sweden)

    Laura Agneessens

    2014-12-01

    Full Text Available Vegetable crop residues take a particular position relative to arable crops due to often large amounts of biomass with a N content up to 200 kg N ha−1 left behind on the field. An important amount of vegetable crops are harvested during late autumn and despite decreasing soil temperatures during autumn, high rates of N mineralization and nitrification still occur. Vegetable crop residues may lead to considerable N losses through leaching during winter and pose a threat to meeting water quality objectives. However, at the same time vegetable crop residues are a vital link in closing the nutrient and organic matter cycle of soils. Appropriate and sustainable management is needed to harness the full potential of vegetable crop residues. Two fundamentally different crop residue management strategies to reduce N losses during winter in intensive vegetable rotations are reviewed, namely (i on-field management options and modifications to crop rotations and (ii removal of crop residues, followed by a useful and profitable application.

  4. The Vegetation Trends and Drivers in Beijing-Tianjing Region from 1982 TO 2013 Based on Time Series Gimms NDVI3g

    Science.gov (United States)

    Liu, S.; Tian, H.; Wang, X.; Li, H.; He, Y.

    2018-04-01

    Vegetation plays a leading role in ecosystems. Plant communities are the main components of ecosystems. Green plants in ecosystems are the primary producers, and they provide the living organic matter for the survival of other organisms. The dynamics of most landscapes are driven by both natural processes and human activities. In this study, the growing season GIMMS NDVI3g and climatic data were used to analyse the vegetation trends and drivers in Beijing-Tianjin-Hebei region from 1982 to 2013. Result shows that, the vegetation in Beijing-Tianjin-Hebei region shows overall restoration and partial degradation trend. The significant restoration region accounts for 61.5 % of Beijing-Tianjin-Hebei region, while the significant degradation region accounts for 2.1 %. The dominant climatic factor for time series NDVI were analyzed using the multi-linear regression model. Vegetation growth in 17.9 % of Beijing-Tianjin-Hebei region is dominated by temperature, 35.5 % is dominated by precipitation, and 11.68 % is dominated by solar radiance. Human activities play important role for vegetation restoration in Beijing-Tianjin-Hebei Region, where the large scale forest restoration programs are the main human activities, such as the three-north shelterbelt construction project, Beijing-Tianjin-Hebei sandstorm source control project and grain for green projects.

  5. Detecting Historical Vegetation Changes in the Dunhuang Oasis Protected Area Using Landsat Images

    Directory of Open Access Journals (Sweden)

    Xiuxia Zhang

    2017-09-01

    Full Text Available Abstract: Given its proximity to an artificial oasis, the Donghu Nature Reserve in the Dunhuang Oasis has faced environmental pressure and vegetation disturbances in recent decades. Satellite vegetation indices (VIs can be used to detect such changes in vegetation if the satellite images are calibrated to surface reflectance (SR values. The aim of this study was to select a suitable VI based on the Landsat Climate Data Record (CDR products and the absolute radiation-corrected results of Landsat L1T images to detect the spatio-temporal changes in vegetation for the Donghu Reserve during 1986–2015. The results showed that the VI difference (ΔVI images effectively reduced the changes in the source images. Compared with the other VIs, the soil-adjusted vegetation index (SAVI displayed greater robustness to atmospheric effects in the two types of SR images and was more responsive to vegetation changes caused by human factors. From 1986 to 2015, the positive changes in vegetation dominated the overall change trend, with changes in vegetation in the reserve decreasing during 1990–1995, increasing until 2005–2010, and then decreasing again. The vegetation changes were mainly distributed at the edge of the artificial oasis outside the reserve. The detected changes in vegetation in the reserve highlight the increased human pressure on the reserve.

  6. Vegetation Removal from Uav Derived Dsms, Using Combination of RGB and NIR Imagery

    Science.gov (United States)

    Skarlatos, D.; Vlachos, M.

    2018-05-01

    Current advancements on photogrammetric software along with affordability and wide spreading of Unmanned Aerial Vehicles (UAV), allow for rapid, timely and accurate 3D modelling and mapping of small to medium sized areas. Although the importance and applications of large format aerial overlaps cameras and photographs in Digital Surface Model (DSM) production and LIDAR data is well documented in literature, this is not the case for UAV photography. Additionally, the main disadvantage of photogrammetry is the inability to map the dead ground (terrain), when we deal with areas that include vegetation. This paper assesses the use of near-infrared imagery captured by small UAV platforms to automatically remove vegetation from Digital Surface Models (DSMs) and obtain a Digital Terrain Model (DTM). Two areas were tested, based on the availability of ground reference points, both under trees and among vegetation, as well as on terrain. In addition, RGB and near-infrared UAV photography was captured and processed using Structure from Motion (SfM) and Multi View Stereo (MVS) algorithms to generate DSMs and corresponding colour and NIR orthoimages with 0.2 m and 0.25 m as pixel size respectively for the two test sites. Moreover, orthophotos were used to eliminate the vegetation from the DSMs using NDVI index, thresholding and masking. Following that, different interpolation algorithms, according to the test sites, were applied to fill in the gaps and created DTMs. Finally, a statistic analysis was made using reference terrain points captured on field, both on dead ground and under vegetation to evaluate the accuracy of the whole process and assess the overall accuracy of the derived DTMs in contrast with the DSMs.

  7. Assessment on the Contamination Status of Heavy Metals in Some Vegetables Growing Areas of Guangdong Province, China

    Directory of Open Access Journals (Sweden)

    WANG Fo-jiao

    2014-10-01

    Full Text Available We detected lead and cadmium in 1 465 vegetable samples of 18 vegetable species collected from 516 vegetable planting bases in Guangdong Province. The results showed that the highest average contents of lead from water spinach(Ipomoeaaquaticswas 0.11 mg·kg -1 in all species of vegetable samples. The highest average contents of cadmium from water cress(Nasturtium officinale R.Br.was 0.060 mg·kg -1 in all species of vegetable samples. The qualified rate of lead in all samples was 97.0%. The qualified rate of cadmium in all samples was 98.9%.The average pollution indexes of lead and cadmium in these species of vegetable were less than 0.7. The heavy metal security status of all veg-etables from these bases in Guangdong Province were at the excellent level.

  8. Výzkum dlouhodobých změn hodnot vegetačních indexů

    OpenAIRE

    Beránková, Petra

    2010-01-01

    The work deals with the issue of research of long-term changes of vegetation indices concretely indices NDVI (Normalized Difference Vegetation Index). The first part is devoted to detailed analysis of domestic and foreign literature, which deals with the calculation and interpretation of vegetation indices values. The main theme of this work is to explore relation between temperature and NDVI changes and precipitation and NDVI changes over the period 1982-2006. These connections are examined ...

  9. Quantifying the role of vegetation in controlling the time-variant age of evapotranspiration, soil water and stream flow

    Science.gov (United States)

    Smith, A.; Tetzlaff, D.; Soulsby, C.

    2017-12-01

    Identifying the sources of water which sustain plant water uptake is an essential prerequisite to understanding the interactions of vegetation and water within the critical zone. Estimating the sources of root-water uptake is complicated by ecohydrological separation, or the notion of "two-water worlds" which distinguishes more mobile and immobile water sources which respectively sustain streamflow and evapotranspiration. Water mobility within the soil determines both the transit time/residence time of water through/in soils and the subsequent age of root-uptake and xylem water. We used time-variant StorAge Selection (SAS) functions to conceptualise the transit/residence times in the critical zone using a dual-storage soil column differentiating gravity (mobile) and tension dependent (immobile) water, calibrated to measured stable isotope signatures of soil water. Storage-discharge relationships [Brutsaert and Nieber, 1977] were used to identify gravity and tension dependent storages. A temporally variable distribution for root water uptake was identified using simulated stable isotopes in xylem and soil water. Composition of δ2H and δ18O was measured in soil water at 4 depths (5, 10, 15, and 20 cm) on 10 occasions, and 5 times for xylem water within the dominant heather (Calluna sp. and Erica sp.) vegetation in a Scottish Highland catchment over a two-year period. Within a 50 cm soil column, we found that more than 53% of the total stored water was water that was present before the start of the simulation. Mean residence times of the mobile water in the upper 20 cm of the soil were 16, 25, 36, and 44 days, respectively. Mean evaporation transit time varied between 9 and 40 days, driven by seasonal changes and precipitation events. Lastly, mean transit times of xylem water ranged between 95-205 days, driven by changes in soil moisture. During low soil moisture (i.e. lower than mean soil moisture), root-uptake was from lower depths, while higher than mean soil

  10. Cross-correlation and time history analysis of laser dynamic specklegram imaging for quality evaluation and assessment of certain seasonal fruits and vegetables

    Science.gov (United States)

    Samuel, Boni; Retheesh, R.; Zaheer Ansari, Md; Nampoori, V. P. N.; Radhakrishnan, P.; Mujeeb, A.

    2017-10-01

    Quality evaluation of fruits and vegetables is of great concern as there is a shortage of unadulterated items on the market. Even unadulterated fruits and vegetables, especially those with soft tissue, cannot be stored for longer times due to physical and chemical changes. Moreover, damage can occur during harvest and in the post-harvest period, while preserving or transporting the fruits and vegetables. This work describes the use of a laser dynamic speckle imaging technique as a powerful optoelectronic tool for the quality evaluation of certain seasonal fruits and vegetables in an Indian market. A simple optical configuration was designed for developing the dynamic speckle imagining system to record dynamic specklegrams of the specimens under different conditions. These images were analysed using a cross-correlation function and the temporal history of specklegrams. The technique can be effectively adapted to the industrial environment and would be beneficial for all stakeholders in the field.

  11. Global assessment of experimental climate warming on tundra vegetation: heterogeneity over space and time

    Science.gov (United States)

    Sarah C. Elmendorf; Gregory H.R. Henry; Robert D. Hollister; Robert G. Björk; Anne D. Bjorkman; Terry V. Callaghan; [and others] NO-VALUE; William Gould; Joel Mercado

    2012-01-01

    Understanding the sensitivity of tundra vegetation to climate warming is critical to forecasting future biodiversity and vegetation feedbacks to climate. In situ warming experiments accelerate climate change on a small scale to forecast responses of local plant communities. Limitations of this approach include the apparent site-specificity of results and uncertainty...

  12. Monitoring Springs in the Mojave Desert Using Landsat Time Series Analysis

    Science.gov (United States)

    Potter, Christopher S.

    2018-01-01

    The purpose of this study, based on Landsat satellite data was to characterize variations and trends over 30 consecutive years (1985-2016) in perennial vegetation green cover at over 400 confirmed Mojave Desert spring locations. These springs were surveyed between in 2015 and 2016 on lands managed in California by the U.S. Bureau of Land Management (BLM) and on several land trusts within the Barstow, Needles, and Ridgecrest BLM Field Offices. The normalized difference vegetation index (NDVI) from July Landsat images was computed at each spring location and a trend model was first fit to the multi-year NDVI time series using least squares linear regression.Â

  13. Terrestrial Water Storage and Vegetation Resilience to Drought

    Science.gov (United States)

    Meyer, V.; Reager, J. T., II; Konings, A. G.

    2017-12-01

    The expected increased occurrences of hydrologic extreme events such as droughts in the coming decades motivates studies to better understand and predict the response of vegetation to such extreme conditions. Previous studies have addressed vegetation resilience to drought, defined as its ability to recover from a perturbation (Hirota et al., 2011; Vicente-Serrano et al., 2012), but appear to only focus on precipitation and a couple of vegetation indices, hence lacking a key element: terrestrial water storage (TWS). In this study, we combine and compare multiple remotely-sensed hydro-ecological datasets providing information on climatic and hydrological conditions (Tropical Rainfall Measuring Mission (TRMM), Gravity Recovery and Climate Experiment (GRACE)) and indices characterizing the state of the vegetation (vegetation water content using Vegetation Optical Depth (VOD) from SMAP (Soil Moisture Active and Passive), Gross Primary Production (GPP) from FluxCom and Specific Fluorescence Intensity (SFI, from GOSat)) to assess the ability of vegetation to face and recover from droughts across the globe. Our results suggest that GRACE hydrological data bridge the knowledge gap between precipitation deficit and vegetation response. All products are aggregated at a 0.5º spatial resolution and a monthly temporal resolution to match the GRACE Mascon product. Despite these coarse spatiotemporal resolutions, we find that the relationship between existing remotely-sensed eco-hydrologic data varies spatially, both in terms of strength of relationship and time lag, showing the response time of vegetation characteristics to hydrological changes and highlighting the role of water storage. A special attention is given to the Amazon river basin, where two well documented droughts occurred in 2005 and 2010, and where a more recent drought occurred in 2015/2016. References : Hirota, Marina, et al. "Global resilience of tropical forest and savanna to critical transitions." Science

  14. The Potential of Forest Biomass Inversion Based on Vegetation Indices Using Multi-Angle CHRIS/PROBA Data

    Directory of Open Access Journals (Sweden)

    Qiang Wang

    2016-10-01

    Full Text Available Multi-angle remote sensing can either be regarded as an added source of uncertainty for variable retrieval, or as a source of additional information, which enhances variable retrieval compared to traditional single-angle observation. However, the magnitude of these angular and band effects for forest structure parameters is difficult to quantify. We used the Discrete Anisotropic Radiative Transfer (DART model and the Zelig model to simulate the forest canopy Bidirectional Reflectance Distribution Factor (BRDF in order to build a look-up table, and eight vegetation indices were used to assess the relationship between BRDF and forest biomass in order to find the sensitive angles and bands. Further, the European Space Agency (ESA mission, Compact High Resolution Imaging Spectrometer onboard the Project for On-board Autonomy (CHRIS-PROBA and field sample measurements, were selected to test the angular and band effects on forest biomass retrieval. The results showed that the off-nadir vegetation indices could predict the forest biomass more accurately than the nadir. Additionally, we found that the viewing angle effect is more important, but the band effect could not be ignored, and the sensitive angles for extracting forest biomass are greater viewing angles, especially around the hot and dark spot directions. This work highlighted the combination of angles and bands, and found a new index based on the traditional vegetation index, Atmospherically Resistant Vegetation Index (ARVI, which is calculated by combining sensitive angles and sensitive bands, such as blue band 490 nm/−55°, green band 530 nm/55°, and the red band 697 nm/55°, and the new index was tested to improve the accuracy of forest biomass retrieval. This is a step forward in multi-angle remote sensing applications for mining the hidden relationship between BRDF and forest structure information, in order to increase the utilization efficiency of remote sensing data.

  15. Past and future effects of climate change on spatially heterogeneous vegetation activity in China

    Science.gov (United States)

    Gao, Jiangbo; Jiao, Kewei; Wu, Shaohong; Ma, Danyang; Zhao, Dongsheng; Yin, Yunhe; Dai, Erfu

    2017-07-01

    Climate change is a major driver of vegetation activity but its complex ecological relationships impede research efforts. In this study, the spatial distribution and dynamic characteristics of climate change effects on vegetation activity in China from the 1980s to the 2010s and from 2021 to 2050 were investigated using a geographically weighted regression (GWR) model. The GWR model was based on combined datasets of satellite vegetation index, climate observation and projection, and future vegetation productivity simulation. Our results revealed that the significantly positive precipitation-vegetation relationship was and will be mostly distributed in North China. However, the regions with temperature-dominated distribution of vegetation activity were and will be mainly located in South China. Due to the varying climate features and vegetation cover, the spatial correlation between vegetation activity and climate change may be altered. There will be different dominant climatic factors for vegetation activity distribution in some regions such as Northwest China, and even opposite correlations in Northeast China. Additionally, the response of vegetation activity to precipitation will move southward in the next three decades. In contrast, although the high warming rate will restrain the vegetation activity, precipitation variability could modify hydrothermal conditions for vegetation activity. This observation is exemplified in the projected future enhancement of vegetation activity in the Tibetan Plateau and weakened vegetation activity in East and Middle China. Furthermore, the vegetation in most parts of North China may adapt to an arid environment, whereas in many southern areas, vegetation will be repressed by water shortage in the future.

  16. Response of Vegetation to Climate Change in the Drylands of East Asia

    International Nuclear Information System (INIS)

    Dai, L; Wang, K; Wang, R L; Zhang, L

    2014-01-01

    Over the past 25 years, global climate and environmental changes have caused an unprecedented rate of vegetation change, as exemplified in the drylands of East Asia. In this study, we investigated the spatio-temporal changes of vegetation in this region and analysed their relationship with climate data. Our results show that vegetation productivity significantly increased from 1982 to 2006. This increasing trend was observed for most of the region, particularly for northwest Mongolia and central Inner Mongolia. Grasslands, croplands, forests, and shrublands, all exhibited this trend. The annual growth rate of the grasslands determined using the Normalized Difference Vegetation Index (NDVI) was the largest observed change; reaching 0.07% p.a, followed by shrublands (0.06%), croplands (0.03%), and forests (0.02%). In the different geographic regions, the roles of temperature and precipitation on vegetation growth were shown to be different. Temperature was the dominant factor for the observed NDVI increase in northwest Mongolia and the centre of Inner Mongolia. The combined influences of temperature and precipitation changes have resulted in the promotion of vegetation growth, as seen in eastern GanSu. Temperature change is the primary factor for initiating vegetation growth in spring and autumn because warmer temperatures increase the length of the growing season, and are thus evaluated as an increased NDVI value. Increased precipitation has been shown to play a positive role on vegetation growth during summer

  17. Vegetation Indices for Mapping Canopy Foliar Nitrogen in a Mixed Temperate Forest

    Directory of Open Access Journals (Sweden)

    Zhihui Wang

    2016-06-01

    Full Text Available Hyperspectral remote sensing serves as an effective tool for estimating foliar nitrogen using a variety of techniques. Vegetation indices (VIs are a simple means of retrieving foliar nitrogen. Despite their popularity, few studies have been conducted to examine the utility of VIs for mapping canopy foliar nitrogen in a mixed forest context. In this study, we assessed the performance of 32 vegetation indices derived from HySpex airborne hyperspectral images for estimating canopy mass-based foliar nitrogen concentration (%N in the Bavarian Forest National Park. The partial least squares regression (PLSR was performed for comparison. These vegetation indices were classified into three categories that are mostly correlated to nitrogen, chlorophyll, and structural properties such as leaf area index (LAI. %N was destructively measured in 26 broadleaf, needle leaf, and mixed stand plots to represent the different species and canopy structure. The canopy foliar %N is defined as the plot-level mean foliar %N of all species weighted by species canopy foliar mass fraction. Our results showed that the variance of canopy foliar %N is mainly explained by functional type and species composition. The normalized difference nitrogen index (NDNI produced the most accurate estimation of %N (R2CV = 0.79, RMSECV = 0.26. A comparable estimation of %N was obtained by the chlorophyll index Boochs2 (R2CV = 0.76, RMSECV = 0.27. In addition, the mean NIR reflectance (800–850 nm, representing canopy structural properties, also achieved a good accuracy in %N estimation (R2CV = 0.73, RMSECV = 0.30. The PLSR model provided a less accurate estimation of %N (R2CV = 0.69, RMSECV = 0.32. We argue that the good performance of all three categories of vegetation indices in %N estimation can be attributed to the synergy among plant traits (i.e., canopy structure, leaf chemical and optical properties while these traits may converge across plant species for evolutionary reasons. Our

  18. Assessment of Vegetation Density and Soil Macrofauna Relationship in Riparian Forest of Karkhe River for the Determination of Rivers Buffer Zone

    Directory of Open Access Journals (Sweden)

    SH. Gholami

    2014-06-01

    Full Text Available The spatial distribution of soil organisms is influenced by the plant cover, thus resulting in a horizontal mosaic of areas subjected to gradients of nutrient availability and microclimatic conditions.This study was conducted to investigate the spatial variability of soil macrofauna in relation to vegetation density in the riparian forest landscape of Karkhe. The vegetation density was determined by calculating the NDVI index. Soil macrofauna were sampled using 200 sampling points along parallel transects (perpendicular to the river. The maximum distance between samples was 0.5 km. Soil macrofauna were extracted from 50 cm×50 cm×25 cm soil monolith by the hand-sorting procedure. Abundance, diversity (Shannon H’ index, richness (Menhinick index and evenness (Sheldon index were calculated. Soil macrofauna and NDVI data were analyzed using geostatistics (variogram in order to describe and quantify the spatial continuity. The variograms were spherical, revealing the presence of spatial autocorrelation. The range of influence was 1724 m for abundance, 1326 m for diversity, 1825 m for richness, 1450 for evenness and 1977 m for NDVI. The kriging maps showed that the NDVI Index and soil macrofauna had spatial variability. The spatial pattern of soil macrofauna abundance and biodiversity were similar to the spatial pattern of vegetation density as shown in the correlation.

  19. Vegetation variation of loess deposits in the southeastern Inner Mongolia, NE China over the past ∼1.08 million years

    Science.gov (United States)

    Lyu, Anqi; Lu, Huayu; Zeng, Lin; Zhang, Hongyan; Zhang, Enlou; Yi, Shuangwen

    2018-04-01

    The stable carbon isotopic composition of organic matter of aeolian silt deposits is regarded as an appropriate proxy index of paleovegetation, especially in the Chinese Loess Plateau in central China. In this study, a loess-paleosol sequence in the southeastern Inner Mongolia Autonomous Region in northeastern (NE) China, which is located outside the Chinese Loess Plateau, is chosen to reconstruct the vegetation history since ∼1.08 Ma. Temperature exhibits a threshold value, which determines the growth of C4 plants in this study area. The organic matter of the samples is derived from two different vegetation types, namely, the mixed C3 and C4 plants and the pure C3 plants. The δ13C of the organic matter shows negative values in loess units and higher values in paleosol units. This finding reflects the influence of temperature and summer monsoon intensity on the vegetation dynamics over glacial-interglacial cycles. On a longer time scale, the δ13C values are higher between ∼1.1 and ∼0.9 Ma and after ∼0.35 Ma, and lower between ∼0.9 and ∼0.35 Ma, which may be attributed to a long-term temperature variation. Our analysis shows that regional temperature is the most important limiting factor that forces vegetation changes at the glacial-interglacial time scale in NE China.

  20. Regional vegetation dynamics and its response to climate change—a case study in the Tao River Basin in Northwestern China

    International Nuclear Information System (INIS)

    Li, Changbin; Yang, Linshan; Wang, Shuaibing; Yang, Wenjin; Zhu, Gaofeng; Qi, Jiaguo; Zou, Songbing; Zhang, Feng

    2014-01-01

    The 30-year normalized-difference vegetation index (NDVI) time series from AVHRR/MODIS satellite sensors was used in this study to assess the regional vegetation dynamic changes in the Tao River Basin, which cuts across the Eastern Tibetan Plateau (ETP) and the Southwestern Loess Plateau (SLP). First, principal component and correlation analyses were carried out to determine the key climatic variables driving ecological change in the region. Then, regression models were tested to correlate NDVI with the selected climatic variables to determine their predictive power. Finally, Sen’s slope method was used to determine how terrestrial vegetation has responded to regional climate change in the region. The results indicated an average winter season NDVI value of 0.14 in the ETP but only 0.04 in the SLP. Primarily driven by increasing temperature, vegetation growth has generally been enhanced since 1981; spring NDVI increased by 0.03 every 10 years in the ETP and 0.02 in the SLP. Further, results from trend analyses suggest vegetation growth in the ETP shifted to earlier-start and earlier-end dates, however in the SLP, the growing season has been extended with an earlier-start and later-end date. The precipitation threshold for vegetation germination, measured by the cumulative spring rainfall, was found to be 44 mm for both the ETP and SLP. (paper)

  1. Robotic tilt table reduces the occurrence of orthostatic hypotension over time in vegetative states.

    Science.gov (United States)

    Taveggia, Giovanni; Ragusa, Ivana; Trani, Vincenzo; Cuva, Daniele; Angeretti, Cristina; Fontanella, Marco; Panciani, Pier Paolo; Borboni, Alberto

    2015-06-01

    The aim of this study is to evaluate the effects of verticalization with or without combined movement of the lower limbs in patients in a vegetative state or a minimally conscious state. In particular, we aimed to study whether, in the group with combined movement, there was better tolerance to verticalization. This was a randomized trial conducted in a neurorehabilitation hospital. Twelve patients with vegetative state and minimally conscious state 3-18 months after acute acquired brain injuries were included. Patients were randomized into A and B treatment groups. Study group A underwent verticalization with a tilt table at 65° and movimentation of the lower limbs with a robotic system for 30 min three times a week for 24 sessions. Control group B underwent the same rehabilitation treatment, with a robotic verticalization system, but an inactive lower-limb movement system. Systolic and diastolic blood pressure and heart rate were determined. Robotic movement of the lower limbs can reduce the occurrence of orthostatic hypotension in hemodynamically unstable patients. Despite the small number of patients involved (only eight patients completed the trial), our results indicate that blood pressures and heart rate can be stabilized better (with) by treatment with passive leg movements in hemodynamically unstable patients.

  2. High Vegetable Fats Intake Is Associated with High Resting Energy Expenditure in Vegetarians.

    Science.gov (United States)

    Montalcini, Tiziana; De Bonis, Daniele; Ferro, Yvelise; Carè, Ilaria; Mazza, Elisa; Accattato, Francesca; Greco, Marta; Foti, Daniela; Romeo, Stefano; Gulletta, Elio; Pujia, Arturo

    2015-07-17

    It has been demonstrated that a vegetarian diet may be effective in reducing body weight, however, the underlying mechanisms are not entirely clear. We investigated whether there is a difference in resting energy expenditure between 26 vegetarians and 26 non-vegetarians and the correlation between some nutritional factors and inflammatory markers with resting energy expenditure. In this cross-sectional study, vegetarians and non-vegetarians were matched by age, body mass index and gender. All underwent instrumental examinations to assess the difference in body composition, nutrient intake and resting energy expenditure. Biochemical analyses and 12 different cytokines and growth factors were measured as an index of inflammatory state. A higher resting energy expenditure was found in vegetarians than in non-vegetarians (p = 0.008). Furthermore, a higher energy from diet, fibre, vegetable fats intake and interleukin-β (IL-1β) was found between the groups. In the univariate and multivariable analysis, resting energy expenditure was associated with vegetarian diet, free-fat mass and vegetable fats (p vegetarian's diet, i.e., vegetable fats. Furthermore, we showed that IL-10 was positively associated with resting energy expenditure in this population.

  3. Analysis of vegetation condition and its relationship with meteorological variables in the Yarlung Zangbo River Basin of China

    Directory of Open Access Journals (Sweden)

    X. Han

    2018-06-01

    Full Text Available The Yarlung Zangbo River Basin is located in the southwest border of China, which is of great significance to the socioeconomic development and ecological environment of Southwest China. Normalized Difference Vegetation Index (NDVI is an important index for investigating the change of vegetation cover, which is widely used as the representation value of vegetation cover. In this study, the NDVI is adopted to explore the vegetation condition in the Yarlung Zangbo River Basin during the recent 17 years, and the relationship between NDVI and meteorological variables has also been discussed. The results show that the annual maximum value of NDVI usually appears from July to September, in which August occupies a large proportion. The minimum value of NDVI appears from January to March, in which February takes up most of the percentage. The higher values of NDVI are generally located in the lower elevation area. When the altitude is higher than 3250 m, NDVI began to decline gradually, and the NDVI became gradual stabilization as the elevation is up to 6000 m. The correlation coefficient between NDVI and precipitation in the Yarlung Zangbo River Basin is greater than that with temperature. The Hurst index of the whole basin is 0.51, indicating that the NDVI of the Yarlung Zangbo River Basin shows a weak sustainability.

  4. Relationships between vegetation and climate change in Transbaikalia, Siberia

    Energy Technology Data Exchange (ETDEWEB)

    Tchebakova, N.M.; Parfenova, E.I. [V.N. Sukachev Inst. of Forest, Russian Academy of Sciences, Siberian Branch, Akademgorodok, Krasnoyarsk (Russian Federation)

    2002-10-01

    This paper demonstrated how vegetation of the Lake Baikal basin may respond to climate change at a mountain biome (an orobiome over the entire basin) and a stand in a locality. An orobiome vegetation model was developed along with a higher resolution stand model based on climatic parameters. Regional climates were modeled based on physiology and site climates based on topography. Bioclimatic multiple regression models were then developed to predict regional vegetation and forest stand characteristics distribution over a mountain range in Central Transbaikalia under current and future climate scenarios. Bioclimatic models were combined with climatic layers of different resolutions. Tree species composition and wood volume was predicted based on 2 climate indices - temperature sums (base 5 degrees C) and the dryness index. Results indicate that lowland vegetation will shift 250 m upslope and highland vegetation will shift 450 m upslope. This will significantly reduce the tundra and light-needled taiga, and will expand the forest-steppe. Results also indicate that the total phytomass within the entire basin will not change much. Stand phytomass across the basin will, however, increase. The model used in this study does not include climate-forcing factors such as wind, snow and permafrost. The model is open to new development to include a dynamic components that would inject vitality into the model. 13 refs., 2 tabs., 3 figs.

  5. Elephant movement closely tracks precipitation-driven vegetation dynamics in a Kenyan forest-savanna landscape.

    Science.gov (United States)

    Bohrer, Gil; Beck, Pieter Sa; Ngene, Shadrack M; Skidmore, Andrew K; Douglas-Hamilton, Ian

    2014-01-01

    This study investigates the ranging behavior of elephants in relation to precipitation-driven dynamics of vegetation. Movement data were acquired for five bachelors and five female family herds during three years in the Marsabit protected area in Kenya and changes in vegetation were mapped using MODIS normalized difference vegetation index time series (NDVI). In the study area, elevations of 650 to 1100 m.a.s.l experience two growth periods per year, while above 1100 m.a.s.l. growth periods last a year or longer. We find that elephants respond quickly to changes in forage and water availability, making migrations in response to both large and small rainfall events. The elevational migration of individual elephants closely matched the patterns of greening and senescing of vegetation in their home range. Elephants occupied lower elevations when vegetation activity was high, whereas they retreated to the evergreen forest at higher elevations while vegetation senesced. Elephant home ranges decreased in size, and overlapped less with increasing elevation. A recent hypothesis that ungulate migrations in savannas result from countervailing seasonally driven rainfall and fertility gradients is demonstrated, and extended to shorter-distance migrations. In other words, the trade-off between the poor forage quality and accessibility in the forest with its year-round water sources on the one hand and the higher quality forage in the low-elevation scrubland with its seasonal availability of water on the other hand, drives the relatively short migrations (the two main corridors are 20 and 90 km) of the elephants. In addition, increased intra-specific competition appears to influence the animals' habitat use during the dry season indicating that the human encroachment on the forest is affecting the elephant population.

  6. Hidden vegetables: an effective strategy to reduce energy intake and increase vegetable intake in adults.

    Science.gov (United States)

    Blatt, Alexandria D; Roe, Liane S; Rolls, Barbara J

    2011-04-01

    The overconsumption of energy-dense foods leads to excessive energy intakes. The substitution of low-energy-dense vegetables for foods higher in energy density can help decrease energy intakes but may be difficult to implement if individuals dislike the taste of vegetables. We investigated whether incorporating puréed vegetables to decrease the energy density of entrées at multiple meals reduced daily energy intakes and increased daily vegetable intakes. In this crossover study, 20 men and 21 women ate ad libitum breakfast, lunch, and dinner in the laboratory once a week for 3 wk. Across conditions, entrées at meals varied in energy density from standard versions (100% condition) to reduced versions (85% and 75% conditions) by the covert incorporation of 3 or 4.5 times the amount of puréed vegetables. Entrées were accompanied by unmanipulated side dishes. Participants rated their hunger and fullness before and after meals. Subjects consumed a consistent weight of foods across conditions of energy density; thus, the daily energy intake significantly decreased by 202 ± 60 kcal in the 85% condition (P kcal in the 75% condition (P Daily vegetable consumption significantly increased from 270 ± 17 g of vegetables in the 100% condition to 487 ± 25 g of vegetables in the 75% condition (P < 0.0001). Despite the decreased energy intake, ratings of hunger and fullness did not significantly differ across conditions. Entrées were rated as similar in palatability across conditions. Large amounts of puréed vegetables can be incorporated into various foods to decrease the energy density. This strategy can lead to substantial reductions in energy intakes and increases in vegetable intakes. This trial was registered at clinicaltrials.gov as NCT01165086.

  7. Remote sensing estimation of vegetation moisture for the prediction of fire hazard

    NARCIS (Netherlands)

    Maffei, C.; Menenti, M.

    2013-01-01

    Various factors contribute to forest fire hazard, and among them vegetation moisture is the one that dictates susceptibility to fire ignition and propagation. The scientific community has developed a number of spectral indexes based on remote sensing measurements in the optical domain for the

  8. Time to address continued poor vegetable intake in Australia for prevention of chronic disease.

    Science.gov (United States)

    Chapman, Kathryn; Havill, Michelle; Watson, Wendy L; Wellard, Lyndal; Hughes, Clare; Bauman, Adrian; Allman-Farinelli, Margaret

    2016-12-01

    Australian and most international Dietary Guidelines recommend people consume more fruits and vegetables (F&V) to maintain a healthy weight and reduce chronic disease risk. Previous Australian and international surveys have shown sub-optimal consumption of F&V. This study aimed to assess adults' F&V consumption, knowledge of recommended servings, readiness to change, barriers/enabling factors, so that this knowledge might be used for campaigns that support improved consumption. An online survey of a representative sample of adults living in New South Wales, Australia (n = 2474) measuring self-reported F&V consumption; attitudes towards F&V consumption; stage of change for increasing F&V; barriers to consumption; and knowledge of cancer-health benefits. F&V consumption was below recommendations, with vegetable consumption notably low. Only 10% of participants ate at least five servings of vegetables/day (median intake was two daily servings), and 57% consumed two servings fruit/day. There was poor recognition that intake of vegetables was inadequate and this was a barrier to improving vegetable consumption; with preferences for other foods, habit and cost also important barriers. Key barriers to increasing fruit intake were habit, preferences for other foods, perishability, and cost. For vegetable consumption, 49% of participants were in the pre-contemplation stage of change, whereas for fruits 56% were in the action/maintenance stage. Sixty-four percent of respondents believed that eating F&V would protect against cancer, with 56% reporting they thought not eating enough F&V would cause cancer. Understanding what motivates and prevents people from consuming F&V is important for developing effective health promotion programs. Similar to previous surveys, there has been little shift in F&V consumption. Social marketing campaigns have been shown to improve health-related behaviours, and this study may assist in identifying audience segmentation for better targeted

  9. DEVELOPMENT OF AN INDEX OF ALIEN SPECIES INVASIVENESS: AN AID TO ASSESSING RIPARIAN VEGETATION CONDITION

    Science.gov (United States)

    Many riparian areas are invaded by alien plant species that negatively affect native species composition, community dynamics and ecosystem properties. We sampled vegetation along reaches of 31 low order streams in eastern Oregon, and characterized species assemblages at patch an...

  10. Presence of riparian vegetation increases biotic condition of fish assemblages in two Brazilian reservoirs

    OpenAIRE

    Ferreira, Fabio Cop; Souza, Ursulla Pereira; Petrere Junior2, Miguel

    2015-01-01

    Abstract The riparian vegetation in lakes and reservoirs is source of course wood structures such as trunks and branches and is used as sheltering, spawning and foraging habitats for fishes. The reduction of these submerged structures can thus, affect the composition and structure of fish assemblages in reservoirs. Aim To evaluate the influence of riparian vegetation on the biotic condition of fish assemblage by adapting the Reservoir Fish Assemblage Index (RFAI) to two reservoirs in the Upp...

  11. CHARACTERISING VEGETATED SURFACES USING MODIS MULTIANGULAR SATELLITE DATA

    Directory of Open Access Journals (Sweden)

    G. McCamley

    2012-07-01

    Full Text Available Bidirectional Reflectance Distribution Functions (BRDF seek to represent variations in surface reflectance resulting from changes in a satellite's view and solar illumination angles. BRDF representations have been widely used to assist in the characterisation of vegetation. However BRDF effects are often noisy, difficult to interpret and are the spatial integral of all the individual surface features present in a pixel. This paper describes the results of an approach to understanding how BRDF effects can be used to characterise vegetation. The implementation of the Ross Thick Li Sparse BRDF model using MODIS is a stable, mature data product with a 10 year history and is a ready data source. Using this dataset, a geometric optical model is proposed that seeks to interpret the BRDF effects in terms of Normalised Difference Vegetation Index (NDVI and a height-to-width ratio of the vegetation components. The height-to-width ratio derived from this model seeks to represent the dependence of NDVI to changes in view zenith angle as a single numeric value. The model proposed within this paper has been applied to MODIS pixels in central Australia for areas in excess of 18,000 km2. The study area is predominantly arid and sparsely vegetated which provides a level of temporal and spatial homogeneity. The selected study area also minimises the effects associated with mutual obscuration of vegetation which is not considered by the model. The results are represented as a map and compared to NDVI derived from MODIS and NDVI derived from Landsat mosaics developed for Australia's National Carbon Accounting System (NCAS. The model reveals additional information not obvious in reflectance data. For example, the height-to-width ratio is able to reveal vegetation features in arid areas that do not have an accompanying significant increase in NDVI derived from MODIS, i.e. the height-to-width ratio reveals vegetation which is otherwise only apparent in NDVI derived

  12. Arbuscular mycorrhizal fungi associated with vegetation and soil parameters under rest grazing management in a desert steppe ecosystem.

    Science.gov (United States)

    Bai, Gegenbaoleer; Bao, Yuying; Du, Guoxin; Qi, Yunlong

    2013-05-01

    The impact of rest grazing on arbuscular mycorrhizal fungi (AMF) and the interactions of AMF with vegetation and soil parameters under rest grazing condition were investigated between spring and late summer in a desert steppe ecosystem with different grazing managements (rest grazing with different lengths of resting period, banned or continuous grazing) in Inner Mongolia, China. AMF diversity and colonization, vegetation biomass, soil properties and soil phosphatase activity were examined. In rest grazing areas of 60 days, AMF spore number and diversity index at a 0-10 cm soil depth as well as vesicular and hyphal colonization rates were higher compared with other grazing treatments. In addition, soil organic matter and total N contents were highest and soil alkaline phosphatase was most active under 60-day rest grazing. In August and September, these areas also had the highest amount of aboveground vegetation. The results indicated that resting grazing for an appropriate period of time in spring has a positive effect on AMF sporulation, colonization and diversity, and that under rest grazing conditions, AMF parameters are positively correlated with some soil characteristics.

  13. Comparison of the time-to-indexing in PubMed between biomedical journals according to impact factor, discipline, and focus.

    Science.gov (United States)

    Irwin, Adriane N; Rackham, Daniel

    Practicing evidence-based medicine requires health care professionals to efficiently retrieve relevant and current literature. The purpose of this study was to compare the time interval between PubMed entry and indexing with Medical Subject Headings (MeSH) between biomedical journals with varying impact factors, focus areas, and health care discipline representation. This was a cross-sectional study of articles entered into PubMed database between January 1 and December 31, 2012. The primary endpoint was the number of days between PubMed entry and indexing with MeSH terms. A total of 7906 articles were reviewed across 18 journals. In the first comparison, the time-to-indexing was 177 ± 100 days, 111 ± 69 days, and 23 ± 40 days for articles published in journals with impact factors of 2.0-2.5, 4.5-6.5, and >25, respectively (P ≤ 0.001). In the second comparison, the time-to-indexing was 111 ± 69 days for general medicine versus 170 ± 74 days for specialty journals (P ≤ 0.001). In the third comparison, the overall time-to-indexing was 177 ± 100 days, 234 ± 107 days, and 163 ± 58 days for medicine, nursing, and pharmacy journals, respectively (P ≤ 0.001). Study results identified a significant delay between entry of articles into the PubMed database and time-to-indexing with MeSH terms across journals of varying impact factor, discipline, and focus. Results suggest that there may be factors that influence the priority by which articles are indexed with MeSH terms. Future research should focus on determining those journal characteristics and any impact of this delay on clinical practice. Copyright © 2016 Elsevier Inc. All rights reserved.

  14. Consumption Frequency of Foods Away from Home Linked with Higher Body Mass Index and Lower Fruit and Vegetable Intake among Adults: A Cross-Sectional Study

    Science.gov (United States)

    Seguin, Rebecca A.; Aggarwal, Anju; Vermeylen, Francoise; Drewnowski, Adam

    2016-01-01

    Introduction. Consumption of foods prepared away from home (FAFH) has grown steadily since the 1970s. We examined the relationship between FAFH and body mass index (BMI) and fruit and vegetable (FV) consumption. Methods. Frequency of FAFH, daily FV intake, height and weight, and sociodemographic data were collected using a telephone survey in 2008-2009. Participants included a representative sample of 2,001 adult men and women (mean age 54 ± 15 years) residing in King County, WA, with an analytical sample of 1,570. Frequency of FAFH was categorized as 0-1, 2–4, or 5+ times per week. BMI was calculated from self-reported height and weight. We examined the relationship between FAFH with FV consumption and BMI using multivariate models. Results. Higher frequency of FAFH was associated with higher BMI, after adjusting for age, income, education, race, smoking, marital status, and physical activity (women: p = 0.001; men: p = 0.003). There was a negative association between frequency of FAFH and FV consumption. FAFH frequency was significantly (p < 0.001) higher among males than females (43.1% versus 54.0% eating out 0-1 meal per week, resp.). Females reported eating significantly (p < 0.001) more FV than males. Conclusion. Among adults, higher frequency of FAFH was related to higher BMI and less FV consumption. PMID:26925111

  15. Consumption Frequency of Foods Away from Home Linked with Higher Body Mass Index and Lower Fruit and Vegetable Intake among Adults: A Cross-Sectional Study

    Directory of Open Access Journals (Sweden)

    Rebecca A. Seguin

    2016-01-01

    Full Text Available Introduction. Consumption of foods prepared away from home (FAFH has grown steadily since the 1970s. We examined the relationship between FAFH and body mass index (BMI and fruit and vegetable (FV consumption. Methods. Frequency of FAFH, daily FV intake, height and weight, and sociodemographic data were collected using a telephone survey in 2008-2009. Participants included a representative sample of 2,001 adult men and women (mean age 54±15 years residing in King County, WA, with an analytical sample of 1,570. Frequency of FAFH was categorized as 0-1, 2–4, or 5+ times per week. BMI was calculated from self-reported height and weight. We examined the relationship between FAFH with FV consumption and BMI using multivariate models. Results. Higher frequency of FAFH was associated with higher BMI, after adjusting for age, income, education, race, smoking, marital status, and physical activity (women: p=0.001; men: p=0.003. There was a negative association between frequency of FAFH and FV consumption. FAFH frequency was significantly (p<0.001 higher among males than females (43.1% versus 54.0% eating out 0-1 meal per week, resp.. Females reported eating significantly (p<0.001 more FV than males. Conclusion. Among adults, higher frequency of FAFH was related to higher BMI and less FV consumption.

  16. Variation of Vegetation Ecological Water Consumption and Its Response to Vegetation Coverage Changes in the Rocky Desertification Areas in South China.

    Science.gov (United States)

    Wan, Long; Tong, Jing; Zhou, Jinxing; Guo, Hongyan; Cui, Ming; Liu, Yuguo; Ning, Like; Tang, Fukai

    2016-01-01

    Over the past several decades, rocky desertification has led to severe ecological problems in karst areas in South China. After a rocky desertification treatment project was completed, the vegetation coverage changed greatly and, consequently, increased the ecology water consumption (approximately equal to the actual evapotranspiration) of the regional vegetation. Thus, it intensified the regional water stresses. This study explored the changes in the actual evapotranspiration (ETa) response to the vegetation coverage changes in the rocky desertification areas in South China based on the precipitation (P), potential evapotranspiration (ETp) and NDVI (the normalized difference vegetation index) datasets. The revised Bagrov model was used to simulate the actual evapotranspiration changes with the supposed increasing NDVI. The results indicated that the average NDVI value was lower when the rocky desertification was more severe. The ETa, evapotranspiration efficiency (ETa/ETp) and potential humidity (P/ETp) generally increased with the increasing NDVI. The sensitivity of the ETa response to vegetation coverage changes varied due to different precipitation conditions and different rocky desertification severities. The ETa was more sensitive under drought conditions. When a drought occurred, the ETa exhibited an average increase of 40~60 mm with the NDVI increasing of 0.1 in the rocky desertification areas. Among the 5 different severity categories of rocky desertification, the ETa values' responses to NDVI changes were less sensitive in the severe rocky desertification areas but more sensitive in the extremely and potential rocky desertification areas. For example, with the NDVI increasing of 0.025, 0.05, 0.075, and 0.1, the corresponding ETa changes increased by an average of 2.64 mm, 10.62 mm, 19.19 mm, and 27.58 mm, respectively, in severe rocky desertification areas but by 4.94 mm, 14.99 mm, 26.80, and 37.13 mm, respectively, in extremely severe rocky

  17. Microbialproperty improvement of saline-alkali soil for vegetable cultivation in Shanghai coastal area and its evaluation

    Directory of Open Access Journals (Sweden)

    KOU Yiming

    2015-10-01

    Full Text Available In order to improve the fertility of saline-alkali soil in Shanghai coastal area,and make it suitable for vegetable cultiration,in the study,the saline-alkali soil was mixed with organic fertilizer,and then sprayed with composite microbes,which have the ability of the synergistically degrading organic substrate.The results showed that the saline-alkali soil added with 5∶1 organic fertilizer can rapidly increase the utilization ability soil organic matter.The soil microbial populations and microbial diversity index were significantly improved when applied with the 0.5% composite microbial liquid which containeds 1∶3∶3∶1 of Bacillus licheniformis,Pseudomonas sp., Flavobacterium sp.and Sphingomonas sp..At the same time,the enzymology indicators of soil urease,phosphatase,cellulase and catalase increased significantly.The vegetable cultivation experiments showed that:the biomass of Brassica chinensis nearly doubled in the original saline-alkali soil,while the yield of organic fertilizer increased 30.2% after 50 days.The research result on of the biological improvement for saline-alkali soil will have good application value in vegetable planting in coastal saline-alkali soil.

  18. Gelation and interfacial behaviour of vegetable proteins

    NARCIS (Netherlands)

    Vliet, T. van; Martin, A.H.; Bos, M.A.

    2002-01-01

    Recent studies on gelation and interfacial properties of vegetable protiens are reviewed. Attention is focused on legume proteins, mainly soy proteins, and on wheat proteins. The rheological properteis of vegetable protein gels as a function of heating time or temperature is discussed as well as the

  19. Gelation and interfacial behaviour of vegetable proteins

    NARCIS (Netherlands)

    Vliet, van T.; Martin, A.H.; Bos, M.A.

    2002-01-01

    Recent studies on gelation and interfacial properties of vegetable proteins are reviewed. Attention is focused on legume proteins, mainly soy proteins, and on wheat proteins. The rheological properties of vegetable protein gels as a function of heating time or temperature is discussed as well as the

  20. Mapping Deforestation in North Korea Using Phenology-Based Multi-Index and Random Forest

    Directory of Open Access Journals (Sweden)

    Yihua Jin

    2016-12-01

    Full Text Available Phenology-based multi-index with the random forest (RF algorithm can be used to overcome the shortcomings of traditional deforestation mapping that involves pixel-based classification, such as ISODATA or decision trees, and single images. The purpose of this study was to investigate methods to identify specific types of deforestation in North Korea, and to increase the accuracy of classification, using phenological characteristics extracted with multi-index and random forest algorithms. The mapping of deforestation area based on RF was carried out by merging phenology-based multi-indices (i.e., normalized difference vegetation index (NDVI, normalized difference water index (NDWI, and normalized difference soil index (NDSI derived from MODIS (Moderate Resolution Imaging Spectroradiometer products and topographical variables. Our results showed overall classification accuracy of 89.38%, with corresponding kappa coefficients of 0.87. In particular, for forest and farm land categories with similar phenological characteristic (e.g., paddy, plateau vegetation, unstocked forest, hillside field, this approach improved the classification accuracy in comparison with pixel-based methods and other classes. The deforestation types were identified by incorporating point data from high-resolution imagery, outcomes of image classification, and slope data. Our study demonstrated that the proposed methodology could be used for deciding on the restoration priority and monitoring the expansion of deforestation areas.