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...

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

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.

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

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).

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

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.

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...

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

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 ...

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

Construction and Application of Enhanced Remote Sensing Ecological Index

Science.gov (United States)

Wang, X.; Liu, C.; Fu, Q.; Yin, B.

2018-04-01

In order to monitor the change of regional ecological environment quality, this paper use MODIS and DMSP / OLS remote sensing data, from the production capacity, external disturbance changes and human socio-economic development of the three main factors affecting the quality of ecosystems, select the net primary productivity, vegetation index and light index, using the principal component analysis method to automatically determine the weight coefficient, construction of the formation of enhanced remote sensing ecological index, and the ecological environment quality of Hainan Island from 2001 to 2013 was monitored and analyzed. The enhanced remote sensing ecological index combines the effects of the natural environment and human activities on ecosystems, and according to the contribution of each principal component automatically determine the weight coefficient, avoid the design of the weight of the parameters caused by the calculation of the human error, which provides a new method for the operational operation of regional macro ecological environment quality monitoring. During the period from 2001 to 2013, the ecological environment quality of Hainan Island showed the characteristics of decend first and then rise, the ecological environment in 2005 was affected by severe natural disasters, and the quality of ecological environment dropped sharply. Compared with 2001, in 2013 about 20000 square kilometers regional ecological environmental quality has improved, about 8760 square kilometers regional ecological environment quality is relatively stable, about 5272 square kilometers regional ecological environment quality has decreased. On the whole, the quality of ecological environment in the study area is good, the frequent occurrence of natural disasters, on the quality of the ecological environment to a certain extent.

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.

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

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.

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...

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.

Enhanced index tracking modelling in portfolio optimization

Science.gov (United States)

Lam, W. S.; Hj. Jaaman, Saiful Hafizah; Ismail, Hamizun bin

2013-09-01

Enhanced index tracking is a popular form of passive fund management in stock market. It is a dual-objective optimization problem, a trade-off between maximizing the mean return and minimizing the risk. Enhanced index tracking aims to generate excess return over the return achieved by the index without purchasing all of the stocks that make up the index by establishing an optimal portfolio. The objective of this study is to determine the optimal portfolio composition and performance by using weighted model in enhanced index tracking. Weighted model focuses on the trade-off between the excess return and the risk. The results of this study show that the optimal portfolio for the weighted model is able to outperform the Malaysia market index which is Kuala Lumpur Composite Index because of higher mean return and lower risk without purchasing all the stocks in the market index.

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)

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

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

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)

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.

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.

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) ...

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

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

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...

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

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...

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.

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.

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

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.

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. ...

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

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

Portfolio optimization in enhanced index tracking with goal programming approach

Science.gov (United States)

Siew, Lam Weng; Jaaman, Saiful Hafizah Hj.; Ismail, Hamizun bin

2014-09-01

Enhanced index tracking is a popular form of passive fund management in stock market. Enhanced index tracking aims to generate excess return over the return achieved by the market index without purchasing all of the stocks that make up the index. This can be done by establishing an optimal portfolio to maximize the mean return and minimize the risk. The objective of this paper is to determine the portfolio composition and performance using goal programming approach in enhanced index tracking and comparing it to the market index. Goal programming is a branch of multi-objective optimization which can handle decision problems that involve two different goals in enhanced index tracking, a trade-off between maximizing the mean return and minimizing the risk. The results of this study show that the optimal portfolio with goal programming approach is able to outperform the Malaysia market index which is FTSE Bursa Malaysia Kuala Lumpur Composite Index because of higher mean return and lower risk without purchasing all the stocks in the market index.

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.

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

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 ...

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.

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...

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

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...

[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.

Application and Comparison of the MODIS-Derived Enhanced Vegetation Index to VIIRS, Landsat 5 TM and Landsat 8 OLI Platforms: A Case Study in the Arid Colorado River Delta, Mexico

Science.gov (United States)

Jarchow, Christopher J.; Didan, Kamel; Barreto-Muñoz, Armando; Glenn, Edward P.

2018-01-01

The Enhanced Vegetation Index (EVI) is a key Earth science parameter used to assess vegetation, originally developed and calibrated for the Moderate Resolution Imaging Spectroradiometer (MODIS) aboard the Terra and Aqua satellites. With the impending decommissioning of the MODIS sensors by the year 2020/2022, alternative platforms will need to be used to estimate EVI. We compared Landsat 5 (2000–2011), 8 (2013–2016) and the Visible Infrared Imaging Radiometer Suite (VIIRS; 2013–2016) to MODIS EVI (2000–2016) over a 420,083-ha area of the arid lower Colorado River Delta in Mexico. Over large areas with mixed land cover or agricultural fields, we found high correspondence between Landsat and MODIS EVI (R2 = 0.93 for the entire area studied and 0.97 for agricultural fields), but the relationship was weak over bare soil (R2 = 0.27) and riparian vegetation (R2 = 0.48). The correlation between MODIS and Landsat EVI was higher over large, homogeneous areas and was generally lower in narrow riparian areas. VIIRS and MODIS EVI were highly similar (R2 = 0.99 for the entire area studied) and did not show the same decrease in performance in smaller, narrower regions as Landsat. Landsat and VIIRS provide EVI estimates of similar quality and characteristics to MODIS, but scale, seasonality and land cover type(s) should be considered before implementing Landsat EVI in a particular area. PMID:29757265

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.

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

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.

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

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...

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.

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

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.

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)

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.

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.

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.

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

Comparison between goal programming and cointegration approaches in enhanced index tracking

Science.gov (United States)

Lam, Weng Siew; Jamaan, Saiful Hafizah Hj.

2013-04-01

Index tracking is a popular form of passive fund management in stock market. Passive management is a buy-and-hold strategy that aims to achieve rate of return similar to the market return. Index tracking problem is a problem of reproducing the performance of a stock market index, without purchasing all of the stocks that make up the index. This can be done by establishing an optimal portfolio that minimizes risk or tracking error. An improved index tracking (enhanced index tracking) is a dual-objective optimization problem, a trade-off between maximizing the mean return and minimizing the tracking error. Enhanced index tracking aims to generate excess return over the return achieved by the index. The objective of this study is to compare the portfolio compositions and performances by using two different approaches in enhanced index tracking problem, which are goal programming and cointegration. The result of this study shows that the optimal portfolios for both approaches are able to outperform the Malaysia market index which is Kuala Lumpur Composite Index. Both approaches give different optimal portfolio compositions. Besides, the cointegration approach outperforms the goal programming approach because the cointegration approach gives higher mean return and lower risk or tracking error. Therefore, the cointegration approach is more appropriate for the investors in Malaysia.

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....

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.

Enhanced

Directory of Open Access Journals (Sweden)

Martin I. Bayala

2014-06-01

Full Text Available Land Surface Temperature (LST is a key parameter in the energy balance model. However, the spatial resolution of the retrieved LST from sensors with high temporal resolution is not accurate enough to be used in local-scale studies. To explore the LST–Normalised Difference Vegetation Index relationship potential and obtain thermal images with high spatial resolution, six enhanced image sharpening techniques were assessed: the disaggregation procedure for radiometric surface temperatures (TsHARP, the Dry Edge Quadratic Function, the Difference of Edges (Ts∗DL and three models supported by the relationship of surface temperature and water stress of vegetation (Normalised Difference Water Index, Normalised Difference Infrared Index and Soil wetness index. Energy Balance Station data and in situ measurements were used to validate the enhanced LST images over a mixed agricultural landscape in the sub-humid Pampean Region of Argentina (PRA, during 2006–2010. Landsat Thematic Mapper (TM and Moderate Resolution Imaging Spectroradiometer (EOS-MODIS thermal datasets were assessed for different spatial resolutions (e.g., 960, 720 and 240 m and the performances were compared with global and local TsHARP procedures. Results suggest that the Ts∗DL technique is the most adequate for simulating LST to high spatial resolution over the heterogeneous landscape of a sub-humid region, showing an average root mean square error of less than 1 K.

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

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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.

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

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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

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

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.

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

Giant Kerr nonlinearities using refractive-index enhancement

International Nuclear Information System (INIS)

Yavuz, D. D.; Sikes, D. E.

2010-01-01

By utilizing refractive-index enhancement with vanishing absorption, a scheme is suggested that achieves giant Kerr nonlinearities between two weak laser beams. One application of this scheme is discussed and an all-optical distributed Bragg reflector is proposed that works at very low light levels.

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

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

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.

A new enhanced index tracking model in portfolio optimization with sum weighted approach

Science.gov (United States)

Siew, Lam Weng; Jaaman, Saiful Hafizah; Hoe, Lam Weng

2017-04-01

Index tracking is a portfolio management which aims to construct the optimal portfolio to achieve similar return with the benchmark index return at minimum tracking error without purchasing all the stocks that make up the index. Enhanced index tracking is an improved portfolio management which aims to generate higher portfolio return than the benchmark index return besides minimizing the tracking error. The objective of this paper is to propose a new enhanced index tracking model with sum weighted approach to improve the existing index tracking model for tracking the benchmark Technology Index in Malaysia. The optimal portfolio composition and performance of both models are determined and compared in terms of portfolio mean return, tracking error and information ratio. The results of this study show that the optimal portfolio of the proposed model is able to generate higher mean return than the benchmark index at minimum tracking error. Besides that, the proposed model is able to outperform the existing model in tracking the benchmark index. The significance of this study is to propose a new enhanced index tracking model with sum weighted apporach which contributes 67% improvement on the portfolio mean return as compared to the existing model.

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.

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

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

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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.

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

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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.

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

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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.

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

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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.

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

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

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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.

Estimating the Fractional Vegetation Cover from GLASS Leaf Area Index Product

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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.

Enhanced index tracking modeling in portfolio optimization with mixed-integer programming z approach

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Siew, Lam Weng; Jaaman, Saiful Hafizah Hj.; Ismail, Hamizun bin

2014-09-01

Enhanced index tracking is a popular form of portfolio management in stock market investment. Enhanced index tracking aims to construct an optimal portfolio to generate excess return over the return achieved by the stock market index without purchasing all of the stocks that make up the index. The objective of this paper is to construct an optimal portfolio using mixed-integer programming model which adopts regression approach in order to generate higher portfolio mean return than stock market index return. In this study, the data consists of 24 component stocks in Malaysia market index which is FTSE Bursa Malaysia Kuala Lumpur Composite Index from January 2010 until December 2012. The results of this study show that the optimal portfolio of mixed-integer programming model is able to generate higher mean return than FTSE Bursa Malaysia Kuala Lumpur Composite Index return with only selecting 30% out of the total stock market index components.

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

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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.

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

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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

A MODIS-based vegetation index climatology

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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 ...

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.

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.

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

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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.

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

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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.

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

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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.

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

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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)

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

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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.

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

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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.

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

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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.

A MODIS-based begetation index climatology

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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...

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.

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

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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.

Refractive index dependent local electric field enhancement in cylindrical gold nanohole

International Nuclear Information System (INIS)

Zhu Jian

2011-01-01

We report on the local electric field characters in a long cylindrical gold nanohole. Theoretical calculation results based on quasi-static model show that the local environmental dielectric constant dependent electric field intensity and field distribution in the gold nanohole show quite unique properties, different from those in the thin gold nanotube. Because of the thick gold wall, no plasmon hybridization exists. So there is only one resonance frequency taking place, and the intense local field has been focused into the gold nanohole. Our main finding is that, the local field in the nanohole is largely dependent on the inner hole refractive index and outer environmental refractive index. The competition between inner hole and outer polarization leads to a non-monotonic change of the local field intensity with increasing the dielectric constant of the nanohole. This refractive index controlled local field enhancement in cylindrical gold nanohole presents a potential for tunable surface-enhanced fluorescence and novel nano-optical biosensing applications.

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.

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.

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.

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

Biofilm formation enhances Helicobacter pylori survivability in vegetables.

Science.gov (United States)

Ng, Chow Goon; Loke, Mun Fai; Goh, Khean Lee; Vadivelu, Jamuna; Ho, Bow

2017-04-01

To date, the exact route and mode of transmission of Helicobacter pylori remains elusive. The detection of H. pylori in food using molecular approaches has led us to postulate that the gastric pathogen may survive in the extragastric environment for an extended period. In this study, we show that H. pylori prolongs its survival by forming biofilm and micro-colonies on vegetables. The biofilm forming capability of H. pylori is both strain and vegetable dependent. H. pylori strains were classified into high and low biofilm formers based on their highest relative biofilm units (BU). High biofilm formers survived longer on vegetables compared to low biofilm formers. The bacteria survived better on cabbage compared to other vegetables tested. In addition, images captured on scanning electron and confocal laser scanning microscopes revealed that the bacteria were able to form biofilm and reside as micro-colonies on vegetable surfaces, strengthening the notion of possible survival of H. pylori on vegetables for an extended period of time. Taken together, the ability of H. pylori to form biofilm on vegetables (a common food source for human) potentially plays an important role in its survival, serving as a mode of transmission of H. pylori in the extragastric environment. Copyright © 2016 Elsevier Ltd. All rights reserved.

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

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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

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

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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.

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.

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

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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

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.

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

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.

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.

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.

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 ...

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

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.

[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.

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)

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.

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...

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

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

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

Long-term decrease in satellite vegetation indices in response to environmental variables in an iconic desert riparian ecosystem: the Upper San Pedro, Arizona, United States

Science.gov (United States)

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

2015-01-01

The Upper San Pedro River is one of the few remaining undammed rivers that maintain a vibrant riparian ecosystem in the southwest United States. However, its riparian forest is threatened by diminishing groundwater and surface water inputs, due to either changes in watershed characteristics such as changes in riparian and upland vegetation, or human activities such as regional groundwater pumping. We used satellite vegetation indices to quantify the green leaf density of the groundwater-dependent riparian forest from 1984 to 2012. The river was divided into a southern, upstream (mainly perennial flow) reach and a northern, downstream (mainly intermittent and ephemeral flow) reach. Pre-monsoon (June) Landsat normalized difference vegetation index (NDVI) values showed a 20% drop for the northern reach (P  0·05). NDVI and enhanced vegetation index values were positively correlated (P deterioration of the riparian forest in the northern reach.

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.

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.)

Improving iris recognition performance using segmentation, quality enhancement, match score fusion, and indexing.

Science.gov (United States)

Vatsa, Mayank; Singh, Richa; Noore, Afzel

2008-08-01

This paper proposes algorithms for iris segmentation, quality enhancement, match score fusion, and indexing to improve both the accuracy and the speed of iris recognition. A curve evolution approach is proposed to effectively segment a nonideal iris image using the modified Mumford-Shah functional. Different enhancement algorithms are concurrently applied on the segmented iris image to produce multiple enhanced versions of the iris image. A support-vector-machine-based learning algorithm selects locally enhanced regions from each globally enhanced image and combines these good-quality regions to create a single high-quality iris image. Two distinct features are extracted from the high-quality iris image. The global textural feature is extracted using the 1-D log polar Gabor transform, and the local topological feature is extracted using Euler numbers. An intelligent fusion algorithm combines the textural and topological matching scores to further improve the iris recognition performance and reduce the false rejection rate, whereas an indexing algorithm enables fast and accurate iris identification. The verification and identification performance of the proposed algorithms is validated and compared with other algorithms using the CASIA Version 3, ICE 2005, and UBIRIS iris databases.

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.

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.

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

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

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

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

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

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.

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

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

Use of Different Vegetable Products to Increase Preschool-Aged Children's Preference for and Intake of a Target Vegetable

NARCIS (Netherlands)

Wild, de Victoire W.T.; Graaf, de Kees; Jager, Gerry

2017-01-01

Background: Children's low vegetable consumption requires effective strategies to enhance preference for and intake of vegetables. Objective: The study compared three preparation practices for a target vegetable (spinach) on their effectiveness in increasing preschool-aged children's preference

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.

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)

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.

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.

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

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.

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 ...

Reduced abscisic acid content is responsible for enhanced sucrose accumulation by potassium nutrition in vegetable soybean seeds.

Science.gov (United States)

Tu, Bingjie; Liu, Changkai; Tian, Bowen; Zhang, Qiuying; Liu, Xiaobing; Herbert, Stephen J

2017-05-01

In order to understand the physiological mechanism of potassium (K) application in enhancing sugar content of vegetable soybean seeds, pot experiments were conducted in 2014 and 2015 with two vegetable soybean (Glycine max L. Merr.) cultivars (c.v. Zhongkemaodou 1 and c.v. 121) under normal rate of nitrogen and phosphorus application. Three potassium (K) fertilization treatments were imposed: No K application (K0), 120 kg K 2 SO 4 ha -1 at seeding (K1), and 120 kg K 2 SO 4 ha -1 at seedling + 1% K 2 SO 4 foliar application at flowering (K2). Contents of indole-3-acetic acid (IAA), gibberellins (GA), cytokinins (ZR) and abscisic acid (ABA) in seeds were determined from 4 to 8 weeks after flowering. K fertilization increased the contents of IAA, GA, ZR, soluble sugar, sucrose and fresh pod yield, but reduced ABA content consistently. When the contents of soluble sugar and sucrose reached the highest level at 7 weeks after flowering for the 2 cultivars, the contents of IAA、GA、ZR all reached the lowest level in general. The content of ABA in seed was negatively correlated with the sucrose content (P abscisic acid content plays a critical role in enhancing sucrose content, which might be a partial mechanism involved in K nutrition to improve the quality of vegetable soybean.

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).

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.

Tunable Resonant-Cavity-Enhanced Photodetector with Double High-Index-Contrast Grating Mirrors

DEFF Research Database (Denmark)

Learkthanakhachon, Supannee; Yvind, Kresten; Chung, Il-Sug

2013-01-01

In this paper, we propose a broadband-tunable resonant-cavity-enhanced photodetector (RCE-PD) structure with double high-index-contrast grating (HCG) mirrors and numerically investigate its characteristics. The detector is designed to operate at 1550-nm wavelength. The detector structure consists....... Furthermore, the fact that it can be fabricated on a silicon platform offers us a possibility of integration with electronics.......In this paper, we propose a broadband-tunable resonant-cavity-enhanced photodetector (RCE-PD) structure with double high-index-contrast grating (HCG) mirrors and numerically investigate its characteristics. The detector is designed to operate at 1550-nm wavelength. The detector structure consists...... of a top InP HCG mirror, a p-i-n photodiode embedding multiple quantum wells, and a Si HCG mirror formed in the Si layer of a silicon-on-insulator wafer. The detection wavelength can be changed by moving the top InP HCG mirror suspended in the air. High reflectivity and small penetration length of HCGs...

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....

[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

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.

Varying responses of vegetation activity to climate changes on the Tibetan Plateau grassland.

Science.gov (United States)

Cong, Nan; Shen, Miaogen; Yang, Wei; Yang, Zhiyong; Zhang, Gengxin; Piao, Shilong

2017-08-01

Vegetation activity on the Tibetan Plateau grassland has been substantially enhanced as a result of climate change, as revealed by satellite observations of vegetation greenness (i.e., the normalized difference vegetation index, NDVI). However, little is known about the temporal variations in the relationships between NDVI and temperature and precipitation, and understanding this is essential for predicting how future climate change would affect vegetation activity. Using NDVI data and meteorological records from 1982 to 2011, we found that the inter-annual partial correlation coefficient between growing season (May-September) NDVI and temperature (R NDVI-T ) in a 15-year moving window for alpine meadow showed little change, likely caused by the increasing R NDVI-T in spring (May-June) and autumn (September) and decreasing R NDVI-T in summer (July-August). Growing season R NDVI-T for alpine steppe increased slightly, mainly due to increasing R NDVI-T in spring and autumn. The partial correlation coefficient between growing season NDVI and precipitation (R NDVI-P ) for alpine meadow increased slightly, mainly in spring and summer, and R NDVI-P for alpine steppe increased, mainly in spring. Moreover, R NDVI-T for the growing season was significantly higher in those 15-year windows with more precipitation for alpine steppe. R NDVI-P for the growing season was significantly higher in those 15-year windows with higher temperature, and this tendency was stronger for alpine meadow than for alpine steppe. These results indicate that the impact of warming on vegetation activity of Tibetan Plateau grassland is more positive (or less negative) during periods with more precipitation and that the impact of increasing precipitation is more positive (or less negative) during periods with higher temperature. Such positive effects of the interactions between temperature and precipitation indicate that the projected warmer and wetter future climate will enhance vegetation activity

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.

[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.

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.

Sustainable landscaping practices for enhancing vegetation establishment.

Science.gov (United States)

2016-02-01

Soil compaction can severely limit the success of vegetation establishment. Current grading and landscaping : practices commonly produce compacted soils of varied textures and profiles within SHA medians and roadsides, : resulting in limited capacity...

Enhanced canopy growth precedes senescence in 2005 and 2010 Amazonian droughts

KAUST Repository

Liu, Yi Y.

2018-04-09

Unprecedented droughts hit southern Amazonia in 2005 and 2010, causing a sharp increase in tree mortality and carbon loss. To better predict the rainforest\\'s response to future droughts, it is necessary to understand its behavior during past events. Satellite observations provide a practical source of continuous observations of Amazonian forest. Here we used a passive microwave-based vegetation water content record (i.e., vegetation optical depth, VOD), together with multiple hydrometeorological observations as well as conventional satellite vegetation measures, to investigate the rainforest canopy dynamics during the 2005 and 2010 droughts. During the onset of droughts in the wet-to-dry season (May–July) of both years, we found large-scale positive anomalies in VOD, leaf area index (LAI) and enhanced vegetation index (EVI) over the southern Amazonia. These observations are very likely caused by enhanced canopy growth. Concurrent below-average rainfall and above-average radiation during the wet-to-dry season can be interpreted as an early arrival of normal dry season conditions, leading to enhanced new leaf development and ecosystem photosynthesis, as supported by field observations. Our results suggest that further rainfall deficit into the subsequent dry season caused water and heat stress during the peak of 2005 and 2010 droughts (August–October) that exceeded the tolerance limits of the rainforest, leading to widespread negative VOD anomalies over the southern Amazonia. Significant VOD anomalies were observed mainly over the western part in 2005 and mainly over central and eastern parts in 2010. The total area with significant negative VOD anomalies was comparable between these two drought years, though the average magnitude of significant negative VOD anomalies was greater in 2005. This finding broadly agrees with the field observations indicating that the reduction in biomass carbon uptake was stronger in 2005 than 2010. The enhanced canopy growth

Enhanced canopy growth precedes senescence in 2005 and 2010 Amazonian droughts

KAUST Repository

Liu, Yi Y.; van Dijk, Albert I.J.M.; Miralles, Diego G.; McCabe, Matthew; Evans, Jason P.; de Jeu, Richard A.M.; Gentine, Pierre; Huete, Alfredo; Parinussa, Robert M.; Wang, Lixin; Guan, Kaiyu; Berry, Joe; Restrepo-Coupe, Natalia

2018-01-01

Unprecedented droughts hit southern Amazonia in 2005 and 2010, causing a sharp increase in tree mortality and carbon loss. To better predict the rainforest's response to future droughts, it is necessary to understand its behavior during past events. Satellite observations provide a practical source of continuous observations of Amazonian forest. Here we used a passive microwave-based vegetation water content record (i.e., vegetation optical depth, VOD), together with multiple hydrometeorological observations as well as conventional satellite vegetation measures, to investigate the rainforest canopy dynamics during the 2005 and 2010 droughts. During the onset of droughts in the wet-to-dry season (May–July) of both years, we found large-scale positive anomalies in VOD, leaf area index (LAI) and enhanced vegetation index (EVI) over the southern Amazonia. These observations are very likely caused by enhanced canopy growth. Concurrent below-average rainfall and above-average radiation during the wet-to-dry season can be interpreted as an early arrival of normal dry season conditions, leading to enhanced new leaf development and ecosystem photosynthesis, as supported by field observations. Our results suggest that further rainfall deficit into the subsequent dry season caused water and heat stress during the peak of 2005 and 2010 droughts (August–October) that exceeded the tolerance limits of the rainforest, leading to widespread negative VOD anomalies over the southern Amazonia. Significant VOD anomalies were observed mainly over the western part in 2005 and mainly over central and eastern parts in 2010. The total area with significant negative VOD anomalies was comparable between these two drought years, though the average magnitude of significant negative VOD anomalies was greater in 2005. This finding broadly agrees with the field observations indicating that the reduction in biomass carbon uptake was stronger in 2005 than 2010. The enhanced canopy growth

Index of refraction enhancement of calcite particles coated with zinc carbonate

Science.gov (United States)

Lattaud, Kathleen; Vilminot, Serge; Hirlimann, Charles; Parant, Hubert; Schoelkopf, Joachim; Gane, Patrick

2006-10-01

ZnCO 3 coating on calcite particles has been developed in order to enhance the index of refraction of this mineral that is used as a charge in paper, paint and polymer industries. Chemical reaction between calcite particles in an aqueous suspension with zinc chloride promotes the formation of a ZnCO 3 coating consisting of two layers with different interactions with the calcite particle. The refraction index of the resulting composite particles increases with the Zn/Ca ratio. A model allows to evaluate the coating thickness. The value of the scattering S and diffusion K coefficients of sheets coated with the ZnCO 3 coated particles reveal a dependence on the preparation conditions with a 15% increase for the best samples.

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.

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.

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.

Relationships of body mass index with serum carotenoids, tocopherols and retinol at steady-state and in response to a carotenoid-rich vegetable diet intervention in Filipino schoolchildren.

Science.gov (United States)

Ribaya-Mercado, Judy D; Maramag, Cherry C; Tengco, Lorena W; Blumberg, Jeffrey B; Solon, Florentino S

2008-04-01

In marginally nourished children, information is scarce regarding the circulating concentrations of carotenoids and tocopherols, and physiological factors influencing their circulating levels. We determined the serum concentrations of carotenoids, tocopherols and retinol at steady state and in response to a 9-week vegetable diet intervention in 9-12-year-old girls (n=54) and boys (n=65) in rural Philippines. We determined cross-sectional relationships of BMI (body mass index) with serum micronutrient levels, and whether BMI is a determinant of serum carotenoid responses to the ingestion of carotenoid-rich vegetables. We measured dietary nutrient intakes and assessed inflammation by measurement of serum C-reactive protein levels. The children had low serum concentrations of carotenoids, tocopherols and retinol as compared with published values for similar-aged children in the U.S.A. The low serum retinol levels can be ascribed to inadequate diets and were not the result of confounding due to inflammation. Significant inverse correlations of BMI and serum all-trans-beta-carotene, 13-cis-beta-carotene, alpha-carotene, lutein, zeaxanthin and alpha-tocopherol (but not beta-cryptoxanthin, lycopene and retinol) were observed among girls at baseline. The dietary intervention markedly enhanced the serum concentrations of all carotenoids. Changes in serum all-trans-beta-carotene and alpha-carotene (but not changes in lutein, zeaxanthin and beta-cryptoxanthin) in response to the dietary intervention were inversely associated with BMI in girls and boys. Thus, in Filipino school-aged children, BMI is inversely related to the steady-state serum concentrations of certain carotenoids and vitamin E, but not vitamin A, and is a determinant of serum beta- and alpha-carotene responses, but not xanthophyll responses, to the ingestion of carotenoid-rich vegetable meals.

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)

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

Consumer Acceptance Comparison Between Seasoned and Unseasoned Vegetables.

Science.gov (United States)

Feng, Yiming; Albiol Tapia, Marta; Okada, Kyle; Castaneda Lazo, Nuria Blanca; Chapman-Novakofski, Karen; Phillips, Carter; Lee, Soo-Yeun

2018-02-01

Recent findings show that approximately 87% of the U.S. population fail to meet the vegetable intake recommendations, with unpleasant taste of vegetables being listed as the primary reason for this shortfall. In this study, spice and herb seasoning was used to enhance palatability of vegetables, in order to increase consumer acceptance. In total, 749 panelists were screened and recruited as specific vegetable likers of the vegetable being tested or general vegetable likers. Four sessions were designed to evaluate the effect of seasoning within each type of vegetable, including broccoli, cauliflower, carrot, and green bean. Each panelist was only allowed to participate in one test session to evaluate only one vegetable type, so as to mitigate potential learning effect. Overall, the results showed that seasoned vegetables were significantly preferred over unseasoned vegetables (P trend of seasoned vegetable being preferred remained. The findings from this study demonstrate the effect of seasoning in enhancing consumer liking of vegetables, which may lead to increased consumption to be assessed in future studies. To improve the sensory properties of vegetables, masking the bitter taste of vegetables using spice and herb seasoning are gaining increasing attention. Our findings suggest that the overall liking of vegetables could be improved by incorporating spice and herb seasonings that are specifically formulated for each vegetable. Ultimately, developing and commercializing spice and herb seasonings may aid to increase vegetable consumption, as well as expanding the vegetable seasoning market. © 2018 The Authors Journal of Food Science published by Wiley Periodicals, Inc. on behalf of Institute of Food Technologists.

Enhancing the Extreme Climate Index (ECI) to monitor climate extremes for an index-based insurance scheme across Africa

Science.gov (United States)

Helmschrot, J.; Malherbe, J.; Chamunorwa, M.; Muthige, M.; Petitta, M.; Calmanti, S.; Cucchi, M.; Syroka, J.; Iyahen, E.; Engelbrecht, F.

2017-12-01

Climate services are a key component of National Adaptation Plan (NAP) processes, which require the analysis of current climate conditions, future climate change scenarios and the identification of adaptation strategies, including the capacity to finance and implement effective adaptation options. The Extreme Climate Facility (XCF) proposed by the African Risk Capacity (ARC) developed a climate index insurance scheme, which is based on the Extreme Climate Index (ECI): an objective, multi-hazard index capable of tracking changes in the frequency or magnitude of extreme weather events, thus indicating possible shifts to a new climate regime in various regions. The main hazards covered by ECI are extreme dry, wet and heat events, with the possibility of adding other region-specific risk events. The ECI is standardized across broad geographical regions, so that extreme events occurring under different climatic regimes in Africa can be compared. Initially developed by an Italian company specialized in Climate Services, research is now conducted at the CSIR and SASSCAL, to verify and further develop the ECI for application in southern African countries, through a project initiated by the World Food Programme (WFP) and ARC. The paper will present findings on the most appropriate definitions of extremely wet and dry conditions in Africa, in terms of their impact across a multitude of sub-regional climates of the African continent. Findings of a verification analysis of the ECI, as determined through vegetation monitoring data and the SASSCAL weather station network will be discussed. Changes in the ECI under climate change will subsequently be projected, using detailed regional projections generated by the CSIR and through the Coordinated Regional Downscaling Experiment (CORDEX). This work will be concluded by the development of a web-based climate service informing African Stakeholders on climate extremes.

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

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...

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.

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...

Pairing vegetables with a liked food and visually appealing presentation: promising strategies for increasing vegetable consumption among preschoolers.

Science.gov (United States)

Correia, Danielle C S; O'Connell, Meghan; Irwin, Melinda L; Henderson, Kathryn E

2014-02-01

Vegetable consumption among preschool children is below recommended levels. New evidence-based approaches to increase preschoolers' vegetable intake, particularly in the child care setting, are needed. This study tests the effectiveness of two community-based randomized interventions to increase vegetable consumption and willingness to try vegetables: (1) the pairing of a vegetable with a familiar, well-liked food and (2) enhancing the visual appeal of a vegetable. Fifty-seven preschoolers enrolled in a Child and Adult Care Food Program-participating child care center participated in the study; complete lunch and snack data were collected from 43 and 42 children, respectively. A within-subjects, randomized design was used, with order of condition counterbalanced. For lunch, steamed broccoli was served either on the side of or on top of cheese pizza. For a snack, raw cucumber was served either as semicircles with chive and an olive garnish or arranged in a visually appealing manner (in the shape of a caterpillar). Paired t-tests were used to determine differences in consumption of meal components, and McNemar's test was performed to compare willingness to taste. Neither visual appeal enhancement nor pairing with a liked food increased vegetable consumption. Pairing increased willingness to try the vegetable from 79% to 95% of children (p=0.07). Greater vegetable intake occurred at snack than at lunch. Further research should explore the strategy of pairing vegetables with liked foods. Greater consumption at snack underscores snack time as a critical opportunity for increasing preschool children's vegetable intake.

Sustainable Production of Underutilized Vegetables to Enhance ...

International Development Research Centre (IDRC) Digital Library (Canada)

... Research Fund (CIFSRF), a joint program of IDRC and the Canadian International Development Agency (CIDA) - aims to increase the food security and economic empowerment of resource-poor rural women farmers in Nigeria through the cultivation, processing, consumption and marketing of underutilized vegetables.

Negative Refractive Index Metasurfaces for Enhanced Biosensing

Directory of Open Access Journals (Sweden)

Dragan Tanasković

2010-12-01

Full Text Available In this paper we review some metasurfaces with negative values of effective refractive index, as scaffolds for a new generation of surface plasmon polariton-based biological or chemical sensors. The electromagnetic properties of a metasurface may be tuned by its full immersion into analyte, or by the adsorption of a thin layer on it, both of which change its properties as a plasmonic guide. We consider various simple forms of plasmonic crystals suitable for this purpose. We start with the basic case of a freestanding, electromagnetically symmetrical plasmonic slab and analyze different ultrathin, multilayer structures, to finally consider some two-dimensional “wallpaper” geometries like split ring resonator arrays and fishnet structures. A part of the text is dedicated to the possibility of multifunctionalization where a metasurface structure is simultaneously utilized both for sensing and for selectivity enhancement. Finally we give an overview of surface-bound intrinsic electromagnetic noise phenomena that limits the ultimate performance of a metasurfaces sensor.

Estimates of evapotranspiration for riparian sites (Eucalyptus) in the Lower Murray -Darling Basin using ground validated sap flow and vegetation index scaling techniques

Science.gov (United States)

Doody, T.; Nagler, P. L.; Glenn, E. P.

2014-12-01

Water accounting is becoming critical globally, and balancing consumptive water demands with environmental water requirements is especially difficult in in arid and semi-arid regions. Within the Murray-Darling Basin (MDB) in Australia, riparian water use has not been assessed across broad scales. This study therefore aimed to apply and validate an existing U.S. riparian ecosystem evapotranspiration (ET) algorithm for the MDB river systems to assist water resource managers to quantify environmental water needs over wide ranges of niche conditions. Ground-based sap flow ET was correlated with remotely sensed predictions of ET, to provide a method to scale annual rates of water consumption by riparian vegetation over entire irrigation districts. Sap flux was measured at nine locations on the Murrumbidgee River between July 2011 and June 2012. Remotely sensed ET was calculated using a combination of local meteorological estimates of potential ET (ETo) and rainfall and MODIS Enhanced Vegetation Index (EVI) from selected 250 m resolution pixels. The sap flow data correlated well with MODIS EVI. Sap flow ranged from 0.81 mm/day to 3.60 mm/day and corresponded to a MODIS-based ET range of 1.43 mm/day to 2.42 mm/day. We found that mean ET across sites could be predicted by EVI-ETo methods with a standard error of about 20% across sites, but that ET at any given site could vary much more due to differences in aquifer and soil properties among sites. Water use was within range of that expected. We conclude that our algorithm developed for US arid land crops and riparian plants is applicable to this region of Australia. Future work includes the development of an adjusted algorithm using these sap flow validated results.

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...

Enhanced subcarrier-index modulation-based asymmetrically clipped optical OFDM using even subcarriers

Science.gov (United States)

Guan, Rui; Xu, Wei; Yang, Zhaohui; Huang, Nuo; Wang, Jin-Yuan; Chen, Ming

2017-11-01

In this paper, we propose a subcarrier-index modulation-based asymmetrically clipped optical orthogonal frequency division multiplexing (SACO-OFDM) scheme for optical wireless communication (OWC) systems, which benefits from the subcarrier-index modulation (SIM) and asymmetrically clipped optical orthogonal frequency division multiplexing (ACO-OFDM) techniques. SACO-OFDM conveys additional information via the subcarrier indexing, and the error rate of the bit transmitted by the subcarrier indexing is much lower than that of the conventional M-ary modulation scheme. On the other hand, as the signal constellation in M-ary modulation is relieved, SACO-OFDM has simple transceiver structure and low detection complexity. Moreover, considering the spectral, an enhanced SACO-OFDM (ESACO-OFDM) using even subcarriers is proposed. In this technique, the odd subcarriers are activated for SACO-OFDM, and the imaginary part of even subcarriers are activated for pulse-amplitude-modulated discrete multitone (PAM-DMT). Clearly, ESACO-OFDM achieves better spectral efficiency than the conventional optical OFDM, since all subcarriers are used for data transmission. Simulation results verify the significant bit error rate (BER) and peak-to-average power ratio (PAPR) improvement by the proposed ESACO-OFDM, especially for the medium-to-high signal-to-noise ratio (SNR) regime.

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.

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.

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.

Refractive index sensing and surface-enhanced Raman spectroscopy using silver–gold layered bimetallic plasmonic crystals

Directory of Open Access Journals (Sweden)

Somi Kang

2017-11-01

Full Text Available Herein we describe the fabrication and characterization of Ag and Au bimetallic plasmonic crystals as a system that exhibits improved capabilities for quantitative, bulk refractive index (RI sensing and surface-enhanced Raman spectroscopy (SERS as compared to monometallic plasmonic crystals of similar form. The sensing optics, which are bimetallic plasmonic crystals consisting of sequential nanoscale layers of Ag coated by Au, are chemically stable and useful for quantitative, multispectral, refractive index and spectroscopic chemical sensing. Compared to previously reported homometallic devices, the results presented herein illustrate improvements in performance that stem from the distinctive plasmonic features and strong localized electric fields produced by the Ag and Au layers, which are optimized in terms of metal thickness and geometric features. Finite-difference time-domain (FDTD simulations theoretically verify the nature of the multimode plasmonic resonances generated by the devices and allow for a better understanding of the enhancements in multispectral refractive index and SERS-based sensing. Taken together, these results demonstrate a robust and potentially useful new platform for chemical/spectroscopic sensing.

Vegetation-climate feedbacks modulate rainfall patterns in Africa under future climate change

Science.gov (United States)

Wu, Minchao; Schurgers, Guy; Rummukainen, Markku; Smith, Benjamin; Samuelsson, Patrick; Jansson, Christer; Siltberg, Joe; May, Wilhelm

2016-07-01

Africa has been undergoing significant changes in climate and vegetation in recent decades, and continued changes may be expected over this century. Vegetation cover and composition impose important influences on the regional climate in Africa. Climate-driven changes in vegetation structure and the distribution of forests versus savannah and grassland may feed back to climate via shifts in the surface energy balance, hydrological cycle and resultant effects on surface pressure and larger-scale atmospheric circulation. We used a regional Earth system model incorporating interactive vegetation-atmosphere coupling to investigate the potential role of vegetation-mediated biophysical feedbacks on climate dynamics in Africa in an RCP8.5-based future climate scenario. The model was applied at high resolution (0.44 × 0.44°) for the CORDEX-Africa domain with boundary conditions from the CanESM2 general circulation model. We found that increased tree cover and leaf-area index (LAI) associated with a CO2 and climate-driven increase in net primary productivity, particularly over subtropical savannah areas, not only imposed important local effect on the regional climate by altering surface energy fluxes but also resulted in remote effects over central Africa by modulating the land-ocean temperature contrast, Atlantic Walker circulation and moisture inflow feeding the central African tropical rainforest region with precipitation. The vegetation-mediated feedbacks were in general negative with respect to temperature, dampening the warming trend simulated in the absence of feedbacks, and positive with respect to precipitation, enhancing rainfall reduction over the rainforest areas. Our results highlight the importance of accounting for vegetation-atmosphere interactions in climate projections for tropical and subtropical Africa.

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.

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.

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

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

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.

The Impact of CO2-Driven Vegetation Changes on Wildfire Risk

Science.gov (United States)

Skinner, C. B.; Poulsen, C. J.

2017-12-01

While wildfires are a key component of natural ecological restoration and succession, they also pose tremendous risks to human life, health, and property. Wildfire frequency is expected to increase in many regions as the radiative effects of elevated CO2 drive warmer surface air temperatures, earlier spring snow melt, and more frequent meteorological drought. However, high CO2 concentrations will also directly impact vegetation growth and physiology, potentially altering wildfire characteristics through changes in fuel amount and surface hydrology. Depending on the biome and time of year, these vegetation-driven responses may mitigate or enhance radiative-driven wildfire changes. In this study, we use a suite of earth system models from the Coupled Model Intercomparison Project 5 with active biogeophysics and biogeochemistry to understand how the vegetation response to high CO2 (CO2 quadrupling) contributes to future changes in wildfire risk across the globe. Across the models, projected CO2 fertilization enhances aboveground biomass (about a 30% leaf area index (LAI) increase averaged across the globe) during the spring and summer months, increasing the availability of wildfire fuel across all biomes. Despite greater LAI, models robustly project widespread reductions in summer season transpiration (about -15% averaged across the globe) in response to reduced stomatal conductance from CO2 physiological forcing. Reduced transpiration warms summer season near surface temperatures and lowers relative humidity across vegetated regions of the mid-to-high latitudes, heightening the risk of wildfire occurrence. However, as transpiration goes down in response to greater plant water use efficiency, a larger fraction of soil water remains in the soil, potentially halting the spread of wildfires in some regions. Given the myriad ways in which the vegetation response to CO2 may alter wildfire risk, and the robustness of the responses across models, an explicit simulation of

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.

Enhanced Deep Blue Aerosol Retrieval Algorithm: The Second Generation

Science.gov (United States)

Hsu, N. C.; Jeong, M.-J.; Bettenhausen, C.; Sayer, A. M.; Hansell, R.; Seftor, C. S.; Huang, J.; Tsay, S.-C.

2013-01-01

The aerosol products retrieved using the MODIS collection 5.1 Deep Blue algorithm have provided useful information about aerosol properties over bright-reflecting land surfaces, such as desert, semi-arid, and urban regions. However, many components of the C5.1 retrieval algorithm needed to be improved; for example, the use of a static surface database to estimate surface reflectances. This is particularly important over regions of mixed vegetated and non- vegetated surfaces, which may undergo strong seasonal changes in land cover. In order to address this issue, we develop a hybrid approach, which takes advantage of the combination of pre-calculated surface reflectance database and normalized difference vegetation index in determining the surface reflectance for aerosol retrievals. As a result, the spatial coverage of aerosol data generated by the enhanced Deep Blue algorithm has been extended from the arid and semi-arid regions to the entire land areas.

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.

Enhanced complete photonic bandgap in a moderate refractive index contrast chalcogenide-air system with connected-annular-rods photonic crystals

KAUST Repository

Hou, Jin

2018-03-27

Connected-annular-rods photonic crystals (CARPCs) in both triangular and square lattices are proposed to enhance the two-dimensional complete photonic bandgap (CPBG) for chalcogenide material systems with moderate refractive index contrast. For the typical chalcogenide-glass–air system with an index contrast of 2.8:1, the optimized square lattice CARPC exhibits a significantly larger normalized CPBG of about 13.50%, though the use of triangular lattice CARPC is unable to enhance the CPBG. It is almost twice as large as our previously reported result [IEEE J. Sel. Top. Quantum Electron. 22, 4900108 (2016) [CrossRef] ]. Moreover, the CPBG of the square-lattice CARPC could remain until an index contrast as low as 2.24:1. The result not only favors wideband CPBG applications for index contrast systems near 2.8:1, but also makes various optical applications that are dependent on CPBG possible for more widely refractive index contrast systems.

Focused Ultrasound-Induced Blood-Brain Barrier Opening: Association with Mechanical Index and Cavitation Index Analyzed by Dynamic Contrast-Enhanced Magnetic-Resonance Imaging.

Science.gov (United States)

Chu, Po-Chun; Chai, Wen-Yen; Tsai, Chih-Hung; Kang, Shih-Tsung; Yeh, Chih-Kuang; Liu, Hao-Li

2016-09-15

Focused ultrasound (FUS) with microbubbles can temporally open the blood-brain barrier (BBB), and the cavitation activities of microbubbles play a key role in the BBB-opening process. Previous attempts used contrast-enhanced magnetic resonance imaging (CE-MRI) to correlate the mechanical index (MI) with the scale of BBB-opening, but MI only partially gauged acoustic activities, and CE-MRI did not fully explore correlations of pharmacodynamic/pharmacokinetic behaviors. Recently, the cavitation index (CI) has been derived to serve as an indicator of microbubble-ultrasound stable cavitation, and may also serve as a valid indicator to gauge the level of FUS-induced BBB opening. This study investigates the feasibility of gauging FUS-induced BBB opened level via the two indexes, MI and CI, through dynamic contrast-enhanced (DCE)-MRI analysis as well as passive cavitation detection (PCD) analysis. Pharmacodynamic/pharmacokinetic parameters derived from DCE-MRI were characterized to identify the scale of FUS-induced BBB opening. Our results demonstrated that DCE-MRI can successfully access pharmacodynamic/pharmacokinetic BBB-opened behavior, and was highly correlated both with MI and CI, implying the feasibility in using these two indices to gauge the scale of FUS-induced BBB opening. The proposed finding may facilitate the design toward using focused ultrasound as a safe and reliable noninvasive CNS drug delivery.

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.

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.

Assessing Vegetation Cover Dynamics Induced by Policy-Driven Ecological Restoration and Implication to Soil Erosion in Southern China.

Science.gov (United States)

Zhang, Jien; Wang, Tianming; Ge, Jianping

2015-01-01

In the aftermath of the severe droughts and floods at the end of the 20th century, the Chinese government launched several ecological restoration projects, including the Natural Forest Protection Program in 1998 and the Grain-for-Green Program in 1999, to promote afforestation and reforestation to reduce surface runoff and consequent soil erosion nationwide. However, it is still unclear how vegetation has changed in southern China since the launch of these programs. In this study, we used the MODIS Enhanced Vegetation Index (EVI) to analyze the vegetation cover dynamics in southern China from 2000 to 2009 and evaluate the resulting effects of controlling soil erosion. Our observations indicate that 5.3% of the study area significantly increased and 0.98% significantly decreased in EVI value (p soil erosion based upon monitoring sediment yields at hydrologic stations in the Yangtze River. This study displays the spatial patterns of trend in vegetation growth since the beginning of the 21st century in southern China and highlights the important role of China's afforestation program.

Evaluation of a linear spectral mixture model and vegetation indices (NDVI and EVI) in a study of schistosomiasis mansoni and Biomphalaria glabrata distribution in the state of Minas Gerais, Brazil.

Science.gov (United States)

Guimarães, Ricardo J P S; Freitas, Corina C; Dutra, Luciano V; Scholte, Ronaldo G C; Amaral, Ronaldo S; Drummond, Sandra C; Shimabukuro, Yosio E; Oliveira, Guilherme C; Carvalho, Omar S

2010-07-01

This paper analyses the associations between Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) on the prevalence of schistosomiasis and the presence of Biomphalaria glabrata in the state of Minas Gerais (MG), Brazil. Additionally, vegetation, soil and shade fraction images were created using a Linear Spectral Mixture Model (LSMM) from the blue, red and infrared channels of the Moderate Resolution Imaging Spectroradiometer spaceborne sensor and the relationship between these images and the prevalence of schistosomiasis and the presence of B. glabrata was analysed. First, we found a high correlation between the vegetation fraction image and EVI and second, a high correlation between soil fraction image and NDVI. The results also indicate that there was a positive correlation between prevalence and the vegetation fraction image (July 2002), a negative correlation between prevalence and the soil fraction image (July 2002) and a positive correlation between B. glabrata and the shade fraction image (July 2002). This paper demonstrates that the LSMM variables can be used as a substitute for the standard vegetation indices (EVI and NDVI) to determine and delimit risk areas for B. glabrata and schistosomiasis in MG, which can be used to improve the allocation of resources for disease control.

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

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)

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

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....

Cumulative drought and land-use impacts on perennial vegetation across a North American dryland region

Science.gov (United States)

Munson, Seth M.; Long, A. Lexine; Wallace, Cynthia; Webb, Robert H.

2016-01-01

Question The decline and loss of perennial vegetation in dryland ecosystems due to global change pressures can alter ecosystem properties and initiate land degradation processes. We tracked changes of perennial vegetation using remote sensing to address the question of how prolonged drought and land-use intensification have affected perennial vegetation cover across a desert region in the early 21st century? Location Mojave Desert, southeastern California, southern Nevada, southwestern Utah and northwestern Arizona, USA. Methods We coupled the Moderate-Resolution Imaging Spectroradiometer Enhanced Vegetation Index (MODIS-EVI) with ground-based measurements of perennial vegetation cover taken in about 2000 and about 2010. Using the difference between these years, we determined perennial vegetation changes in the early 21st century and related these shifts to climate, soil and landscape properties, and patterns of land use. Results We found a good fit between MODIS-EVI and perennial vegetation cover (2000: R2 = 0.83 and 2010: R2 = 0.74). The southwestern, far southeastern and central Mojave Desert had large declines in perennial vegetation cover in the early 21st century, while the northeastern and southeastern portions of the desert had increases. These changes were explained by 10-yr precipitation anomalies, particularly in the cool season and during extreme dry or wet years. Areas heavily impacted by visitor use or wildfire lost perennial vegetation cover, and vegetation in protected areas increased to a greater degree than in unprotected areas. Conclusions We find that we can extrapolate previously documented declines of perennial plant cover to an entire desert, and demonstrate that prolonged water shortages coupled with land-use intensification create identifiable patterns of vegetation change in dryland regions.

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.

Remote Estimation of Vegetation Fraction and Flower Fraction in Oilseed Rape with Unmanned Aerial Vehicle Data

Directory of Open Access Journals (Sweden)

Shenghui Fang

2016-05-01

Full Text Available This study developed an approach for remote estimation of Vegetation Fraction (VF and Flower Fraction (FF in oilseed rape, which is a crop species with conspicuous flowers during reproduction. Canopy reflectance in green, red, red edge and NIR bands was obtained by a camera system mounted on an unmanned aerial vehicle (UAV when oilseed rape was in the vegetative growth and flowering stage. The relationship of several widely-used Vegetation Indices (VI vs. VF was tested and found to be different in different phenology stages. At the same VF when oilseed rape was flowering, canopy reflectance increased in all bands, and the tested VI decreased. Therefore, two algorithms to estimate VF were calibrated respectively, one for samples during vegetative growth and the other for samples during flowering stage. The results showed that the Visible Atmospherically Resistant Index (VARIgreen worked most accurately for estimating VF in flower-free samples with an Root Mean Square Error (RMSE of 3.56%, while the Enhanced Vegetation Index (EVI2 was the best in flower-containing samples with an RMSE of 5.65%. Based on reflectance in green and NIR bands, a technique was developed to identify whether a sample contained flowers and then to choose automatically the appropriate algorithm for its VF estimation. During the flowering season, we also explored the potential of using canopy reflectance or VIs to estimate FF in oilseed rape. No significant correlation was observed between VI and FF when soil was visible in the sensor’s field of view. Reflectance at 550 nm worked well for FF estimation with coefficient of determination (R2 above 0.6. Our model was validated in oilseed rape planted under different nitrogen fertilization applications and in different phenology stages. The results showed that it was able to predict VF and FF accurately in oilseed rape with RMSE below 6%.

Role of vegetation on river bank accretion

NARCIS (Netherlands)

Vargas Luna, A.

2016-01-01

There is rising awareness of the need to include the effects of vegetation in studies dealing with the morphological response of rivers. Vegetation growth on river banks and floodplains alters the river bed topography, reduces the bank erosion rates and enhances the development of new floodplains

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...

Reconstruction of the refractive index gradient by x-ray diffraction enhanced computed tomography

Energy Technology Data Exchange (ETDEWEB)

Wang Junyue [Beijing Synchrotron Radiation Facility, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049 (China); Zhu Peiping [Beijing Synchrotron Radiation Facility, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049 (China); Yuan Qingxi [Beijing Synchrotron Radiation Facility, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049 (China); Huang Wanxia [Beijing Synchrotron Radiation Facility, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049 (China); Shu Hang [Beijing Synchrotron Radiation Facility, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049 (China); Chen Bo [Department of Physics, University of Science and Technology of China, Hefei 230026 (China); Hu Tiandou [Beijing Synchrotron Radiation Facility, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049 (China); Wu Ziyu [Beijing Synchrotron Radiation Facility, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049 (China)

2006-07-21

The computed tomography technique cannot easily be extended to diffraction enhanced imaging (DEI) because, while from DEI we may extract the refractive index gradient in one dimension, from the conventional CT reconstruction algorithm we may reconstruct only a scalar quantity. However, recently we showed that changing the direction of the scan axis, and collecting a set of data related to the three-dimensional distribution of the refractive index gradient of the sample, a CT image was obtained. The algorithm we used is based on the conventional CT algorithm but with a specific pre-processing of the projection data. The mathematical framework of the procedure and a simple CT experiment are presented and discussed.

Reconstruction of the refractive index gradient by x-ray diffraction enhanced computed tomography

International Nuclear Information System (INIS)

Wang Junyue; Zhu Peiping; Yuan Qingxi; Huang Wanxia; Shu Hang; Chen Bo; Hu Tiandou; Wu Ziyu

2006-01-01

The computed tomography technique cannot easily be extended to diffraction enhanced imaging (DEI) because, while from DEI we may extract the refractive index gradient in one dimension, from the conventional CT reconstruction algorithm we may reconstruct only a scalar quantity. However, recently we showed that changing the direction of the scan axis, and collecting a set of data related to the three-dimensional distribution of the refractive index gradient of the sample, a CT image was obtained. The algorithm we used is based on the conventional CT algorithm but with a specific pre-processing of the projection data. The mathematical framework of the procedure and a simple CT experiment are presented and discussed

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

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

Enhancing Competitiveness Business Strategy of Organic Vegetables Using Analytical Hierarchy Process (AHP

Directory of Open Access Journals (Sweden)

Pristiana Widyastuti

2017-09-01

Full Text Available Public awareness about healthy lifestyles leads people to want to understand more about the food they consume. Choosing organic vegetables is one alternative choices when seeking to have a healthy body and healthy lifestyle. Unfortunately, not a lot of organic vegetable farmers in Indonesia succeed in seizing the organic vegetable market rather than the non-organic and the competition with imported organic vegetables into Indonesia prevents farmers from thriving. This study aims to: 1 Analyze the factors affecting the competitiveness of the organic vegetables market; 2 Analyze the appropriate strategy for increasing the competitiveness of the organic vegetables market; 3 Analyze the factors priority strategies for improving the competitiveness of the organic vegetables market. Porter's Generic Model and Analysis Analytical Hierarchy Process (AHP is used to determine the best strategy. The research found that organic vegetables marketing channels are still dominated by conventional market; the higher cost for intensive cultivation of organic vegetables. The main strategies are derived from the analysis is focusing on market delivery. There needs to be retailers of organic vegetables either modern or traditional to display these products. The establishment of organic vegetable outlets and online marketing that are not dependent on large retail (hypermarket become recommendations in this study. Bahasa Indonesia Abstrak: Kesadaran masyarakat tentang gaya hidup sehat memberi pilihan kepada masyarakat untuk memahami makanan yang mereka konsumsi. Pilihan sayuran organik merupakan salah satu alternatif untuk memiliki tubuh sehat dan gaya hidup sehat bagi masyarakat. Sayangnya, tidak banyak petani sayuran organik di Indonesia yang berhasil merebut pasar sayuran organik daripada non organic. Persaingan produk impor sayuran organik ke Indonesia membuat petani tidak bisa berkembang. Penelitian ini bertujuan untuk: 1 Menganalisis faktor-faktor yang

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.

Monitoring vegetation change in Abu Dhabi Emirate from 1996 to 2000 and 2004 using Landsat Satellite Imagery

International Nuclear Information System (INIS)

Starbuck, M.J.; Tamayo, J.

2007-01-01

In the fall of 2001, a study was initiated to investigate vegetation changes in the Abu Dhabi Emirates. The vast majority of vegetation present in the region is irrigated and analysis of vegetation change will support groundwater investigations in the region by indicating areas of increased water use. Satellite-based imaging systems provide a good source of data for such an analysis. The recent analysis was completed between February and November 2002 using Landsat 5 Thematic Mapper satellite imagery acquired in 1996 and Landsat 7 Enhanced Thematic Mapper Plus imagery acquired in 2000. These assessments were augmented in 2004with the study of Landsat 7 imagery acquired in early 2004. The total area of vegetation for each of seven study areas was calculated using the Normalized Difference Vegetation Index (NDVI) technique. Multiband image classification was used to differentiate general vegetation types. Change analysis consisted of simple NDVI image differencing and post-classification change matrices. Measurements of total vegetation are for the Abu Dhabi Emirate indicate an increase from 77,200 hectares in 1996 to 162,700 hectares in 2000 (110% increase). Based on comparison with manual interpretation of satellite imagery, the amount of under-reporting of irrigated land is estimated at about 15% of the actual area. From the assessment of 2004 Landset imagery, it was found that the growth of irrigated vegetation in most areas of Emirate had stabilized and had actually slightly decreased in some cases. The decreases are probably due to variability in the measurement technique and not due to actual decreases in area of vegetation. (author)

Contributions of seed bank and vegetative propagules to vegetation composition on prairie dog colonies in western South Dakota

Science.gov (United States)

Emily R. Helms; Lan Xu; Jack L. Butler

2012-01-01

Characterizing the contributions of the seed bank and vegetative propagules will enhance our understanding of community resiliency associated with prairie dog disturbances. Our objective was to determine the effects of ecological condition (EC) and distance from burrows on the soil seed bank and vegetative propagules. Based on species composition of the extant...

Plasma-enhanced growth, composition, and refractive index of silicon oxy-nitride films

DEFF Research Database (Denmark)

Mattsson, Kent Erik

1995-01-01

Secondary ion mass spectrometry and refractive index measurements have been carried out on silicon oxy-nitride produced by plasma-enhanced chemical vapor deposition (PECVD). Nitrous oxide and ammonia were added to a constant flow of 2% silane in nitrogen, to produce oxy-nitride films with atomic...... nitrogen concentrations between 2 and 10 at. %. A simple atomic valence model is found to describe both the measured atomic concentrations and published material compositions for silicon oxy-nitride produced by PECVD. A relation between the Si–N bond concentration and the refractive index is found......-product. A model, that combine the chemical net reaction and the stoichiometric rules, is found to agree with measured deposition rates for given material compositions. Effects of annealing in a nitrogen atmosphere has been investigated for the 400 °C– 1100 °C temperature range. It is observed that PECVD oxy...

Gradient-index phononic crystal lens-based enhancement of elastic wave energy harvesting

Science.gov (United States)

Tol, S.; Degertekin, F. L.; Erturk, A.

2016-08-01

We explore the enhancement of structure-borne elastic wave energy harvesting, both numerically and experimentally, by exploiting a Gradient-Index Phononic Crystal Lens (GRIN-PCL) structure. The proposed GRIN-PCL is formed by an array of blind holes with different diameters on an aluminum plate, where the blind hole distribution is tailored to obtain a hyperbolic secant gradient profile of refractive index guided by finite-element simulations of the lowest asymmetric mode Lamb wave band diagrams. Under plane wave excitation from a line source, experimentally measured wave field validates the numerical simulation of wave focusing within the GRIN-PCL domain. A piezoelectric energy harvester disk located at the first focus of the GRIN-PCL yields an order of magnitude larger power output as compared to the baseline case of energy harvesting without the GRIN-PCL on the uniform plate counterpart.

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.

Recent change of vegetation growth trend in China

International Nuclear Information System (INIS)

Peng Shushi; Fang Jingyun; Piao Shilong; Chen, Anping; Xu Liang; Myneni, Ranga B; Cao Chunxiang; Pinzon, Jorge E; Tucker, Compton J

2011-01-01

Using satellite-derived normalized difference vegetation index (NDVI) data, several previous studies have indicated that vegetation growth significantly increased in most areas of China during the period 1982–99. In this letter, we extended the study period to 2010. We found that at the national scale the growing season (April–October) NDVI significantly increased by 0.0007 yr −1 from 1982 to 2010, but the increasing trend in NDVI over the last decade decreased in comparison to that of the 1982–99 period. The trends in NDVI show significant seasonal and spatial variances. The increasing trend in April and May (AM) NDVI (0.0013 yr −1 ) is larger than those in June, July and August (JJA) (0.0003 yr −1 ) and September and October (SO) (0.0008 yr −1 ). This relatively small increasing trend of JJA NDVI during 1982–2010 compared with that during 1982–99 (0.0012 yr −1 ) (Piao et al 2003 J. Geophys. Res.—Atmos. 108 4401) implies a change in the JJA vegetation growth trend, which significantly turned from increasing (0.0039 yr −1 ) to slightly decreasing ( − 0.0002 yr −1 ) in 1988. Regarding the spatial pattern of changes in NDVI, the growing season NDVI increased (over 0.0020 yr −1 ) from 1982 to 2010 in southern China, while its change was close to zero in northern China, as a result of a significant changing trend reversal that occurred in the 1990s and early 2000s. In northern China, the growing season NDVI significantly increased before the 1990s as a result of warming and enhanced precipitation, but decreased after the 1990s due to drought stress strengthened by warming and reduced precipitation. Our results also show that the responses of vegetation growth to climate change vary across different seasons and ecosystems.

Recent Change of Vegetation Growth Trend in China

Science.gov (United States)

Peng, Shushi; Chen, Anping; Xu, Liang; Cao, Chunxiang; Fang, Jingyun; Myneni, Ranga B.; Pinzon, Jorge E.; Tucker, COmpton J.; Piao, Shilong

2011-01-01

Using satellite-derived normalized difference vegetation index (NDVI) data, several previous studies have indicated that vegetation growth significantly increased in most areas of China during the period 1982-99. In this letter, we extended the study period to 2010. We found that at the national scale the growing season (April-October) NDVI significantly increased by 0.0007/yr from 1982 to 2010, but the increasing trend in NDVI over the last decade decreased in comparison to that of the 1982-99 period. The trends in NDVI show significant seasonal and spatial variances. The increasing trend in April and May (AM) NDVI (0.0013/yr is larger than those in June, July and August (JJA) (0.0003/yr) and September and October (SO) (0.0008/yr). This relatively small increasing trend of JJA NDVI during 1982-2010 compared with that during 1982-99 (0.0012/yr) (Piao et al 2003 J. Geophys. Res.-Atmos. 108 4401) implies a change in the JJA vegetation growth trend, which significantly turned from increasing (0.0039/yr) to slightly decreasing (0:0002/yr) in 1988. Regarding the spatial pattern of changes in NDVI, the growing season NDVI increased (over 0.0020/yr) from 1982 to 2010 in southern China, while its change was close to zero in northern China, as a result of a significant changing trend reversal that occurred in the 1990s and early 2000s. In northern China, the growing season NDVI significantly increased before the 1990s as a result of warming and enhanced precipitation, but decreased after the 1990s due to drought stress strengthened by warming and reduced precipitation. Our results also show that the responses of vegetation growth to climate change vary across different seasons and ecosystems.

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

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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.

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

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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.

Vegetation Patchiness Enhances Hydrological Connectivity in River Deltas Below the Percolation Threshold

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Wright, K. A.; Hiatt, M. R.; Passalacqua, P.

2017-12-01

The humanitarian and ecological importance of coastal deltas has led many to research the factors influencing their ecogeomorphic evolution, in hopes of predicting the response of these regions to the growing number of natural and anthropogenic threats they face. One area of this effort, in which many unresolved questions remain, concerns the hydrological connectivity between the distributary channels and interdistributary islands, which field observations and numerical modeling have shown to be significant. Island vegetation is known to affect the degree of connectivity, but the effect of the spatial distribution of vegetation on connectivity remains an important question. This research aims to determine to what extent vegetation percent cover, patch size, and plant density affect connectivity in an idealized deltaic system. A 2D hydrodynamic model was used to numerically solve the shallow water equations in an idealized channel-island complex, modeled after Wax Lake Delta in Louisiana. For each model run, vegetation patches were distributed randomly throughout the islands according to a specified percent cover and patch size. Vegetation was modeled as a modified bed roughness, which was varied to represent a range of sparse-to-dense vegetation. To determine the effect of heterogeneity, the results of each patchy scenario were compared to results from a uniform run with the same spatially-averaged roughness. It was found that, while all patchy model runs demonstrated more channel-island connectivity than comparable uniform runs, this was particularly true when vegetation patches were dense and covered distributions in the deltaic islands, which can have implications for the fate and transport of sediment/nutrients. These results indicate that the spatial distribution of vegetation can have a notable impact on our ability to model connectivity in deltaic systems.

[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.

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

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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.

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

Multispectral and Panchromatic used Enhancement Resolution and Study Effective Enhancement on Supervised and Unsupervised Classification Land – Cover

Science.gov (United States)

Salman, S. S.; Abbas, W. A.

2018-05-01

The goal of the study is to support analysis Enhancement of Resolution and study effect on classification methods on bands spectral information of specific and quantitative approaches. In this study introduce a method to enhancement resolution Landsat 8 of combining the bands spectral of 30 meters resolution with panchromatic band 8 of 15 meters resolution, because of importance multispectral imagery to extracting land - cover. Classification methods used in this study to classify several lands -covers recorded from OLI- 8 imagery. Two methods of Data mining can be classified as either supervised or unsupervised. In supervised methods, there is a particular predefined target, that means the algorithm learn which values of the target are associated with which values of the predictor sample. K-nearest neighbors and maximum likelihood algorithms examine in this work as supervised methods. In other hand, no sample identified as target in unsupervised methods, the algorithm of data extraction searches for structure and patterns between all the variables, represented by Fuzzy C-mean clustering method as one of the unsupervised methods, NDVI vegetation index used to compare the results of classification method, the percent of dense vegetation in maximum likelihood method give a best results.

Preparation of function-enhanced vegetable oils

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Hiroshi Maeda

2016-01-01

Full Text Available Background: Previously, we (HM found that most commercially available edible oils, which were processed by hexane extraction followed by a number of purification steps, were extremely low in anti-peroxy radical (ROO., or radical scavenging activity. This is a great contrast to the respective virgin oils as exemplified by extra-virgin olive oil or crude rape seed oil [1-4] (Figure 1. Therefore, such highly purified oils will became prooxidant and less desirable food components in terms of health oriented diet. Oxidized oils may eventually cause DNA cleavages, modification of proteins, RNA, and lipids, as well as cellular damage, or promote inflammation and carcinogenesis at later time [5-9]. These commercial oils of low antioxidant activity may be improved by adding functionally effective antioxidative components, by using dried vegetable-waste such as tomato-juice-waste-residues and wine-ferment-waste-residues. Their antioxiative components will be transferred into the functionally poor grade edible oils, and consequently, one can improve the quality of such functionally poor oils and thereby contributing human health [2,8,9]. The purpose of this paper is to report a practical procedure to fortify functionally low grade conventional edible oils to functionally enriched edible oils using dried vegetable-waste residues such as tomato juice waste, and wine-ferment-residues, or other vegetable-waste residues. Methods: (1 Preparation and measurements of lycopene and carotenoid enriched oils. To 5.0g or 1.0g of the dried residue of tomato juice waste, 100ml of commercial rape seed (canola oil was added respectively. Each mixture was incubated at room temperature in dark for several weeks. Amount of lycopene and carotenoids extracted into the oil was monitored by increase of absorption (400-550nm and fluorescence at 470nm of carotenoid. Grape-juice ferment (wine waste was similarly prepared after hot air drying, and immersed in canola oil. (2

Application of Cocktail method in vegetation classification

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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.

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.

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.

Satellite observations of high northern latitude vegetation productivity changes between 1982 and 2008: ecological variability and regional differences

Energy Technology Data Exchange (ETDEWEB)

Beck, Pieter S A; Goetz, Scott J, E-mail: pbeck@whrc.org [Woods Hole Research Center, 149 Woods Hole Road, Falmouth, MA 02540 (United States)

2011-10-15

To assess ongoing changes in high latitude vegetation productivity we compared spatiotemporal patterns in remotely sensed vegetation productivity in the tundra and boreal zones of North America and Eurasia. We compared the long-term GIMMS (Global Inventory Modeling and Mapping Studies) NDVI (Normalized Difference Vegetation Index) to the more recent and advanced MODIS (Moderate Resolution Imaging Spectroradiometer) NDVI data set, and mapped circumpolar trends in a gross productivity metric derived from the former. We then analyzed how temporal changes in productivity differed along an evergreen-deciduous gradient in boreal Alaska, along a shrub cover gradient in Arctic Alaska, and during succession after fire in boreal North America and northern Eurasia. We find that the earlier reported contrast between trends of increasing tundra and decreasing boreal forest productivity has amplified in recent years, particularly in North America. Decreases in boreal forest productivity are most prominent in areas of denser tree cover and, particularly in Alaska, evergreen forest stands. On the North Slope of Alaska, however, increases in tundra productivity do not appear restricted to areas of higher shrub cover, which suggests enhanced productivity across functional vegetation types. Differences in the recovery of post-disturbance vegetation productivity between North America and Eurasia are described using burn chronosequences, and the potential factors driving regional differences are discussed.

Satellite observations of high northern latitude vegetation productivity changes between 1982 and 2008: ecological variability and regional differences

International Nuclear Information System (INIS)

Beck, Pieter S A; Goetz, Scott J

2011-01-01

To assess ongoing changes in high latitude vegetation productivity we compared spatiotemporal patterns in remotely sensed vegetation productivity in the tundra and boreal zones of North America and Eurasia. We compared the long-term GIMMS (Global Inventory Modeling and Mapping Studies) NDVI (Normalized Difference Vegetation Index) to the more recent and advanced MODIS (Moderate Resolution Imaging Spectroradiometer) NDVI data set, and mapped circumpolar trends in a gross productivity metric derived from the former. We then analyzed how temporal changes in productivity differed along an evergreen-deciduous gradient in boreal Alaska, along a shrub cover gradient in Arctic Alaska, and during succession after fire in boreal North America and northern Eurasia. We find that the earlier reported contrast between trends of increasing tundra and decreasing boreal forest productivity has amplified in recent years, particularly in North America. Decreases in boreal forest productivity are most prominent in areas of denser tree cover and, particularly in Alaska, evergreen forest stands. On the North Slope of Alaska, however, increases in tundra productivity do not appear restricted to areas of higher shrub cover, which suggests enhanced productivity across functional vegetation types. Differences in the recovery of post-disturbance vegetation productivity between North America and Eurasia are described using burn chronosequences, and the potential factors driving regional differences are discussed.

Native Roadside Vegetation that Enhances Soil Erosion Control in Boreal Scandinavia

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Annika K. Jägerbrand

2014-07-01

Full Text Available This study focused on identifying vegetation characteristics associated with erosion control at nine roadside sites in mid-West Sweden. A number of vegetation characteristics such as cover, diversity, plant functional type, biomass and plant community structure were included. Significant difference in cover between eroded and non-eroded sub-sites was found in evergreen shrubs, total cover, and total above ground biomass. Thus, our results support the use of shrubs in order to stabilize vegetation and minimize erosion along roadsides. However, shrubs are disfavored by several natural and human imposed factors. This could have several impacts on the long-term management of roadsides in boreal regions. By both choosing and applying active management that supports native evergreen shrubs in boreal regions, several positive effects could be achieved along roadsides, such as lower erosion rate and secured long-term vegetation cover. This could also lead to lower costs for roadside maintenance as lower erosion rates would require less frequent stabilizing treatments and mowing could be kept to a minimum in order not to disfavor shrubs.

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

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...

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.

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.

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

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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.

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

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

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

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.

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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

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.

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.

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.

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)

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...

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

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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.

The Influence and Compatibility of Vegetable Oils and other ...

African Journals Online (AJOL)

The vegetable oils used as skin permeation enhancers were selected on the basis of compatibility studies data. A total of eight monolithic systems were prepared by using different concentrations of drug-polymers-permeation enhancers. The permeation parameters, flux, permeability coefficient, enhancement ratio and ...

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.

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

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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.

[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.

Monitoring of Vegetation Impact Due to Trampling on Cadillac Mountain Summit Using High Spatial Resolution Remote Sensing Data Sets

Science.gov (United States)

Kim, Min-Kook; Daigle, John J.

2012-11-01

Cadillac Mountain—the highest peak along the eastern seaboard of the United States—is a major tourist destination in Acadia National Park, Maine. Managing vegetation impact due to trampling on the Cadillac Mountain summit is extremely challenging because of the large number of visitors and the general open nature of landscape in this fragile subalpine environmental setting. Since 2000, more intensive management strategies—based on placing physical barriers and educational messages for visitors—have been employed to protect threatened vegetation, decrease vegetation impact, and enhance vegetation recovery in the vicinity of the summit loop trail. The primary purpose of this study was to evaluate the effect of the management strategies employed. For this purpose, vegetation cover changes between 2001 and 2007 were detected using multispectral high spatial resolution remote sensing data sets. A normalized difference vegetation index was employed to identify the rates of increase and decrease in the vegetation areas. Three buffering distances (30, 60, and 90 m) from the edges of the trail were used to define multiple spatial extents of the site, and the same spatial extents were employed at a nearby control site that had no visitors. No significant differences were detected between the mean rates of vegetation increase and decrease at the experimental site compared with a nearby control site in the case of a small spatial scale (≤30 m) comparison (in all cases P > 0.05). However, in the medium (≤60 m) and large (≤90 m) spatial scales, the rates of increased vegetation were significantly greater and rates of decreased vegetation significantly lower at the experimental site compared with the control site (in all cases P Management implications are explored in terms of the spatial strategies used to decrease the impact of trampling on vegetation.

Close relationship between spectral vegetation indices and Vcmax in deciduous and mixed forests

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Yanlian Zhou

2014-04-01

Full Text Available Seasonal variations of photosynthetic capacity parameters, notably the maximum carboxylation rate, Vcmax, play an important role in accurate estimation of CO2 assimilation in gas-exchange models. Satellite-derived normalised difference vegetation index (NDVI, enhanced vegetation index (EVI and model-data fusion can provide means to predict seasonal variation in Vcmax. In this study, Vcmax was obtained from a process-based model inversion, based on an ensemble Kalman filter (EnKF, and gross primary productivity, and sensible and latent heat fluxes measured using eddy covariance technique at two deciduous broadleaf forest sites and a mixed forest site. Optimised Vcmax showed considerable seasonal and inter-annual variations in both mixed and deciduous forest ecosystems. There was noticeable seasonal hysteresis in Vcmax in relation to EVI and NDVI from 8 d composites of satellite data during the growing period. When the growing period was phenologically divided into two phases (increasing VIs and decreasing VIs phases, significant seasonal correlations were found between Vcmax and VIs, mostly showing R2>0.95. Vcmax varied exponentially with increasing VIs during the first phase (increasing VIs, but second and third-order polynomials provided the best fits of Vcmax to VIs in the second phase (decreasing VIs. The relationships between NDVI and EVI with Vcmax were different. Further efforts are needed to investigate Vcmax–VIs relationships at more ecosystem sites to the use of satellite-based VIs for estimating Vcmax.

Vegetation Changes along the Qinghai-Tibet Plateau Engineering Corridor Since 2000 Induced by Climate Change and Human Activities

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Yi Song

2018-01-01

Full Text Available The Qinghai-Tibet (QT Plateau Engineering Corridor is located in the hinterland of the QT Plateau, which is highly sensitive to global climate change. Climate change causes permafrost degradation, which subsequently affects vegetation growth. This study focused on the vegetation dynamics and their relationships with climate change and human activities in the region surrounding the QT Plateau Engineering Corridor. The vegetation changes were inferred by applying trend analysis, the Mann-Kendall trend test and abrupt change analysis. Six key regions, each containing 40 nested quadrats that ranged in size from 500 × 500 m to 20 × 20 km, were selected to determine the spatial scales of the impacts from different factors. Cumulative growing season integrated enhanced vegetation index (CGSIEVI values were calculated for each of the nested quadrats of different sizes to indicate the overall vegetation state over the entire year at different spatial scales. The impacts from human activities, a sudden increase in precipitation and permafrost degradation were quantified at different spatial scales using the CGSIEVI values and meteorological data based on the double mass curve method. Three conclusions were derived. First, the vegetation displayed a significant increasing trend over 23.6% of the study area. The areas displaying increases were mainly distributed in the Hoh Xil. Of the area where the vegetation displayed a significant decreasing trend, 72.4% was made up of alpine meadows. Second, more vegetation, especially the alpine meadows, has begun to degenerate or experience more rapid degradation since 2007 due to permafrost degradation and overgrazing. Finally, an active layer depth of 3 m to 3.2 m represents a limiting depth for alpine meadows.

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.

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

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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.

[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.

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

Evaporative cooling over the Tibetan Plateau induced by vegetation growth

Science.gov (United States)

Shen, Miaogen; Piao, Shilong; Jeong, Su-Jong; Zhou, Liming; Zeng, Zhenzhong; Ciais, Philippe; Chen, Deliang; Huang, Mengtian; Jin, Chun-Sil; Li, Laurent Z. X.; Li, Yue; Myneni, Ranga B.; Yang, Kun; Zhang, Gengxin; Zhang, Yangjian; Yao, Tandong

2015-01-01

In the Arctic, climate warming enhances vegetation activity by extending the length of the growing season and intensifying maximum rates of productivity. In turn, increased vegetation productivity reduces albedo, which causes a positive feedback on temperature. Over the Tibetan Plateau (TP), regional vegetation greening has also been observed in response to recent warming. Here, we show that in contrast to arctic regions, increased growing season vegetation activity over the TP may have attenuated surface warming. This negative feedback on growing season vegetation temperature is attributed to enhanced evapotranspiration (ET). The extra energy available at the surface, which results from lower albedo, is efficiently dissipated by evaporative cooling. The net effect is a decrease in daily maximum temperature and the diurnal temperature range, which is supported by statistical analyses of in situ observations and by decomposition of the surface energy budget. A daytime cooling effect from increased vegetation activity is also modeled from a set of regional weather research and forecasting (WRF) mesoscale model simulations, but with a magnitude smaller than observed, likely because the WRF model simulates a weaker ET enhancement. Our results suggest that actions to restore native grasslands in degraded areas, roughly one-third of the plateau, will both facilitate a sustainable ecological development in this region and have local climate cobenefits. More accurate simulations of the biophysical coupling between the land surface and the atmosphere are needed to help understand regional climate change over the TP, and possible larger scale feedbacks between climate in the TP and the Asian monsoon system. PMID:26170316

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

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

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.

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

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.

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).

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

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.

Influence of food acidulants and antioxidant spices on the bioaccessibility of beta-carotene from selected vegetables.

Science.gov (United States)

Veda, Supriya; Platel, Kalpana; Srinivasan, Krishnapura

2008-09-24

Four common food acidulants--amchur, lime, tamarind, and kokum--and two antioxidant spices--turmeric and onion--were examined for their influence on the bioaccessibility of beta-carotene from two fleshy and two leafy vegetables. Amchur and lime generally enhanced the bioaccessibility of beta-carotene from these test vegetables in many instances. Such an improved bioaccessibility was evident in both raw and heat-processed vegetables. The effect of lime juice was generally more pronounced than that of amchur. Turmeric significantly enhanced the bioaccessibility of beta-carotene from all of the vegetables tested, especially when heat-processed. Onion enhanced the bioaccessibility of beta-carotene from pressure-cooked carrot and amaranth leaf and from open-pan-boiled pumpkin and fenugreek leaf. Lime juice and the antioxidant spices turmeric and onion minimized the loss of beta-carotene during heat processing of the vegetables. In the case of antioxidant spices, improved bioaccessibility of beta-carotene from heat-processed vegetables is attributable to their role in minimizing the loss of this provitamin. Lime juice, which enhanced the bioaccessibility of this provitamin from both raw and heat-processed vegetables, probably exerted this effect by some other mechanism in addition to minimizing the loss of beta-carotene. Thus, the presence of food acidulants (lime juice/amchur) and antioxidant spices (turmeric/onion) proved to be advantageous in the context of deriving maximum beta-carotene from the vegetable sources.

Browse Title Index

African Journals Online (AJOL)

Items 151 - 200 of 207 ... Vol 3, No 2 (2007), Rural Women\\'s Involvement In Dry Season Vegetable Production And Marketing In Ezinihitte Local Government Area Of Imo State, Nigeria, Abstract. AN Imoh, JP ... Vol 6, No 1 (2010), Strategic advertising for enhanced agri-business development in Abia State, Nigeria, Abstract.

Master Veteran Index (MVI)

Data.gov (United States)

Department of Veterans Affairs — As of June 28, 2010, the Master Veteran Index (MVI) database based on the enhanced Master Patient Index (MPI) is the authoritative identity service within the VA,...

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)

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...

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.

Menu-engineering in restaurants - adapting portion sizes on plates to enhance vegetable consumption

NARCIS (Netherlands)

Reinders, Machiel J.; Huitink, Marlijn; Dijkstra, S.C.; Maaskant, Anna J.; Heijnen, Joris

2017-01-01

Background: The aim of this research was to investigate whether increased portion sizes of vegetables and decreased portion sizes of meat on main dishes increased the amount of vegetables consumed in a real-life restaurant setting without affecting customer satisfaction. The participants were

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...

Mathematical Modeling of Vegetable-Oil Crystallization

DEFF Research Database (Denmark)

Hjorth, Jeppe Lindegaard

be desirable to enhance specific properties such as shelf life, viscosity, texture, sensory aspects and physical appearance. Vegetable oils and fats constitute a considerable part of many food products such as chocolate, margarine, bread, spreads and ice cream. Several attractive properties found......In recent years the food sector has experienced a great boost in demand for tailor-made fats and oils to produce so-called functional foods, where ingredients have been carefully modified to yield products with specific, valuable properties. Depending on market segment and product, it may...... in these products, including flavor release, melting profile and appearance, are governed by the oils and fats added. Consequently, altering the fat phase may lead to enhanced properties of the products. The primary focus of the present work is vegetable oils and fats originating from different sources covering...

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

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.

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...

Dynamic Response of Satellite-Derived Vegetation Growth to Climate Change in the Three North Shelter Forest Region in China

Directory of Open Access Journals (Sweden)

Bin He

2015-08-01

Full Text Available Since the late 1970s, the Chinese government has initiated ecological restoration programs in the Three North Shelter Forest System Project (TNSFSP area. Whether accelerated climate change will help or hinder these efforts is still poorly understood. Using the updated and extended AVHRR NDVI3g dataset from 1982 to 2011 and corresponding climatic data, we investigated vegetation variations in response to climate change. The results showed that the overall state of vegetation in the study region has improved over the past three decades. Vegetation cover significantly decreased in 23.1% and significantly increased in 21.8% of the study area. An increase in all three main vegetation types (forest, grassland, and cropland was observed, but the trend was only statistically significant in cropland. In addition, bare and sparsely vegetated areas, mainly located in the western part of the study area, have significantly expanded since the early 2000s. A moisture condition analysis indicated that the study area experienced significant climate variations, with warm-wet conditions in the western region and warm-dry conditions in the eastern region. Correlation analysis showed that variations in the Normalized Difference Vegetation Index (NDVI were positively correlated with precipitation and negatively correlated with temperature. Ultimately, climate change influenced vegetation growth by controlling the availability of soil moisture. Further investigation suggested that the positive impacts of precipitation on NDVI have weakened in the study region, whereas the negative impacts from temperature have been enhanced in the eastern study area. However, over recent years, the negative temperature impacts have been converted to positive impacts in the western region. Considering the variations in the relationship between NDVI and climatic variables, the warm–dry climate in the eastern region is likely harmful to vegetation growth, whereas the warm�

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 ...

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.

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.

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.

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

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.

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

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.

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.

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 ...

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.

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.

Role of Antidesma ghaesembilla Gaertn in Enriching the Depauperate Bird Community in “Cogon” Imperata cylindrica (L. Raeuschel Dominated Grassland in Swidden Vegetation Matrix

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Alejandro A. Bernardo Jr.

2017-11-01

Full Text Available The study was conducted to understand the role of Antidesma ghaesembilla Gaertn in enhancing the avifaunal diversity in Imperata cylindrica (L. Raeuschel dominated grassland patches and to realize the influence of adjacent vegetations on the assemblage of birds that feed on the fruit of this tree. An avifaunal survey was conducted on “Cogon” dominated grassland patches adjacent to selected vegetations such as primary forest, secondary forest and upland agricultural area. A total of 250 birds belonging to 19 species representing ten families were found feeding on the fruits of Antidesma ghaesembilla. The site adjacent to secondary forest has the highest species richness, abundance and diversity index values. This accentuates the combined influence of the open and forest dwelling bird species thriving in the secondary forest. The sites adjacent to the primary forest and to the agricultural area have the same species richness but differ in species composition as reflected by the low similarity index. More forest dwelling bird species were recorded near the forest while more open dwelling bird species were recorded near the agricultural area. This highlights the spillover effect of the adjacent vegetations on the feeding bird assemblage. The presence of several endemic and conservation priority bird species that feed on the fruits of Antidesma ghaesembilla unfolds its important role in avifaunal conservation. Finally, the wide collection of fruit eating bird species attracted to it emphasized its importance in improving the overall avifaunal diversity in Imperata cylindrica dominated grassland patches within the swidden vegetation matrix.

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.

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.

Oxygation enhances growth, gas exchange and salt tolerance of vegetable soybean and cotton in a saline vertisol.

Science.gov (United States)

Bhattarai, Surya P; Midmore, David J

2009-07-01

Impacts of salinity become severe when the soil is deficient in oxygen. Oxygation (using aerated water for subsurface drip irrigation of crop) could minimize the impact of salinity on plants under oxygen-limiting soil environments. Pot experiments were conducted to evaluate the effects of oxygation (12% air volume/volume of water) on vegetable soybean (moderately salt tolerant) and cotton (salt tolerant) in a salinized vertisol at 2, 8, 14, 20 dS/m EC(e). In vegetable soybean, oxygation increased above ground biomass yield and water use efficiency (WUE) by 13% and 22%, respectively, compared with the control. Higher yield with oxygation was accompanied by greater plant height and stem diameter and reduced specific leaf area and leaf Na+ and Cl- concentrations. In cotton, oxygation increased lint yield and WUE by 18% and 16%, respectively, compared with the control, and was accompanied by greater canopy light interception, plant height and stem diameter. Oxygation also led to a greater rate of photosynthesis, higher relative water content in the leaf, reduced crop water stress index and lower leaf water potential. It did not, however, affect leaf Na+ or Cl- concentration. Oxygation invariably increased, whereas salinity reduced the K+ : Na+ ratio in the leaves of both species. Oxygation improved yield and WUE performance of salt tolerant and moderately tolerant crops under saline soil environments, and this may have a significant impact for irrigated agriculture where saline soils pose constraints to crop production.

Can a canopy temperature-based stress index enhance water use efficiency in irrigated wine grape under arid conditions?

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Enhancement of irrigation water use efficiency and water productivity in arid wine grape production regions is hindered by a lack of automated, real-time methods for monitoring and interpreting vine water status. A normalized, water stress index calculated from real-time vine canopy temperature meas...

Improved Vegetation Profiles with GOCI Imagery Using Optimized BRDF Composite

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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.

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

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

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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.

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.

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

Utility of Rice Bran Mixed with Fermentation Extract of Vegetable Waste Unconditioned as Probiotics from Vegetable Market

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Cahya Setya Utama

2013-06-01

Full Text Available The aimed of the study was to enhance utilization of Lactobacillus Sp. and Saccharomyces sp. as starter for fermentation of waste cabbage and green mustard to enhance the utility of rice bran as an ingredient of poultry feed. The first stage of the study was to characterize the extract of fermented wasted vegetable with difference concentration of glucose and different period of time for incubation. Completely randomized design using 3 x 3 factorial with three replications was used for the first stage of the study. The second stage of the study was to evaluate the effectiveness of the extract of fermented wasted vegetable to improve the quality and utility of rice bran. Completely randomized design with four treatments and 4 replications. The third stage of the study was to obtain the value of nitrogen, calcium and phosphorus retention, as well as metabolic energy of rice bran after fermentation in broiler hatching. The third stage analysis was conducted by t-test analysis. The results of the study showed that the microbial characteristics on the extract of fermented wasted vegetable in two days incubation time and 2% concentration of glucose was able to produce pH of 3.80, log of total lactic acid bacteria 7.38 and types of microbes that grow predominantly were Lactobacillus Sp. and Saccharomyces Sp. The effectiveness of the extract fermented wasted vegetable for the fermentation of rice bran were shown in additional concentration of extract wasted vegetable of 40% with a moisture content of  toluene 65.24%, 13.36% ash, 14.93% protein, 7.61% crude fat, 12.39% crude fiber, nitrogen free extract material (NFE 51.59% and 0.07% biomass. The biological value and the availability of fermented rice bran were higher than unfermented rice bran on the broiler chickens after hatching. The values were justified from nitrogen, calcium and phosphorus retention also metabolic energy. The study concluded that the benefits and utility of rice bran could

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

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...

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...

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

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.

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

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

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

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.

An ecological vegetation-activated sludge process (V-ASP) for decentralized wastewater treatment: system development, treatment performance, and mathematical modeling.

Science.gov (United States)

Yuan, Jiajia; Dong, Wenyi; Sun, Feiyun; Li, Pu; Zhao, Ke

2016-05-01

An environment-friendly decentralized wastewater treatment process that is comprised of activated sludge process (ASP) and wetland vegetation, named as vegetation-activated sludge process (V-ASP), was developed for decentralized wastewater treatment. The long-term experimental results evidenced that the vegetation sequencing batch reactor (V-SBR) process had consistently stable higher removal efficiencies of organic substances and nutrients from domestic wastewater compared with traditional sequencing batch reactor (SBR). The vegetation allocated into V-SBR system could not only remove nutrients through its vegetation transpiration ratio but also provide great surface area for microorganism activity enhancement. This high vegetation transpiration ratio enhanced nutrients removal effectiveness from wastewater mainly by flux enhancement, oxygen and substrate transportation acceleration, and vegetation respiration stimulation. A mathematical model based on ASM2d was successfully established by involving the specific function of vegetation to simulate system performance. The simulation results on the influence of operational parameters on V-ASP treatment effectiveness demonstrated that V-SBR had a high resistance to seasonal temperature fluctuations and influent loading shocking.

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)

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.

The relation of vegetation over the Tibetan Plateau to rainfall in China during the boreal summer

Energy Technology Data Exchange (ETDEWEB)

Zuo, Zhiyan; Zhang, Renhe [Chinese Academy of Meteorological Sciences, State Key Laboratory of Severe Weather, Beijing (China); Zhao, Ping [National Meteorological Information Centre, Beijing (China)

2011-03-15

The relationship between vegetation on the Tibetan Plateau (TP) and summer (June-August) rainfall in China is investigated using the normalized difference vegetation index (NDVI) from the Earth Resources Observation System and observed rainfall data from surface 616 stations in China for the period 1982-2001. The leading mode of empirical orthogonal functions analysis for summer rainfall variability in China shows a negative anomaly in the area from the Yangtze River valley to the Yellow River valley (YYR) and most of western China, and positive anomalies in southern China and North China. This mode is significantly correlated with summer NDVI around the southern TP. This finding indicates that vegetation around the southern TP has a positive correlation with summer rainfall in southern China and North China, but a negative correlation with summer rainfall in YYR and western China. We investigate the physical process by which vegetation change affects summer rainfall in China. Increased vegetation around the southern TP is associated with a descending motion anomaly on the TP and the neighboring area to the east, resulting in reduced surface heating and a lower Bowen ratio, accompanied by weaker divergence in the upper troposphere and convergence in the lower troposphere on the TP. In turn, these changes result in the weakening of and a westward shift in the southern Asian High in the upper troposphere and thereby the weakening of and an eastward withdrawal in the western Pacific subtropical high. These features result in weak circulation in the East Asian summer monsoon. Consequently, enhanced summer rainfall occurs in southern China and North China, but reduced rainfall in YYR. (orig.)

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.

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.

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.

Spatial mapping of leaf area index using hyperspectral remote sensing for hydrological applications with a particular focus on canopy interception

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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.

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

Assessing Vegetation Cover Dynamics Induced by Policy-Driven Ecological Restoration and Implication to Soil Erosion in Southern China.

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Jien Zhang

Full Text Available In the aftermath of the severe droughts and floods at the end of the 20th century, the Chinese government launched several ecological restoration projects, including the Natural Forest Protection Program in 1998 and the Grain-for-Green Program in 1999, to promote afforestation and reforestation to reduce surface runoff and consequent soil erosion nationwide. However, it is still unclear how vegetation has changed in southern China since the launch of these programs. In this study, we used the MODIS Enhanced Vegetation Index (EVI to analyze the vegetation cover dynamics in southern China from 2000 to 2009 and evaluate the resulting effects of controlling soil erosion. Our observations indicate that 5.3% of the study area significantly increased and 0.98% significantly decreased in EVI value (p < 0.05. The spring EVI had largest increase in space. The conversions of croplands on steep slopes to forests resulting from national policies led to significant increases in EVI. The increase in EVI was not driven by annual average temperature and annual precipitation. By referencing ecological restoration statistical data and field observations, we showed that ecological restoration programs significantly improved vegetation cover in southern China. Increase in the area of farmland-converted forestlands has reduced soil erosion based upon monitoring sediment yields at hydrologic stations in the Yangtze River. This study displays the spatial patterns of trend in vegetation growth since the beginning of the 21st century in southern China and highlights the important role of China's afforestation program.

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).

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.

Quantification of net carbon flux from plastic greenhouse vegetable cultivation: A full carbon cycle analysis

International Nuclear Information System (INIS)

Wang Yan; Xu Hao; Wu Xu; Zhu Yimei; Gu Baojing; Niu Xiaoyin; Liu Anqin; Peng Changhui; Ge Ying; Chang Jie

2011-01-01

Plastic greenhouse vegetable cultivation (PGVC) has played a vital role in increasing incomes of farmers and expanded dramatically in last several decades. However, carbon budget after conversion from conventional vegetable cultivation (CVC) to PGVC has been poorly quantified. A full carbon cycle analysis was used to estimate the net carbon flux from PGVC systems based on the combination of data from both field observations and literatures. Carbon fixation was evaluated at two pre-selected locations in China. Results suggest that: (1) the carbon sink of PGVC is 1.21 and 1.23 Mg C ha -1 yr -1 for temperate and subtropical area, respectively; (2) the conversion from CVC to PGVC could substantially enhance carbon sink potential by 8.6 times in the temperate area and by 1.3 times in the subtropical area; (3) the expansion of PGVC usage could enhance the potential carbon sink of arable land in China overall. - Highlights: → We used full carbon (C) cycle analysis to estimate the net C flux from cultivation. → The plastic greenhouse vegetable cultivation system in China can act as a C sink. → Intensified agricultural practices can generate C sinks. → Expansion of plastic greenhouse vegetable cultivation can enhance regional C sink. - The conversion from conventional vegetable cultivation to plastic greenhouse vegetable cultivation could substantially enhance carbon sink potential by 8.6 and 1.3 times for temperate and subtropical area, respectively.

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

Study Of The Physicochemical Analysis Of Biodiesel Produced From Waste Vegetable Oil.

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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.

Enhanced complete photonic bandgap in a moderate refractive index contrast chalcogenide-air system with connected-annular-rods photonic crystals

KAUST Repository

Hou, Jin; Yang, Chunyong; Li, Xiaohang; Cao, Zhenzhou; Chen, Shaoping

2018-01-01

. For the typical chalcogenide-glass–air system with an index contrast of 2.8:1, the optimized square lattice CARPC exhibits a significantly larger normalized CPBG of about 13.50%, though the use of triangular lattice CARPC is unable to enhance the CPBG

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...

Coatings for minimally processed fruits and vegetables

Science.gov (United States)

Fresh-cut fruit and vegetables are gaining increasing popularity and market share. Techniques to enhance stability of fresh cut produce are reviewed. Among these techniques, edibles coatings can provide protection against dehydration, microbial decay and decrease events related to physiological sene...

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…

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.

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

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

Integrated analysis of climate, soil, topography and vegetative growth in Iberian viticultural regions.

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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.

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

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.

Australian consumer awareness of health benefits associated with vegetable consumption.

Science.gov (United States)

Rekhy, Reetica; Khan, Aila; Eason, Jocelyn; Mactavish-West, Hazel; Lister, Carolyn; Mcconchie, Robyn

2017-04-01

The present study investigated the perceived health benefits of specific vegetable consumption to guide the use of nutrition and health claims on vegetable marketing collateral. Free elicitation and consumer ranking data were collected through an online survey of 1000 adults from across Australia and analysed for the perceived importance of vegetables in the daily diet, number of serves consumed per day, knowledge about health-related benefits of specific vegetables and perceived health benefits of vegetable consumption. The importance of vegetables in the diet and daily vegetable consumption was higher in people from an English-speaking background, females, people aged 45 years and over and people living in non-metropolitan areas. Digestion was selected as the major health benefit from consumption of specific vegetables. However, understanding of the health benefits of specific vegetable consumption was relatively low among consumers. Half of the respondents were not sure of the health benefits associated with specific vegetables, except for carrots and spinach. Some respondents volunteered nutrient content or other information. There was no clear indication that consumers understand the specific health benefits conferred by consumption of vegetables. Nutrient and health benefit labelling therefore has the capacity to enhance knowledge of vegetable consumers. It is recommended that health benefit labelling be tailored to promote greater consumption of vegetables in those demographic groups where vegetable consumption was lower. The present study assists the Australian vegetable industry in helping consumers make more informed consumption choices. © 2016 Dietitians Association of Australia.

EVALUATING THE TECHNICAL EFFICIENCY OF SMALLHOLDER VEGETABLE FARMS IN DIVERSE AGROECOLOGICAL REGIONS OF NEPAL

Directory of Open Access Journals (Sweden)

Rudra Bahadur Shrestha

2017-01-01

Full Text Available Enhancing the efficiency of vegetable farms is crucial to increase the vegetable outputs for meeting the demand for growing population. This study evaluated the technical efficiency and explored factors determining the efficiencies of smallholder vegetable farms in diversified agro-ecological regions using Stochastic Frontier Analysis (SFA with cross-section data collected in 2013. The results revealed that average technical efficiency was found to be 0.77 and the variance parameters were highly significant indicating that the inefficiency existed in vegetable farms. The inefficiency gap could improve by operating the farms at the frontier level. The input variables consisting of land, labor, animal power, fertilizer, compost, pesticide, and capital were proved to be the important factors in determining the level of outputs. Meanwhile, the major sources of the inefficiencies identified were: age of farmer, training to the farmers, and infrastructure development. The efficiency in vegetable production can be improved by allocating input resources at the optimum levels, encouraging younger farmers in vegetable production, increasing training and extension activities, enhancing market access to the farmers, and developing infrastructures with regard to vegetable production.

Computed tomography of x-ray index of refraction using the diffraction enhanced imaging method

International Nuclear Information System (INIS)

Dilmanian, F.A.; Ren, B.; Wu, X.Y.; Orion, I.; Zhong, Z.; Thomlinson, W.C.; Chapman, L.D.

2000-01-01

Diffraction enhanced imaging (DEI) is a new, synchrotron-based, x-ray radiography method that uses monochromatic, fan-shaped beams, with an analyser crystal positioned between the subject and the detector. The analyser allows the detection of only those x-rays transmitted by the subject that fall into the acceptance angle (central part of the rocking curve) of the monochromator/analyser system. As shown by Chapman et al , in addition to the x-ray attenuation, the method provides information on the out-of-plane angular deviation of x-rays. New images result in which the image contrast depends on the x-ray index of refraction and on the yield of small-angle scattering, respectively. We implemented DEI in the tomography mode at the National Synchrotron Light Source using 22 keV x-rays, and imaged a cylindrical acrylic phantom that included oil-filled, slanted channels. The resulting 'refraction CT image' shows the pure image of the out-of-plane gradient of the x-ray index of refraction. No image artefacts were present, indicating that the CT projection data were a consistent set. The 'refraction CT image' signal is linear with the gradient of the refractive index, and its value is equal to that expected. The method, at the energy used or higher, has the potential for use in clinical radiography and in industry. (author)

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;

Advances in estimation methods of vegetation water content based on optical remote sensing techniques

Institute of Scientific and Technical Information of China (English)

无

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.

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)

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

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

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

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.

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.

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.

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.

Enhanced Removal of a Human Norovirus Surrogate from Fresh Vegetables and Fruits by a Combination of Surfactants and Sanitizers▿

Science.gov (United States)

Predmore, Ashley; Li, Jianrong

2011-01-01

Fruits and vegetables are major vehicles for transmission of food-borne enteric viruses since they are easily contaminated at pre- and postharvest stages and they undergo little or no processing. However, commonly used sanitizers are relatively ineffective for removing human norovirus surrogates from fresh produce. In this study, we systematically evaluated the effectiveness of surfactants on removal of a human norovirus surrogate, murine norovirus 1 (MNV-1), from fresh produce. We showed that a panel of surfactants, including sodium dodecyl sulfate (SDS), Nonidet P-40 (NP-40), Triton X-100, and polysorbates, significantly enhanced the removal of viruses from fresh fruits and vegetables. While tap water alone and chlorine solution (200 ppm) gave only <1.2-log reductions in virus titer in all fresh produce, a solution containing 50 ppm of surfactant was able to achieve a 3-log reduction in virus titer in strawberries and an approximately 2-log reduction in virus titer in lettuce, cabbage, and raspberries. Moreover, a reduction of approximately 3 logs was observed in all the tested fresh produce after sanitization with a solution containing a combination of 50 ppm of each surfactant and 200 ppm of chlorine. Taken together, our results demonstrate that the combination of a surfactant with a commonly used sanitizer enhanced the efficiency in removing viruses from fresh produce by approximately 100 times. Since SDS is an FDA-approved food additive and polysorbates are recognized by the FDA as GRAS (generally recognized as safe) products, implementation of this novel sanitization strategy would be a feasible approach for efficient reduction of the virus load in fresh produce. PMID:21622782

Does urban vegetation mitigate air pollution in northern conditions?

International Nuclear Information System (INIS)

Setälä, Heikki; Viippola, Viljami; Rantalainen, Anna-Lea; Pennanen, Arto; Yli-Pelkonen, Vesa

2013-01-01

It is generally accepted that urban vegetation improves air quality and thereby enhances the well-being of citizens. However, empirical evidence on the potential of urban trees to mitigate air pollution is meager, particularly in northern climates with a short growing season. We studied the ability of urban park/forest vegetation to remove air pollutants (NO 2 , anthropogenic VOCs and particle deposition) using passive samplers in two Finnish cities. Concentrations of each pollutant in August (summer; leaf-period) and March (winter, leaf-free period) were slightly but often insignificantly lower under tree canopies than in adjacent open areas, suggesting that the role of foliage in removing air pollutants is insignificant. Furthermore, vegetation-related environmental variables (canopy closure, number and size of trees, density of understorey vegetation) did not explain the variation in pollution concentrations. Our results suggest that the ability of urban vegetation to remove air pollutants is minor in northern climates. -- Highlights: ► The ability of northern urban vegetation to remove air pollutants is minor. ► Vegetation-related environmental variables had no effect on air pollution levels. ► The ability of vegetation to clean air did not differ between summer and winter. ► Dry deposition passive samplers proved applicable in urban air pollution study. -- The ability of urban vegetation to remove air pollutants seems to be minor in northern climates

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).

Enhanced Dispersion and Removal of Ammonia Emitted from a Poultry House with a Vegetative Environmental Buffer

Directory of Open Access Journals (Sweden)

Kyoung S. Ro

2018-03-01

Full Text Available Vegetative environmental buffers (VEBs, which are composed of tolerant trees, shrubs, and tall grasses, can be used to control and reduce the transport of ammonia (NH3 emissions from animal feeding operations (AFOs. However, the effectiveness of VEBs has not been quantitated. In this study, we measure the dispersion and removal of NH3 in simulated emissions from a small broiler house that was equipped with a VEB. The dispersion enhancement due to the VEB was estimated by comparing the measured downwind concentration of the co-released tracer gas, methane (CH4, to the theoretical CH4 concentrations at the same distance downwind without the VEB. The accuracy of the theoretical downwind concentrations calculated using the forward Lagrangian stochastic (fLS technique was 95%, which was validated by comparing the measured and calculated CH4 concentrations in a separate experiment without the VEB. The VEB enhanced the dispersion of CH4 and reduced the downwind concentration to 63% of the theoretical concentration. In addition to dispersion, the VEB removed another 22% of the NH3, resulting in a net 51% decrease of the theoretical downwind concentration. These results clearly demonstrated that the VEB was effective both in dispersing and removing NH3 emitted from the broiler house.

Modelling spatial and temporal dynamics of gross primary production in the Sahel from earth-observation-based photosynthetic capacity and quantum efficiency

DEFF Research Database (Denmark)

Tagesson, Håkan Torbern; Ardoe, Jonas; Cappelaere, Bernard

2017-01-01

based on earth observation (EO) (normalized difference vegetation index (NDVI), renormalized difference vegetation index (RDVI), enhanced vegetation index (EVI) and shortwave infrared water stress index (SIWSI)); and (3) to study the applicability of EO upscaled Fopt and α for GPP modelling purposes...... impacted by anthropogenic land use. Upscaled GPP for the Sahel 2001-2014 was 736 ± 39 gCm-2yr-1. This study indicates the strong applicability of EO as a tool for spatially explicit estimates of GPP, Fopt and α incorporating EO-based Fopt and α in dynamic global vegetation models could improve estimates...

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

Análise da dinâmica sazonal de fitofisionomias do bioma Mata Atlântica com base em índices de vegetação do sensor MODIS/TERRA / Analysis of the seasonal dynamics of some Atlantic Forest biome physiognomies with basis of vegetation indices derived from MOD

Directory of Open Access Journals (Sweden)

Elói Lennon Dalla Nora

2010-08-01

Full Text Available Composições de dezesseis dias de índices de vegetação do sensor Moderate Resolution Imaging Spectroradiometer (MODIS, com resolução espacial de 250 metros, a bordo do satélite TERRA, foram utilizadas para caracterizar a dinâmica sazonal no ano de 2008 de duas fitofisionomias do bioma Mata Atlântica e analisar a sua dinâmica espectral. Os índices Normalized Difference Vegetation Index (NDVI e Enhanced Vegetation Index (EVI, calculados a partir dos dados do sensor MODIS e uma base comum de pixels, foram comparados entre si e com uma base de dados de ordem climática (temperatura e precipitação, para cada fitofisionomia. Os resultados indicaram que os fragmentos de floresta estacional decídua e floresta ombrófila mista apresentam um padrão sazonal comum, porém, com variações de amplitude em relação a cada índice. O EVI apresentou-se mais sensível às variações anuais da vegetação em relação ao NDVI, demonstrando-se mais eficiente. Para ambas as formações florestais se estabelece uma correlação positiva entre o perfil EVI e NDVI com as variações de temperatura. A dinâmica espectral/temporal revelou um contraste marcante sob condições sazonais distintas convergindo com o padrão apresentado pelos índices de vegetação. Os dados produzidos indicam potencialidades da utilização do sensor MODIS para o monitoramento contínuo das formações florestais sulinas com resolução espacial moderada e alta resolução temporal. AbstractModerate resolution imaging spectroradiometer (MODIS 16-day vegetation index composites with 250 meters of spatial resolution from TERRA satellites were used to characterize the seasonal dynamics in the period of 2008 of two physiognomies of Atlantic Forest biome and to analyze its spectral dynamics. The Normalized Difference Vegetation Index (NDVI and Enhanced Vegetation Index (EVI, calculated from the data of MODIS sensor and a common base of pixels, were compared between themselves

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.)

Linking Vital Rates of Landbirds on a Tropical Island to Rainfall and Vegetation Greenness.

Directory of Open Access Journals (Sweden)

James F Saracco

Full Text Available Remote tropical oceanic islands are of high conservation priority, and they are exemplified by range-restricted species with small global populations. Spatial and temporal patterns in rainfall and plant productivity may be important in driving dynamics of these species. Yet, little is known about environmental influences on population dynamics for most islands and species. Here we leveraged avian capture-recapture, rainfall, and remote-sensed habitat data (enhanced vegetation index [EVI] to assess relationships between rainfall, vegetation greenness, and demographic rates (productivity, adult apparent survival of three native bird species on Saipan, Northern Mariana Islands: rufous fantail (Rhipidura rufifrons, bridled white-eye (Zosterops conspicillatus, and golden white-eye (Cleptornis marchei. Rainfall was positively related to vegetation greenness at all but the highest rainfall levels. Temporal variation in greenness affected the productivity of each bird species in unique ways. Predicted productivity of rufous fantail was highest when dry and wet season greenness values were high relative to site-specific 5-year seasonal mean values (i.e., relative greenness; while the white-eye species had highest predicted productivity when relative greenness contrasted between wet and dry seasons. Survival of rufous fantail and bridled white eye was positively related to relative dry-season greenness and negatively related to relative wet-season greenness. Bridled white-eye survival also showed evidence of a positive response to overall greenness. Our results highlight the potentially important role of rainfall regimes in affecting population dynamics of species on oceanic tropical islands. Understanding linkages between rainfall, vegetation, and animal population dynamics will be critical for developing effective conservation strategies in this and other regions where the seasonal timing, extent, and variability of rainfall is expected to change in the

Monitoring the Wobbe Index of Natural Gas Using Fiber-Enhanced Raman Spectroscopy.

Science.gov (United States)

Sandfort, Vincenz; Trabold, Barbara M; Abdolvand, Amir; Bolwien, Carsten; Russell, Philip St. J; Wöllenstein, Jürgen; Palzer, Stefan

2017-11-24

The fast and reliable analysis of the natural gas composition requires the simultaneous quantification of numerous gaseous components. To this end, fiber-enhanced Raman spectroscopy is a powerful tool to detect most components in a single measurement using a single laser source. However, practical issues such as detection limit, gas exchange time and background Raman signals from the fiber material still pose obstacles to utilizing the scheme in real-world settings. This paper compares the performance of two types of hollow-core photonic crystal fiber (PCF), namely photonic bandgap PCF and kagomé-style PCF, and assesses their potential for online determination of the Wobbe index. In contrast to bandgap PCF, kagomé-PCF allows for reliable detection of Raman-scattered photons even below 1200 cm -1 , which in turn enables fast and comprehensive assessment of the natural gas quality of arbitrary mixtures.

Estimation of Crop Gross Primary Production (GPP): I. Impact of MODIS Observation Footprint and Impact of Vegetation BRDF Characteristics

Science.gov (United States)

Zhang, Qingyuan; Cheng, Yen-Ben; Lyapustin, Alexei I.; Wang, Yujie; Xiao, Xiangming; Suyker, Andrew; Verma, Shashi; Tan, Bin; Middleton, Elizabeth M.

2014-01-01

Accurate estimation of gross primary production (GPP) is essential for carbon cycle and climate change studies. Three AmeriFlux crop sites of maize and soybean were selected for this study. Two of the sites were irrigated and the other one was rainfed. The normalized difference vegetation index (NDVI), the enhanced vegetation index (EVI), the green band chlorophyll index (CIgreen), and the green band wide dynamic range vegetation index (WDRVIgreen) were computed from the moderate resolution imaging spectroradiometer (MODIS) surface reflectance data. We examined the impacts of the MODIS observation footprint and the vegetation bidirectional reflectance distribution function (BRDF) on crop daily GPP estimation with the four spectral vegetation indices (VIs - NDVI, EVI, WDRVIgreen and CIgreen) where GPP was predicted with two linear models, with and without offset: GPP = a × VI × PAR and GPP = a × VI × PAR + b. Model performance was evaluated with coefficient of determination (R2), root mean square error (RMSE), and coefficient of variation (CV). The MODIS data were filtered into four categories and four experiments were conducted to assess the impacts. The first experiment included all observations. The second experiment only included observations with view zenith angle (VZA) = 35? to constrain growth of the footprint size,which achieved a better grid cell match with the agricultural fields. The third experiment included only forward scatter observations with VZA = 35?. The fourth experiment included only backscatter observations with VZA = 35?. Overall, the EVI yielded the most consistently strong relationships to daily GPP under all examined conditions. The model GPP = a × VI × PAR + b had better performance than the model GPP = a × VI × PAR, and the offset was significant for most cases. Better performance was obtained for the irrigated field than its counterpart rainfed field. Comparison of experiment 2 vs. experiment 1 was used to examine the observation

Nigerian women reap benefits from indigenous vegetables

International Development Research Centre (IDRC) Digital Library (Canada)

Working in four administrative states in south- western Nigeria, the Sustainable Production and Utilization of Underutilized Nigerian. Vegetables to Enhance Rural .... children's school fees and health care needs of the family. This will continue to sustain their use of improved production and cultivation once the project has ...

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.

Spatio-temporal variations of vegetation indicators in Eastern Siberia under global warming

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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.

Bioaccessibility and risk assessment of essential and non-essential elements in vegetables commonly consumed in Swaziland.

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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.

Enhancing light out-coupling of organic light-emitting devices using indium tin oxide-free low-index transparent electrodes

Energy Technology Data Exchange (ETDEWEB)

Huang, Yi-Hsiang; Lu, Chun-Yang; Tsai, Shang-Ta; Tsai, Yu-Tang; Chen, Chien-Yu; Tsai, Wei-Lung; Lin, Chun-Yu; Chang, Hong-Wei; Lee, Wei-Kai; Jiao, Min; Wu, Chung-Chih, E-mail: wucc@ntu.edu.tw [Department of Electrical Engineering, Graduate Institute of Photonics and Optoelectronics, Graduate Institute of Electronics Engineering, and Innovative Photonics Advanced Research Center (i-PARC), National Taiwan University, Taipei 10617, Taiwan (China)

2014-05-05

With its increasing and sufficient conductivity, the conducting polymer poly(3,4-ethylenedioxythiophene):poly(styrenesulfonate) (PEDOT:PSS) has been capable of replacing the widely used but less cost-effective indium tin oxides (ITOs) as alternative transparent electrodes for organic light-emitting devices (OLEDs). Intriguingly, PEDOT:PSS also possesses an optical refractive index significantly lower than those of ITO and typical organic layers in OLEDs and well matching those of typical OLED substrates. Optical simulation reveals that by replacing ITO with such a low-index transparent electrode, the guided modes trapped within the organic/ITO layers in conventional OLEDs can be substantially suppressed, leading to more light coupled into the substrate than the conventional ITO device. By applying light out-coupling structures onto outer surfaces of substrates to effectively extract radiation into substrates, OLEDs using such low-index transparent electrodes achieve enhanced optical out-coupling and external quantum efficiencies in comparison with conventional OLEDs using ITO.

[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

Observed Effects of Vegetation Growth on Temperature in the Early Summer over the Northeast China Plain

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Xiaxiang Li

2017-05-01

Full Text Available The effect of vegetation on temperature is an emerging topic in the climate science community. Existing studies have mostly examined the effects of vegetation on daytime temperature (Tmax, whereas this study investigates the effects on nighttime temperature (Tmin. Ground measurements from 53 sites across northeastern China (NEC from 1982 to 2006 show that early summer (June Tmax and Tmin increased at mean rates of approximately 0.61 °C/10 year and 0.67 °C/10 year, respectively. Over the same period, the satellite-based Normalized Difference Vegetation Index (NDVI decreased by approximately 0.10 (accounting for 18% of the climatological NDVI for 1982–1991. It is highlighted that a larger increase in Tmax (Tmin co-occurred spatially with a larger (smaller decrease in NDVI. Deriving from such spatial co-occurrences, we found that the spatial variability of changes in Tmax (i.e., ΔTmax is negatively correlated with the spatial variability of changes in NDVI (i.e., ΔNDVI, while the spatial variability of changes in Tmin (i.e., ΔTmin is positively correlated (r2 = 0.10; p < 0.05 with that of ΔNDVI. Similarly, we detected significant positive correlations between the spatial variability of ΔNDVI and the change in surface latent heat flux (r2 = 0.16; p < 0.01 and in surface air specific humidity (r2 = 0.28; p < 0.001. These findings on the spatial co-occurrences suggest that the vegetation growth intensifies the atmospheric water vapor through evapotranspiration, which enhances the atmospheric downward longwave radiation and strengthens the greenhouse warming effects at night. Thereby, the positive correlation between ΔNDVI and ΔTmin is better understood. These results indicate that vegetation growth may not only exert effects on daytime temperature but also exert warming effects on nighttime temperature by increasing atmospheric water vapor and thus intensifying the local greenhouse effect. This study presents new observation evidence of the

Wetland habitat disturbance best predicts metrics of an amphibian index of biotic integrity

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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.

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

Effects of Warming Hiatuses on Vegetation Growth in the Northern Hemisphere

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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

Woody plants diversity and type of vegetation in non cultivated plain of Moutourwa, Far-North, Cameroon

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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

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.

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.

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.

WAVEFORM ANALYSIS FOR THE EXTRACTION OF POST-FIRE VEGETATION CHARACTERISTICS

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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.

Detecting Historical Vegetation Changes in the Dunhuang Oasis Protected Area Using Landsat Images

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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.

Vertical Finger Displacement Is Reduced in Index Finger Tapping During Repeated Bout Rate Enhancement.

Science.gov (United States)

Mora-Jensen, Mark Holten; Madeleine, Pascal; Hansen, Ernst Albin

2017-10-01

The present study analyzed (a) whether a recently reported phenomenon of repeated bout rate enhancement in finger tapping (i.e., a cumulating increase in freely chosen finger tapping frequency following submaximal muscle activation in the form of externally unloaded voluntary tapping) could be replicated and (b) the hypotheses that the faster tapping was accompanied by changed vertical displacement of the fingertip and changed peak force during tapping. Right-handed, healthy, and recreationally active individuals (n = 24) performed two 3-min index finger tapping bouts at freely chosen tapping frequency, separated by 10-min rest. The recently reported phenomenon of repeated bout rate enhancement was replicated. The faster tapping (8.8 ± 18.7 taps/min, corresponding to 6.0 ± 11.0%, p = .033) was accompanied by reduced vertical displacement (1.6 ± 2.9 mm, corresponding to 6.3 ± 14.9%, p = .012) of the fingertip. Concurrently, peak force was unchanged. The present study points at separate control mechanisms governing kinematics and kinetics during finger tapping.

Projected effects of vegetation feedbacks on drought characteristics with SPEI over West Africa using the RegCM-CLM-CN-DV

Science.gov (United States)

Jaehyeong, L.; Kim, Y.; Erfanian, A.; Wang, G.; Um, M. J.

2017-12-01

This study utilizes the Standardized Precipitation-Evapotranspiration Index (SPEI) to investigate the projected effect of vegetation feedbacks on drought in West Africa using the Regional Climate Model coupled to the NCAR Community Land Model with both the Carbon and Nitrogen module (CN) and Dynamic Vegetation module (DV) activated (RegCM-CLM-CN-DV). The role of vegetation feedbacks is examined based on simulations with and without dynamic vegetation. The four different future climate scenarios from CCSM, GFDL, MIROC and MPI are used as the boundary conditions of RegCM for two historical and future periods, i.e., for 1981 to 2000 and for 2081 to 2100, respectively. Using SPEI, the duration, frequency, severity and spatial extents are quantified over West Africa and analyzed for two regions of the Sahel and the Gulf of Guinea. In this study, we find that the estimated annual SPEIs clearly indicate that the projected future droughts over the Sahel are enhanced and prolonged when DV is activated. The opposite is shown over the Gulf of Guinea in general. AcknowledgementsThis work was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT & Future Planning (2015R1C1A2A01054800), by the Korea Meteorological Administration R&D Program under Grant KMIPA 2015-6180 and by the Yonsei University Future-leading Research Initiative of 2015(2016-22-0061).

Assessment on the Contamination Status of Heavy Metals in Some Vegetables Growing Areas of Guangdong Province, China