WorldWideScience

Sample records for satellite vegetation index

  1. 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

  2. Evapotranspiration estimation using a normalized difference vegetation index transformation of satellite data

    Science.gov (United States)

    Seevers, P.M.; Ottmann, R. W.

    1994-01-01

    Evapotranspiration of irrigated crops on two irrigation service areas along the lower Colorado River was estimated using a normalized difference vegetation index of satellite data. A procedure was developed which equated the index to crop coefficients. Evapotranspiration estimates for fields for three dates of thematic mapper data were highly correlated with ground estimates. Service area estimates using thematic mapper and Advanced Very High Resolution Radiometer data agreed well with estimates based on US Geological Survey gauging station data.

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

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    Ainong Li

    2010-06-01

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

  4. Trends in a satellite-derived vegetation index and environmental variables in a restored brackish lagoon

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    Ji Yoon Kim

    2015-07-01

    Full Text Available We evaluated relative influence of climatic variables on the plant productivity after lagoon restoration. Chilika Lagoon, the largest brackish lake ecosystem in East Asia, experienced severe problems such as excessive dominance of freshwater exotic plants and rapid debasement of biodiversity associated with decreased hydrologic connectivity between the lagoon and the ocean. To halt the degradation of the lagoon ecosystem, the Chilika Development Authority implemented a restoration project, creating a new channel to penetrate the barrier beach of the lagoon. Using a satellite-derived normalized difference vegetation index (NDVI dataset, we compared the trend of vegetation changes after the lagoon restoration, from April 1998 to May 2014. The time series of NDVI data were decomposed into trend, seasonal, and random components using a local regression method. The results were visualized to understand the traits of spatial distribution in the lagoon. The NDVI trend, indicative of primary productivity, decreased rapidly during the restoration period, and gradually increased (slope coefficient: 2.1×10−4, p<0.05 after two years of restoration. Level of seawater exchange had more influences on plant productivity than local precipitation in the restored lagoon. Higher El Niño/Southern Oscillation increased sea level pressure, and caused intrusion of seawater into the lagoon, and the subsequently elevated salinity decreased the annual mean NDVI. Our findings suggest that lagoon restoration plans for enhancing interconnectivity with the ocean should consider oceanographic effects due to meteorological forcing, and long-term NDVI results can be used as a valuable index for adaptive management of the restoration site.

  5. A Satellite-Based Estimation of Evapotranspiration Using Vegetation Index-Temperature Trapezoid Concept: A Case Study in Southern Florida, U.S.A.

    Science.gov (United States)

    Yagci, A. L.; Santanello, J. A., Jr.; Jones, J. W.

    2015-12-01

    One of the key surface variables for hydrological applications, monitoring of natural and anthropogenic water consumption, closing energy balance and water budgets and drought identification is evapotranspiration (ET). There is currently a strong need for high temporal and spatial resolution ET products for climate and hydrological modelers. A satellite-based retrieval method based on vegetation index-temperature trapezoid (VITT) concept has been developed. This model has the ability to generate accurate ET estimates at high temporal and spatial resolutions by taking advantage of key remotely sensed parameters such as vegetation indices (VIs) and land surface temperature (LST) acquired by satellites as well as routinely-measured meteorological variables such as air temperature (Ta) and net radiation. For local-scale applications, the model has been successfully implemented in Python programming language and tested using Landsat satellite products at an eddy covariance flux tower in Florida. It is fully functional and automated such that there is no need of user intervention to run the model. The model development for continental-scale applications using VI and LST products from NASA satellites such as the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Visible Infrared Imaging Radiometer Suite (VIIRS) is currently in progress. The results for local-scale application and early results for continental-scale (US) will be presented and discussed.

  6. LEAF AREA INDEX CHANGE DETECTION OF UNDERSTORY VEGETATION IN THE ALBEMARLE-PAMLICO BASIN USING IKOMOS AND LANDSAT ETM+ SATELLITE DATA

    Science.gov (United States)

    The advent of remotely sensed data from satellite platforms has enabled the research community to examine vegetative spatial distributions over regional and global scales. This assessment of ecosystem condition through the synoptic monitoring of terrestrial vegetation extent, bio...

  7. LEAF AREA INDEX (LAI) CHANGES DETECTION OF UNDERSTORY VEGETATION IN THE ALBEMARLE-PAMLICO BASIN IKONOS AND LANDSAT ETM+ SATELLITE DATA

    Science.gov (United States)

    The advent of remotely sensed data from satellite platforms has enabled the research community to examine vegetative spatial distributions over regional and global scales. This assessment of ecosystem condition through the synoptic monitoring of terrestrial vegetation extent, bio...

  8. Assessment of surface dryness due to deforestation using satellite-based temperature-vegetation dryness index (TVDI) in Rondônia, Amazon

    Science.gov (United States)

    Ryu, J. H.; Cho, J.

    2016-12-01

    The Rondônia is the most deforested region in the Amazon due to human activities such as forest lumbering for the several decades. The deforestation affects to water cycle because evapotranspiration was reduced, and then soil moisture and precipitation will be changed. In this study, we assess surface dryness using satellite-based data such as moderate resolution imaging spectroradiometer (MODIS) land surface temperature (LST), normalized difference vegetation index (NDVI), albedo, TRMM Multi-sensor Precipitation Analysis (TMPA) precipitation from 2002 to 2014, and Global Ozone Monitoring Experiment-2 (GOME-2) sun-induced fluorescence (SIF) from 2007 to 2014. Temperature-vegetation dryness index (TVDI) was calculated using LST and NDVI to evaluate surface dryness during dry season (June-July). TVDI relatively represents the surface dryness on specific area and period. Forest, deforesting and deforested regions were selected in the Rondônia to assess the relative changes on surface dryness occurred from human activity. The relative TVDI (rTVDI) at deforesting region increased because of deforestation, it means that surface in deforesting region became more dryness. We also found that to assess the impact of deforestation using satellite-based precipitation and vegetation conditions such as NDVI and sun-induced fluorescence (SIF) is possible. The relative NDVI (rNDVI) and SIF decreased when TVDI increased, and two variables (rTVDI-rNDVI, rTVDI-SIF) had linear correlation. Thesis results can be helpful to comprehend impact of deforestation in Amazon, and to validate simulations of deforestation from hydrological models.

  9. Exploration of Loggerhead Shrike Habitats in Grassland National Park of Canada Based on in Situ Measurements and Satellite-Derived Adjusted Transformed Soil-Adjusted Vegetation Index (ATSAVI

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    Li Shen

    2013-01-01

    Full Text Available The population of loggerhead shrike (Lanius ludovicianus excubutirudes in Grassland National Park of Canada (GNPC has undergone a severe decline due to habitat loss and limitation. Shrike habitat availability is highly impacted by the biophysical characteristics of grassland landscapes. This study was conducted in the west block of GNPC. The overall purpose was to extract important biophysical and topographical variables from both SPOT satellite imagery and in situ measurements. Statistical analysis including Analysis of Variance (ANOVA, measuring Coefficient Variation (CV, and regression analysis were applied to these variables obtained from both imagery and in situ measurement. Vegetation spatial variation and heterogeneity among active, inactive and control nesting sites at 20 m × 20 m, 60 m × 60 m and 100 m × 100 m scales were investigated. Results indicated that shrikes prefer to nest in open areas with scattered shrubs, particularly thick or thorny species of smaller size, to discourage mammalian predators. The most important topographical characteristic is that active sites are located far away from roads at higher elevation. Vegetation index was identified as a good indicator of vegetation characteristics for shrike habitats due to its significant relation to most relevant biophysical factors. Spatial variation analysis showed that at all spatial scales, active sites have the lowest vegetation abundance and the highest heterogeneity among the three types of nesting sites. For all shrike habitat types, vegetation abundance decreases with increasing spatial scales while habitat heterogeneity increases with increasing spatial scales. This research also indicated that suitable shrike habitat for GNPC can be mapped using a logistical model with ATSAVI and dead material in shrub canopy as the independent variables.

  10. The 2010 Russian Drought Impact on Satellite Measurements of Solar-Induced Chlorophyll Fluorescence: Insights from Modeling and Comparisons with the Normalized Differential Vegetation Index (NDVI)

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    Yoshida, Y.; Joiner, J.; Tucker, C.; Berry, J.; Lee, J. -E.; Walker, G.; Reichle, R.; Koster, R.; Lyapustin, A.; Wang, Y.

    2015-01-01

    We examine satellite-based measurements of chlorophyll solar-induced fluorescence (SIF) over the region impacted by the Russian drought and heat wave of 2010. Like the popular Normalized Difference Vegetation Index (NDVI) that has been used for decades to measure photosynthetic capacity, SIF measurements are sensitive to the fraction of absorbed photosynthetically-active radiation (fPAR). However, in addition, SIF is sensitive to the fluorescence yield that is related to the photosynthetic yield. Both SIF and NDVI from satellite data show drought-related declines early in the growing season in 2010 as compared to other years between 2007 and 2013 for areas dominated by crops and grasslands. This suggests an early manifestation of the dry conditions on fPAR. We also simulated SIF using a global land surface model driven by observation-based meteorological fields. The model provides a reasonable simulation of the drought and heat impacts on SIF in terms of the timing and spatial extents of anomalies, but there are some differences between modeled and observed SIF. The model may potentially be improved through data assimilation or parameter estimation using satellite observations of SIF (as well as NDVI). The model simulations also offer the opportunity to examine separately the different components of the SIF signal and relationships with Gross Primary Productivity (GPP).

  11. Timely monitoring of Asian Migratory locust habitats in the Amudarya delta, Uzbekistan using time series of satellite remote sensing vegetation index.

    Science.gov (United States)

    Löw, Fabian; Waldner, François; Latchininsky, Alexandre; Biradar, Chandrashekhar; Bolkart, Maximilian; Colditz, René R

    2016-12-01

    The Asian Migratory locust (Locusta migratoria migratoria L.) is a pest that continuously threatens crops in the Amudarya River delta near the Aral Sea in Uzbekistan, Central Asia. Its development coincides with the growing period of its main food plant, a tall reed grass (Phragmites australis), which represents the predominant vegetation in the delta and which cover vast areas of the former Aral Sea, which is desiccating since the 1960s. Current locust survey methods and control practices would tremendously benefit from accurate and timely spatially explicit information on the potential locust habitat distribution. To that aim, satellite observation from the MODIS Terra/Aqua satellites and in-situ observations were combined to monitor potential locust habitats according to their corresponding risk of infestations along the growing season. A Random Forest (RF) algorithm was applied for classifying time series of MODIS enhanced vegetation index (EVI) from 2003 to 2014 at an 8-day interval. Based on an independent ground truth data set, classification accuracies of reeds posing a medium or high risk of locust infestation exceeded 89% on average. For the 12-year period covered in this study, an average of 7504 km(2) (28% of the observed area) was flagged as potential locust habitat and 5% represents a permanent high risk of locust infestation. Results are instrumental for predicting potential locust outbreaks and developing well-targeted management plans. The method offers positive perspectives for locust management and treatment of infested sites because it is able to deliver risk maps in near real time, with an accuracy of 80% in April-May which coincides with both locust hatching and the first control surveys. Such maps could help in rapid decision-making regarding control interventions against the initial locust congregations, and thus the efficiency of survey teams and the chemical treatments could be increased, thus potentially reducing environmental pollution

  12. 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.

  13. Parameterization of Vegetation Aerodynamic Roughness of Natural Regions Satellite Imagery

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    Jasinski, Michael F.; Crago, Richard; Stewart, Pamela

    1998-01-01

    Parameterizations of the frontal area index and canopy area index of natural or randomly distributed plants are developed, and applied to the estimation of local aerodynamic roughness using satellite imagery. The formulas are expressed in terms of the subpixel fractional vegetation cover and one non-dimensional geometric parameter that characterizes the plant's shape. Geometrically similar plants and Poisson distributed plant centers are assumed. An appropriate averaging technique to extend satellite pixel-scale estimates to larger scales is provided. The parameterization is applied to the estimation of aerodynamic roughness using satellite imagery for a 2.3 sq km coniferous portion of the Landes Forest near Lubbon, France, during the 1986 HAPEX-Mobilhy Experiment. The canopy area index is estimated first for each pixel in the scene based on previous estimates of fractional cover obtained using Landsat Thematic Mapper imagery. Next, the results are incorporated into Raupach's (1992, 1994) analytical formulas for momentum roughness and zero-plane displacement height. The estimates compare reasonably well to reference values determined from measurements taken during the experiment and to published literature values. The approach offers the potential for estimating regionally variable, vegetation aerodynamic roughness lengths over natural regions using satellite imagery when there exists only limited knowledge of the vegetated surface.

  14. Vegetation Drought Response Index: 2010-Present

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — VegDRI, short for Vegetation Drought Response Index, is a drought-monitoring tool developed by scientists at EROS in collaboration with the National Drought...

  15. Investigation of Vegetation Dynamics using Long-Term Normalized Difference Vegetation Index Time-Series

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    Tamara Bellone

    2009-01-01

    Full Text Available Problem statement: The Normalized Difference Vegetation Index (NDVI is the most extensively used satellite-derived index of vegetation health and density. Since climate is one of the most important factors affecting vegetation condition, satellite-derived vegetation indexes have been often used to evaluate climatic and environmental changes at regional and global scale. The proposed study attempted to investigate the temporal vegetation dynamics in the whole Africa using historical NDVI time-series. Approach: For this aim, 15 day maximum value NDVI composites at 8 km spatial resolution produced from the NASA Global Inventory Mapping and Monitoring System (GIMMS had been used. They were derived from data collected daily by NOAA AVHRR satellites. The AVHRR NDVI GIMMS dataset was freely available and gives global coverage over an extensive time period. First of all, the selected NDVI base data had been geometrically pre-processed and organized into a historical database implemented in order to grant their spatial integration. Starting from this archive, monthly and yearly NDVI historical time-series, extended from 1982-2006, had been then developed and analysed on a pixel basis. Several routines hade been developed in IDL (Interactive Data Language programming tool with the purpose of applying suitable statistical analysis techniques to the historical information in the database in order to identify the long-term trend components of generated NDVI time-series and extract vegetation dynamics. Specific tests had been then considered in order to define the validity of results. Results: The existence of clear regional trends of NDVI, both decreasing and increasing had been showed, which helped to highlight areas subject, respectively to reduction or increase in vegetation greenness. Conclusion: As the relationship between the NDVI and vegetation productivity was well established, these estimated long-term trend components may be also, with much more

  16. Using the satellite-derived normalized difference vegetation index (NDVI) to explain ranging patterns in a lek-breeding antelope: the importance of scale.

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    Bro-Jørgensen, Jakob; Brown, Molly E; Pettorelli, Nathalie

    2008-11-01

    Lek-breeding species are characterized by a negative association between territorial resource availability and male mating success; however, the impact of resources on the overall distribution patterns of the two sexes in lek systems is not clear. The normalized difference vegetation index (NDVI) has recently emerged as a powerful proxy measure for primary productivity, allowing the links between the distributions of animals and resources to be explored. Using NDVI at four spatial resolutions, we here investigate how the distribution of the two sexes in a lek-breeding population of topi antelopes relates to resource abundance before and during the rut. We found that in the dry season preceding the rut, topi density correlated positively with NDVI at the large, but not the fine, scale. This suggests that before the rut, when resources were relatively scant, topi preferred pastures where green grass was widely abundant. The pattern was less pronounced in males, suggesting that the need for territorial attendance prevents males from tracking resources as freely as females do. During the rut, which occurs in the wet season, both male and female densities correlated negatively with NDVI at the fine scale. At this time, resources were generally plentiful and the results suggest that, rather than by resource maximization, distribution during the rut was determined by benefits of aggregating on relatively resource-poor leks for mating, and possibly antipredator, purposes. At the large scale, no correlation between density and NDVI was found during the rut in either sex, which can be explained by leks covering areas too small to be reflected at this resolution. The study illustrates that when investigating spatial organization, it is important: (1) to choose the appropriate analytic scale, and (2) to consider behavioural as well as strictly ecological factors.

  17. Portable Instrument for Normalized Difference Vegetation Index

    Institute of Scientific and Technical Information of China (English)

    ZHOU Han-chang; ZHAO Chun-jiang; XUE Xu-zhang; HAO Xiao-jian

    2004-01-01

    By using four specially designed narrow bandpass filters and photodetectors in the instrument, the incident and reflected radiances of sun light on the vegetation are optically sensed, at the red and near infrared bands, then the normalized difference vegetation index(NDVI) is processed by a microprocessor. Compared with conventional spectrometer measuring method of NDVI, the instrument is easy to be used, compact, light and low-cost.

  18. Global relation between microwave satellite vegetation products and vegetation productivity

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    Teubner, Irene E.; Forkel, Matthias; Jung, Martin; Miralles, Diego G.; Dorigo, Wouter A.

    2017-04-01

    The occurrence of unfavourable environmental conditions like droughts commonly reduces the photosynthetic activity of ecosystems and, hence, their potential to take up carbon from the atmosphere. Ecosystem photosynthetic activity is commonly determined using remote sensing observations in the optical domain, which however have limitations particularly in regions of frequent cloud cover, e.g. the tropics. In this study, we explore the potential of vegetation optical depth (VOD) from microwave satellite observations as an alternative source for assessing vegetation productivity. VOD serves as an estimate for vegetation density and water content, which has an impact on plant physiological processes and hence should potentially provide a link to gross primary production (GPP). However, to date, it is unclear how microwave-retrieved VOD data and GPP data are related. We compare seasonal dynamics and anomalies of VOD retrievals from different satellite sensors and microwave frequencies with site level and global GPP estimates. We use VOD observations from active (ASCAT) and passive microwave sensors (AMSR-E, SMOS). We include eddy covariance measurements from the FLUXNET2015 dataset to assess the VOD products at site level. For a global scale analysis, we use the solar-induced chlorophyll fluorescence (SIF) observations from GOME-2 as a proxy for GPP and the FLUXCOM GPP product, which presents an upscaling of site measurements based on remote sensing data. Our results demonstrate that in general a good agreement between VOD and GPP or SIF exists. However, the strength of these relations depends on the microwave frequency, land cover type, and the time within the growing season. Correlations between anomalies of VOD and GPP or SIF support the assumption that microwave-derived VOD can be used to monitor vegetation productivity dynamics. The study is performed as part of the EOWAVE project funded by the Vienna University of Technology (http://eowave.geo.tuwien.ac.at/) and

  19. CHARACTERISING VEGETATED SURFACES USING MODIS MULTIANGULAR SATELLITE DATA

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    G. McCamley

    2012-07-01

    Full Text Available Bidirectional Reflectance Distribution Functions (BRDF seek to represent variations in surface reflectance resulting from changes in a satellite's view and solar illumination angles. BRDF representations have been widely used to assist in the characterisation of vegetation. However BRDF effects are often noisy, difficult to interpret and are the spatial integral of all the individual surface features present in a pixel. This paper describes the results of an approach to understanding how BRDF effects can be used to characterise vegetation. The implementation of the Ross Thick Li Sparse BRDF model using MODIS is a stable, mature data product with a 10 year history and is a ready data source. Using this dataset, a geometric optical model is proposed that seeks to interpret the BRDF effects in terms of Normalised Difference Vegetation Index (NDVI and a height-to-width ratio of the vegetation components. The height-to-width ratio derived from this model seeks to represent the dependence of NDVI to changes in view zenith angle as a single numeric value. The model proposed within this paper has been applied to MODIS pixels in central Australia for areas in excess of 18,000 km2. The study area is predominantly arid and sparsely vegetated which provides a level of temporal and spatial homogeneity. The selected study area also minimises the effects associated with mutual obscuration of vegetation which is not considered by the model. The results are represented as a map and compared to NDVI derived from MODIS and NDVI derived from Landsat mosaics developed for Australia's National Carbon Accounting System (NCAS. The model reveals additional information not obvious in reflectance data. For example, the height-to-width ratio is able to reveal vegetation features in arid areas that do not have an accompanying significant increase in NDVI derived from MODIS, i.e. the height-to-width ratio reveals vegetation which is otherwise only apparent in NDVI derived

  20. Bi-directional normalized difference vegetation index: concept and application

    Institute of Scientific and Technical Information of China (English)

    2002-01-01

    The data products of land surface bi-directional reflectance distribution function (BRDF) from the space-borne Polarization and Directionality of the Earth Reflectance (POLDER) of France and the Moderate Resolution Imaging Spectroradiometer (MODIS)of USA are available recently, but the atmospheric correction for meeting the requirement of quantitative remote sensing is still a very dfficult problem. This paper presents a concept: bi-directional normalized difference vegetation index (Bi-NDVI), in order to consider simul taneously the effects of both land surface BRDF and atmospheric path scattering. An atmospheric quality index is thus defined for satellite multi-angular observations. The quality of MODIS/BRDF data products can be improved notably through iterative inversion weighed by this index.

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

    Science.gov (United States)

    Shariatinajafabadi, Mitra; Wang, Tiejun; Skidmore, Andrew K; Toxopeus, Albertus G; Kölzsch, Andrea; Nolet, Bart A; Exo, Klaus-Michael; Griffin, Larry; Stahl, Julia; Cabot, David

    2014-01-01

    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.

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

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    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.

  3. The role of spatial and spectral resolution on the effectiveness of satellite-based vegetation indices

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

    2016-10-01

    Remote Sensing applications are designed to provide farmers with timely crop monitoring and production information. Such information can be used to identify crop needs or health problems and provide solutions for a better crop management. Vegetation indices (VIs) derived from satellite data have been widely used to assess variations in the physiological state and biophysical properties of vegetation. In the present study, the experimental area is located near the village Eleftherion of Larissa Prefecture in the Thessaly Plain, and consisted of two adjacent agricultural fields of cotton and corn. Imagery from WorldView-2 (WV2) satellite platform was obtained from European Space Imaging and Landsat-8 (L8) free of charge data were downloaded from the United States Geological Survey (USGS) archive. The images were selected for a four month span to evaluate continuity with respect to vegetation growth variation. VIs for each satellite platform data such as the Normalized Difference Vegetation Index (NDVI), the Soil-Adjusted Vegetation Index (SAVI) and the Fraction Photosynthetically Radiation (FPAR) were calculated. The comparison of these VIs produced from the two satellite systems with different spatial and spectral resolution was made for each growth stage of the crops and their results were analyzed in order to examine their correlation. Utilizing the WV2 new spectral data, several innovative chlorophyll and vegetation indices were created and evaluated so as to reveal their effectiveness in the detection of problematic plant growth areas. The Green Chlorophyll index appeared to be the most efficient index for the delineation of these areas.

  4. A PROPOSED NEW VEGETATION INDEX, THE TOTAL RATIO VEGETATION INDEX (TRVI, FOR ARID AND SEMI-ARID REGIONS

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    H. Fadaei

    2012-07-01

    Full Text Available Vegetation indices that provide important key to predict amount vegetation in forest such as percentage vegetation cover, aboveground biomass, and leaf-area index. Arid and semi-arid areas are not exempt of this rule. Arid and semi-arid areas of northeast Iran cover about 3.4 million ha and are populated by two main tree species, the broadleaf Pistacia vera (pistachio and the conifer Juniperus excelsa ssp. polycarpos (Persian juniper. Natural stands of pistachio in Iran are not only environmentally important but also genetically essential as seed sources for pistachio production in orchards. We investigated the relationships between tree density and vegetation indices in the arid and semi-arid regions in the northeast of Iran by analysing Advanced Land Observing Satellite (ALOS data PRISM is a panchromatic radiometer with a 2.5 m spatial resolution at nadir, and has one band with a wavelength of 0.52–0.77 μm (JAXA EORC. AVNIR-2 is a visible and near infrared radiometer for observing land and coastal zones with a 10 m spatial resolution at nadir, and has four multispectral bands: blue (0.42–0.50 μm, green (0.52–0.60 μm, red (0.61–0.69 μm, and near infrared (0.76–0.89 μm (JAXA EORC. In this study, we estimated various vegetation indices using maximum filtering algorithm (5×5 and examined. This study carried out of juniper forests and natural pistachio stand using Advanced Land Observing Satellite (ALOS and field inventories. Have been compared linear regression model of vegetation indices and proposed new vegetation index for arid and semi-arid regions. Also, we estimated the densities of juniper forests and natural pistachio stands using remote sensing to help in the sustainable management and production of pistachio in Iran. We present a new vegetation index for arid and semi-arid regions with sparse forest cover, the Total Ratio Vegetation Index (TRVI, and we investigate the relationship of the new index to tree density by

  5. Use of spectral channels and vegetation indices from satellite VEGETATION time series for the Post-Fire vegetation recovery estimation

    Science.gov (United States)

    Coluzzi, Rosa; Lasaponara, Rosa; Montesano, Tiziana; Lanorte, Antonio; de Santis, Fortunato

    2010-05-01

    Satellite data can help monitoring the dynamics of vegetation in burned and unburned areas. Several methods can be used to perform such kind of analysis. This paper is focused on the use of different satellite-based parameters for fire recovery monitoring. In particular, time series of single spectral channels and vegetation indices from SPOT-VEGETATION have investigated. The test areas is the Mediterranean ecosystems of Southern Italy. For this study we considered: 1) the most widely used index to follow the process of recovery after fire: normalized difference vegetation index (NDVI) obtained from the visible (Red) and near infrared (NIR) by using the following formula NDVI = (NIR_Red)/(NIR + Red), 2) moisture index MSI obtained from the near infrared and Mir for characterization of leaf and canopy water content. 3) NDWI obtained from the near infrared and Mir as in the case of MSI, but with the normalization (as the NDVI) to reduce the atmospheric effects. All analysis for this work was performed on ten-daily normalized difference vegetation index (NDVI) image composites (S10) from the SPOT- VEGETATION (VGT) sensor. The final data set consisted of 279 ten-daily, 1 km resolution NDVI S1O composites for the period 1 April 1998 to 31 December 2005 with additional surface reflectance values in the blue (B; 0.43-0.47,um), red (R; 0.61-0.68,um), near-infrared (NIR; 0.78-0.89,um) and shortwave-infrared (SWIR; 1.58-1.75,um) spectral bands, and information on the viewing geometry and pixel status. Preprocessing of the data was performed by the Vlaamse Instelling voor Technologisch Onderzoek (VITO) in the framework of the Global Vegetation Monitoring (GLOVEG) preprocessing chain. It consisted of the Simplified Method for Atmospheric Correction (SMAC) and compositing at ten-day intervals based on the Maximum Value Compositing (MVC) criterion. All the satellite time series were analysed using the Detrended Fluctuation Analysis (DFA) to estimate post fire vegetation recovery

  6. Structural High-resolution Satellite Image Indexing

    OpenAIRE

    Xia, Gui-Song; YANG, WEN; Delon, Julie; Gousseau, Yann; Sun, Hong; Maître, Henri

    2010-01-01

    International audience; Satellite images with high spatial resolution raise many challenging issues in image understanding and pattern recognition. First, they allow measurement of small objects maybe up to 0.5 m, and both texture and geometrical structures emerge simultaneously. Second, objects in the same type of scenes might appear at different scales and orientations. Consequently, image indexing methods should combine the structure and texture information of images and comply with some i...

  7. Satellite-based Studies on Large-Scale Vegetation Changes in China

    Institute of Scientific and Technical Information of China (English)

    Xia Zhao; Daojing Zhou; Jingyun Fang

    2012-01-01

    Remotely-sensed vegetation indices,which indicate the density and photosynthetic capacity of vegetation,have been widely used to monitor vegetation dynamics over broad areas.In this paper,we reviewed satellite-based studies on vegetation cover changes,biomass and productivity variations,phenological dynamics,desertification,and grassland degradation in China that occurred over the past 2-3 decades.Our review shows that the satellite-derived index (Normalized Difference Vegetation Index,NDVI) during growing season and the vegetation net primary productivity in major terrestrial ecosystems (for example forests,grasslands,shrubs,and croplands) have significantly increased,while the number of fresh lakes and vegetation coverage in urban regions have experienced a substantial decline.The start of the growing season continually advanced in China's temperate regions until the 1990s,with a large spatial heterogeneity.We also found that the coverage of sparsely-vegetated areas declined,and the NDVI per unit in vegetated areas increased in arid and semi-arid regions because of increased vegetation activity in grassland and oasis areas.However,these results depend strongly not only on the periods chosen for investigation,but also on factors such as data sources,changes in detection methods,and geospatial heterogeneity.Therefore,we should be cautious when applying remote sensing techniques to monitor vegetation structures,functions,and changes.

  8. Test of multi-spectral vegetation index for floating and canopy-forming submerged vegetation.

    Science.gov (United States)

    Cho, Hyun Jung; Kirui, Philemon; Natarajan, Harene

    2008-12-01

    Remote sensing of terrestrial vegetation has been successful thanks to the unique spectral characteristics of green vegetation, low reflectance in red and high reflectance in Near-InfraRed (NIR). These spectral characteristics were used to develop vegetation indices, including Normalized Difference Vegetation Index (NDVI). However, the NIR absorption by water and light scattering from suspended particles reduces the practical application of such indices in aquatic vegetation studies, especially for the Submerged Aquatic Vegetation (SAV) that grows below water surface. We experimentally tested if NDVI can be used to depict canopies of aquatic plants in shallow waters. A 100-gallonoutdoor tank was lined with black pond liners, a black panel or SAV shoots were mounted on the bottom, and filled with water up to 0.5 m. We used a GER 1500 spectroradiometer to collect spectral data over floating waterhyacinth (Eichhornia crassipes) and also over the tanks that contain SAV and black panel at varying water depths. The measured upwelling radiance was converted to % reflectance; and we integrated the hyperspectral reflectance to match the Red and NIR bands of three satellite sensors: Landsat 7 ETM, SPOT 5 HRG, and ASTER. NDVI values ranged 0.6-0.65 when the SAV canopy was at the water level, then they decreased linearly (slope of 0.013 NDVI/meter) with water depth increases in clear water. When corrected for water attenuation using the data obtained from the black panel, the NDVI values significantly increased at all depths that we tested (0.1 - 0.5 m). Our results suggest the conventional NDVI: (1) can be used to depict SAV canopies at water surface; (2) is not a good indicator for SAV that is adapted to live underwater or other aquatic plants that are submerged during flooding even at shallow waters (0.3 m); and (3) the index values can significantly improve if information on spectral reflectance attenuation caused by water volume increases is collected simultaneously

  9. Vegetation/Soil Synthesis Water Index Using MODIS Data

    Institute of Scientific and Technical Information of China (English)

    2005-01-01

    In consideration of the spectral character of MODIS (Moderate Resolution Imaging Spectroradiometer) data and the reflective spectrum of vegetation and soil, NDVI (Normalized Difference Vegetation Index) and NDWI (Normalized Difference Water Index) are deduced using one visible band (0.66μm) and two near-infrared bands (0.86μm, 1.24 μm). Vegetation canopy temperature is derived using two thermal infrared bands (8.6 μm and 11μm). Then the vegetation/soil synthesis water index (VSWI) is acquired through analyzing the coupling character of three indexes which can reflect the water condition of vegetation. Finally, the synthesis index is verified by equivalent water content of a single leaf. The matching results show that the synthesis index is directly proportional to the modeled data, which means that the vegetation water content can be reflected using the synthesis index effectively.

  10. Correlation between satellite vegetation indices and crop coefficients

    Science.gov (United States)

    Russo, A. L.; Simoniello, T.; Greco, M.; Squicciarrino, G.; Lanfredi, M.; Macchiato, M.

    2010-05-01

    the cultivation with more homogeneous canopy, e.g. kiwifruit, the best performing index was the WDVI showing a determination coefficient of 0.90; whereas its performances for vineyards and mixed olive cultivations were not satisfactory (R2 < 0.40). The EVI showed a behaviour similar to WDVI with slightly lower correlation values. The obtained results highlight the capability of medium resolution satellites for dynamically estimating crop coefficients and so for improving water balance assessment by taking into account the actual status of vegetation instead of expected and tabulated Kc-values. Ayenew, T., 2003. Evapotranspiration estimation using thematic mapper spectral satellite data in the Ethiopian rift and adjacent highlands, Journal of Hydrology, 279: 83-93 Bastiaanssen, W.G.M., Menenti, M., Feddes, R.A., Holstlag, A.A.M., 1998. A remote sensing surface energy balance algorithm for land (SEBAL). 1. Formulation, Journal of Hydrology, 212-213: 198-212. Calera A., Jochum A., Cuesta Garcia A., Montoro Rodriguez A., Lopez Fuster P., 2005. Irrigation management from space: Towards user-friendly products, Irrigation and Drainage Systems, 19: 337-353. Gonzalez-Dugo M.P. and Mateos L., 2008. Spectral vegetation indices for benchmarking water productivity of irrigated cotton and sugarbeet crops, Agricultural Water Management, 95: 48-58.

  11. An initial assessment of Suomi NPP VIIRS vegetation index EDR

    Science.gov (United States)

    Vargas, M.; Miura, T.; Shabanov, N.; Kato, A.

    2013-11-01

    The Suomi National Polar-orbiting Partnership (S-NPP) satellite with Visible/Infrared Imager/Radiometer Suite (VIIRS) onboard was launched in October 2011. VIIRS is the primary instrument for a suite of Environmental Data Records (EDR), including Vegetation Index (VI) EDR, for weather forecasting and climate research. The VIIRS VI EDR operational product consists of the Top of the Atmosphere (TOA) Normalized Difference Vegetation Index (NDVI), the Top of the Canopy (TOC) Enhanced Vegetation Index (EVI), and per-pixel product quality information. In this paper, we report results of our assessment of the early VIIRS VI EDR (beta quality) using Aqua MODIS and NOAA-18 AVHRR/3 as a reference for May 2012 to March 2013. We conducted two types of analyses focused on an assessment of physical (global scale) and radiometric (regional scale) performances of VIIRS VI EDR. Both TOA NDVI and TOC EVI of VIIRS showed spatial and temporal trends consistent with the MODIS counterparts, whereas VIIRS TOA NDVI was systematically higher than that of AVHRR. Performance of the early VIIRS VI EDR was limited by a lack of adequate per-pixel quality information, commission/omission errors of the cloud mask, and uncertainties associated with the surface reflectance retrievals. A number of enhancements to the VI EDR are planned, including: (1) implementation of a TOC EVI back-up algorithm, (2) addition of more detailed quality flags on aerosols, clouds, and snow cover, and (3) implementation of gridding and temporal compositing. A web-based, product quality monitoring tool has been developed and automated product validation protocols are being prototyped.

  12. Vegetation Cover Change in Yellowstone National Park Detected Using Landsat Satellite Image Analysis

    Science.gov (United States)

    Potter, Christopher S.

    2015-01-01

    Results from Landsat satellite image analysis since 1987 in all unburned areas (since the 1880s) of Yellowstone National Park (YNP) showed that consistent decreases in the normalized difference vegetation index (NDVI) have been strongly dependent on periodic variations in peak annual snow water equivalents (SWE).

  13. Development of JPSS VIIRS Global Gridded Vegetation Index products for NOAA NCEP Environmental Modeling Systems

    Science.gov (United States)

    Vargas, Marco; Miura, Tomoaki; Csiszar, Ivan; Zheng, Weizhong; Wu, Yihua; Ek, Michael

    2017-04-01

    The first Joint Polar Satellite System (JPSS) mission, the Suomi National Polar-orbiting Partnership (S-NPP) satellite, was successfully launched in October, 2011, and it will be followed by JPSS-1, slated for launch in 2017. JPSS provides operational continuity of satellite-based observations and products for NOAA's Polar Operational Environmental Satellites (POES). Vegetation products derived from satellite measurements are used for weather forecasting, land modeling, climate research, and monitoring the environment including drought, the health of ecosystems, crop monitoring and forest fires. The operationally produced S-NPP VIIRS Vegetation Index (VI) Environmental Data Record (EDR) includes two vegetation indices: the Top of the Atmosphere (TOA) Normalized Difference Vegetation Index (NDVI), and the Top of the Canopy (TOC) Enhanced Vegetation Index (EVI). For JPSS-1, the S-NPP Vegetation Index EDR algorithm has been updated to include the TOC NDV. The current JPSS operational VI products are generated in granule style at 375 meter resolution at nadir, but these products in granule format cannot be ingested into NOAA operational monitoring and decision making systems. For that reason, the NOAA JPSS Land Team is developing a new global gridded Vegetation Index (VI) product suite for operational use by the NOAA National Centers for Environmental Prediction (NCEP). The new global gridded VIs will be used in the Multi-Physics (MP) version of the Noah land surface model (Noah-MP) in NCEP NOAA Environmental Modeling System (NEMS) for plant growth and data assimilation and to describe vegetation coverage and density in order to model the correct surface energy partition. The new VI 4km resolution global gridded products (TOA NDVI, TOC NDVI and TOC EVI) are being designed to meet the needs of directly ingesting vegetation index variables without the need to develop local gridding and compositing procedures. These VI products will be consistent with the already

  14. A simple interpretation of the surface temperature/vegetation index space for assessment of surface moisture status

    DEFF Research Database (Denmark)

    Sandholt, Inge; Rasmussen, Kjeld; Andersen, Jens Asger

    2002-01-01

    A simplified land surface dryness index (Temperature-Vegetation Dryness Index, TVDI) based on an empirical parameterisation of the relationship between surface temperature (T-s) and vegetation index (NDVI) is suggested. The index is related to soil moisture and, in comparison to existing interpre......A simplified land surface dryness index (Temperature-Vegetation Dryness Index, TVDI) based on an empirical parameterisation of the relationship between surface temperature (T-s) and vegetation index (NDVI) is suggested. The index is related to soil moisture and, in comparison to existing...... interpretations of the T-s/NDVI space, the index is conceptually and computationally straightforward. It is based on satellite derived information only, and the potential for operational application of the index is therefore large. The spatial pattern and temporal evolution in TVDI has been analysed using 37 NOAA...

  15. 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.

  16. Assessing Leaf Area Index from High Resolution Satellite Datasets for Maize in Trans Nzoia County, Kenya

    Science.gov (United States)

    Bartolomew Thiongo, Kuria; Menz, Gunter; Thonfeld, Frank

    2016-08-01

    The Normalized Differenced Vegetation Index (NDVI) and the two band Enhanced vegetation Index (EVI2) derived from RapidEye and Landsat 8 satellite images were evaluated against the empirically derived terrestrial Leaf Area Index (LAI) acquired during the maize growth season April to November, 2015 and covering the phenological growth stages prescribed in the BBCH code. The results indicate a high correlation of the vegetation indices plotted over the entire maize season with R2 values of 88% and 83% for NDVI and EVI2 respectively. The maximum values were found to occur during the maize vegetative phase in the months of July and August. The correlation between the vegetation indices and the LAI had R2 values of 50% and 49% for NDVI and EVI2 respectively. Alternative methods of estimating and calculating the LAI values may improve the achieved results.

  17. Monitoring Rangeland Health With MODIS Vegetation Index Data

    Science.gov (United States)

    Brown, J. F.

    2004-12-01

    Rangelands cover approximately one third of the land area of the conterminous U.S. These lands supply much of the forage for the U.S. cattle industry. Large area monitoring of these vast expanses of range has proved challenging since most of these lands are in the western U.S., are relatively sparsely populated, and are not well covered by meteorological weather stations. Improvements in the spatial and temporal precision of rangeland health information would be useful both for the cattle industry and for scientific studies of soil erosion, water runoff, ecosystem health, and carbon cycling. Optical multispectral remote sensing data from satellites are an objective source of synoptic, timely information for monitoring rangeland health. The objective of this study is to develop and evaluate a method for measuring and monitoring rangeland health over large areas. In the past, data collected by the Advanced Very High Resolution Radiometer has proved useful for this purpose, however the basic 1 km spatial resolution is not ideal when scaling up from ground observations. This study assesses MODIS 250 meter resolution vegetation index data for this purpose. MODIS data not only have finer spatial resolution and improved geolocation, but they also exhibit enhanced vegetation sensitivity and minimized variations associated with external atmospheric and non-atmospheric effects. Ground data collected over 51 sites in western South Dakota over four years are used as training for regression tree models of range health. Range health maps for the growing season derived from the models are presented and evaluated.

  18. Retrieving leaf area index from SPOT4 satellite data

    Directory of Open Access Journals (Sweden)

    M. Aboelghar

    2010-12-01

    Full Text Available A research project was conducted as collaboration between the National Authority for Remote Sensing and Space Sciences (NARSS in Egypt and the Institute of Remote Sensing Applications (IRSA, Chinese Academy of Sciences. The objective of this study is to generate normalized difference vegetation index (NDVI–leaf area index (LAI statistical inversion models for three rice varieties planted in Egypt (Giza-178, Sakha-102, and Sakha-104 using the data of two rice growing seasons. Field observations were carried out to collect LAI field measurements during 2008 and 2009 rice seasons. The SPOT4 satellite data acquired in rice season of 2008 and 2009 conjunction with field observations dates were used to calculate the vegetation indices values. Statistical analyses were performed to confirm the assumptions of inversion modeling for plant variables and to get reliable models that fit the inversion relationship between LAI and NDVI. The inversion process resulted in three NDVI–LAI models adequate to predict LAI with 95% confidence for the three different rice varieties. The accuracy of the generated models ranged between 50% in the case of Sakha-104 and 82% in the case of Giza-178. LAI maps were produced from NDVI imageries based on the generated models.

  19. Test of Multi-spectral Vegetation Index for Floating and Canopy-forming Submerged Vegetation

    Directory of Open Access Journals (Sweden)

    Philemon Kirui

    2008-12-01

    Full Text Available Remote sensing of terrestrial vegetation has been successful thanks to the unique spectral characteristics of green vegetation, low reflectance in red and high reflectance in Near-InfraRed (NIR. These spectral characteristics were used to develop vegetation indices, including Normalized Difference Vegetation Index (NDVI. However, the NIR absorption by water and light scattering from suspended particles reduces the practical application of such indices in aquatic vegetation studies, especially for the Submerged Aquatic Vegetation (SAV that grows below water surface. We experimentally tested if NDVI can be used to depict canopies of aquatic plants in shallow waters. A 100-gallonoutdoor tank was lined with black pond liners, a black panel or SAV shoots were mounted on the bottom, and filled with water up to 0.5 m. We used a GER 1500 spectroradiometer to collect spectral data over floating waterhyacinth (Eichhornia crassipes and also over the tanks that contain SAV and black panel at varying water depths. The measured upwelling radiance was converted to % reflectance; and we integrated the hyperspectral reflectance to match the Red and NIR bands of three satellite sensors: Landsat 7 ETM, SPOT 5 HRG, and ASTER. NDVI values ranged 0.6-0.65 when the SAV canopy was at the water level, then they decreased linearly (slope of 0.013 NDVI/meter with water depth increases in clear water. When corrected for water attenuation using the data obtained from the black panel, the NDVI values significantly increased at all depths that we tested (0.1 – 0.5 m. Our results suggest the conventional NDVI: (1 can be used to depict SAV canopies at water surface; (2 is not a good indicator for SAV that is adapted to live underwater or other aquatic plants that are submerged during flooding even at shallow waters (0.3 m; and (3 the index values can significantly improve if information on spectral reflectance attenuation caused by water volume increases is

  20. Estimation of Vegetation Aerodynamic Roughness of Natural Regions Using Frontal Area Density Determined from Satellite Imagery

    Science.gov (United States)

    Jasinski, Michael F.; Crago, Richard

    1994-01-01

    Parameterizations of the frontal area index and canopy area index of natural or randomly distributed plants are developed, and applied to the estimation of local aerodynamic roughness using satellite imagery. The formulas are expressed in terms of the subpixel fractional vegetation cover and one non-dimensional geometric parameter that characterizes the plant's shape. Geometrically similar plants and Poisson distributed plant centers are assumed. An appropriate averaging technique to extend satellite pixel-scale estimates to larger scales is provided. ne parameterization is applied to the estimation of aerodynamic roughness using satellite imagery for a 2.3 sq km coniferous portion of the Landes Forest near Lubbon, France, during the 1986 HAPEX-Mobilhy Experiment. The canopy area index is estimated first for each pixel in the scene based on previous estimates of fractional cover obtained using Landsat Thematic Mapper imagery. Next, the results are incorporated into Raupach's (1992, 1994) analytical formulas for momentum roughness and zero-plane displacement height. The estimates compare reasonably well to reference values determined from measurements taken during the experiment and to published literature values. The approach offers the potential for estimating regionally variable, vegetation aerodynamic roughness lengths over natural regions using satellite imagery when there exists only limited knowledge of the vegetated surface.

  1. Satellite-scale Estimates of the "b Parameter" Relating Vegetation Water Content and SMOS Optical Thickness

    Science.gov (United States)

    Patton, J. C.; Hornbuckle, B. K.

    2013-12-01

    Microwave radiation emitted by Earth's land surface is primarily determined by soil moisture and vegetation. One of the effects of vegetation on surface microwave emissions is often termed the "vegetation optical thickness" or "vegetation opacity" and is often abbreviated as tau. Retrievals of soil moisture from microwave radiometer measurements requires knowledge of tau. The Soil Moisture and Ocean Salinity (SMOS) satellite measures microwave radiation at multiple incidence angles, enabling the simultaneous retrieval of soil moisture and tau. Other soil moisture satellites, such as the upcoming Soil Moisture Active Passive (SMAP) satellite, only measure at single incidence angles and may need auxiliary sources of tau data in order to retrieve soil moisture. One proposed method for estimating tau for these satellites is by relating reflectance data, e.g. the normalized difference vegetation index, to vegetation water content (VWC), then relating VWC to tau. VWC and tau can be related through the b parameter, i.e. tau = b x VWC. Values of b for different land cover types have been estimated from tower (~1 m) and airplane (~10-100 m) data, but have not been measured at the satellite scale (~10 km). Estimating b at the satellite scale from measurements at smaller scales is difficult because the effective value of b in a satellite pixel may not be well represented by linear weighted average based on the fraction of each land cover type in the pixel. However, by relating county crop yields, estimated by the USDA National Agricultural Statistics Service, to measurements of SMOS tau, and by using certain allometric relationships, such as the ratio of water to dry matter and the harvest index of crops, we can estimate b at the satellite scale. We have used this method to estimate b for each Iowa county for the years 2010-2012. Initial results suggest that b may change year to year; our current estimates for b in Iowa range from 0.065 in 2010 to 0.100 in 2012. These

  2. Evaluating drought in the United States using the emissivity difference vegetation index

    Science.gov (United States)

    Hirani, Hanisha K.

    As monitoring vegetation and crops becomes increasingly important due to climate change, there arises the need for a monitoring scheme that places more weight on water availability as an indication of vegetation health and vitality. The Emissivity Difference Vegetation Index (EDVI) is the first step towards that type of monitoring scheme. With the potential for diurnal studies, there are applications towards agriculture monitoring, wildfire monitoring, and much more. EDVI is a synergetic product retrieved from microwave, visible, and infrared satellite measurements, as well as reanalysis. Since microwave measurements are more sensitive to vegetation water content, EDVI has the potential to capture intrinsic changes in vegetation. A new drought index is developed from EDVI, the Emissivity Vegetation Condition Index (EVCI). The high temporal sampling of EVCI will make it one of the more dynamic attempts to measure and investigate drought impacts on vegetation and crops on short-term scales. This new drought index will be compared to presently operational drought indices including the Palmer drought indices, the Vegetation Condition Index (VCI), and the Vegetation Health Index (VHI) for the period between 2009-2011 in the United States. The focus will be on improving the methodology of the EDVI retrieval and then examining two periods of identified drought, one in the Southern Great Plains in 2011, and one short-term drought in the Great Lakes region in 2010. The results indicate an agreement between ECVI and precipitation, and the drought episodes in 2010 and 2011 are resolved by EVCI. With a dataset beyond the three years used for this study it would be possible to correct more accurately for climatology.

  3. Relative Spectral Mixture Analysis: a new multitemporal index of total vegetation cover

    Science.gov (United States)

    Okin, G. S.; Liu, C. S.

    2005-12-01

    High temporal resolution remote sensing provides an opportunity to monitor phenological variability and interannual changes in vegetation cover across diverse. A principal tool in multitemporal vegetation monitoring has been the Normalized Difference Vegetation Index. NDVI provides an index of the depth of the red edge and is usually interpreted as a measure of vegetation greenness and/or green vegetation cover. NDVI as a measure of phenology has several failings, particularly when applied over large areas: 1) NDVI is sensitive to the spectra of the soil background, particularly in partially or seasonally vegetated areas, 2) NDVI does not provide information about the non-photosynthetic portion of standing biomass, and 3) NDVI is very sensitive to the presence of small amounts of snow in a pixel. A new method for measuring vegetation phenology has been developed called Relative Spectral Mixture Analysis. RSMA uses a linear spectral mixture analysis to provide an index of the relative cover of four landscape components: green vegetation (GV), nonphotosynthetic vegetation (NPV), soil, and snow. RSMA uses generalized spectral for GV, NPV and snow, but does not require knowledge of the background soil spectra. This allows RSMA to be applied over very large areas (continental-scale) in which the soil background is highly diverse. RSMA has been implemented in the IDL language and used to analyze MODIS nadir-adjusted reflectance products from 2000 to the present. Our results show that RSMA GV index values are highly correlated with NDVI, except in regions with snow where RSMA outperforms NDVI. As a result RSMA GV indices and total vegetation indices (GV+NPV) can be used to extract information from spectral timeseries such as the onset of greenness, the termination of greenness, maximum vegetation cover, integrated vegetation cover (an index of NPP), length of the growing season, and duration of fodder availability. RSMA snow indices correlate well with other satellite

  4. Advanced Very High Resolution Radiometer Normalized Difference Vegetation Index Composites

    Science.gov (United States)

    ,

    2005-01-01

    The Advanced Very High Resolution Radiometer (AVHRR) is a broad-band scanner with four to six bands, depending on the model. The AVHRR senses in the visible, near-, middle-, and thermal- infrared portions of the electromagnetic spectrum. This sensor is carried on a series of National Oceanic and Atmospheric Administration (NOAA) Polar Orbiting Environmental Satellites (POES), beginning with the Television InfraRed Observation Satellite (TIROS-N) in 1978. Since 1989, the United States Geological Survey (USGS) Center for Earth Resources Observation and Science (EROS) has been mapping the vegetation condition of the United States and Alaska using satellite information from the AVHRR sensor. The vegetation condition composites, more commonly called greenness maps, are produced every week using the latest information on the growth and condition of the vegetation. One of the most important aspects of USGS greenness mapping is the historical archive of information dating back to 1989. This historical stretch of information has allowed the USGS to determine a 'normal' vegetation condition. As a result, it is possible to compare the current week's vegetation condition with normal vegetation conditions. An above normal condition could indicate wetter or warmer than normal conditions, while a below normal condition could indicate colder or dryer than normal conditions. The interpretation of departure from normal will depend on the season and geography of a region.

  5. Sensitivity of vegetation indices to different burn and vegetation ratios using LANDSAT-5 satellite data

    Science.gov (United States)

    Pleniou, M.; Koutsias, N.

    2013-08-01

    The application of vegetation indices is a very common approach in remote sensing of burned areas to either map the fire scar or estimate burn severity since they minimize the effect of exogenous factors and enhance the correlation with the internal parameters of vegetation. In a recent study we found that the original spectral channels, based on which these indices are estimated, are sensitive to external parameters of the vegetation as for example the spectral reflectance of the background soil. In such cases, the influence of the soil in the reflectance values is different in the various spectral regions depending on its type. These problems are further enhanced by the non-homogeneous pixels, as created from fractions of different types of land cover. Parnitha (Greece), where a wildfire occurred on July 2007, was established as test site. The purpose of this work is to explore the sensitivity of vegetation indices when used to estimate and map different fractions of fire-scorched (burned) and non fire-scorched (vegetated) areas. IKONOS, a very high resolution satellite imagery, was used to create a three-class thematic map to extract the percentages of vegetation, burned surfaces, and bare soil. Using an overlaid fishnet we extracted samples of completely "burned", completely "vegetated" pixels and proportions with different burn/vegetation ratios (45%-55% burned - 45%-55% vegetation, 20%-30% burned - 70%- 80% vegetation, 70%-80% burned - 20%-30% vegetation). Vegetation indices were calculated (NDVI, IPVI, SAVI) and their values were extracted to characterize the mentioned classes. The main findings of our recent research were that vegetation indices are less sensitive to external parameters of the vegetation by minimizing external effects. Thus, the semi-burned classes were spectrally more consistent to their different fractions of scorched and non-scorched vegetation, than the original spectral channels based on which these indices are estimated.

  6. Analysis of the role of urban vegetation in local climate of Budapest using satellite measurements

    Science.gov (United States)

    Pongracz, Rita; Bartholy, Judit; Dezso, Zsuzsanna; Fricke, Cathy

    2016-08-01

    Urban areas significantly modify the natural environment due to the concentrated presence of humans and the associated anthropogenic activities. In order to assess this effect, it is essential to evaluate the relationship between urban and vegetated surface covers. In our study we focused on the Hungarian capital, Budapest, in which about 1.7 million inhabitants are living nowadays. The entire city is divided by the river Danube into the hilly, greener Buda side on the west, and the flat, more densely built-up Pest side on the east. Most of the extended urban vegetation, i.e., forests are located in the western Buda side. The effects of the past changing of these green areas are analyzed using surface temperature data calculated from satellite measurements in the infrared channels, and NDVI (Normalized Difference Vegetation Index) derived from visible and near-infrared satellite measurements. For this purpose, data available from sensor MODIS (Moderate Resolution Imaging Spectroradiometer) of NASA satellites (i.e., Terra and Aqua) are used. First, the climatological effects of forests on the urban heat island intensity are evaluated. Then, we also aim to evaluate the relationship of surface temperature and NDVI in this urban environment with special focus on vegetation-related sections of the city where the vegetation cover either increased or decreased remarkably.

  7. Estimation of leaf area index using an angular vegetation index based on in situ measurements and CHRIS/PROBA data

    Science.gov (United States)

    Wang, Lijuan; Zhang, Guimin; Lin, Hui; Liang, Liang; Niu, Zheng

    2016-06-01

    The Normalized Difference Vegetation Index (NDVI) is widely used for Leaf Area Index (LAI) estimation. It is well documented that the NDVI is extremely subject to the saturation problem when LAI reaches a high value. A new multi-angular vegetation index, the Hotspot-darkspot Difference Vegetation Index (HDVI) is proposed to estimate the high density LAI. The HDVI, defined as the difference between the hot and dark spot NDVI, relative to the dark spot NDVI, was proposed based on the Analytical two-layer Canopy Reflectance Model (ACRM) model outputs. This index is validated using both in situ experimental data in wheat and data from the multi-angular optical Compact High-Resolution Imaging Spectrometer (CHRIS) satellite. Both indices, the Hotspot-Darkspot Index (HDS) and the NDVI were also selected to analyze the relationship with LAI, and were compared with new index HDVI. The results show that HDVI is an appropriate proxy of LAI with higher determination coefficients (R2) for both the data from the in situ experiment (R2=0.7342, RMSE=0.0205) and the CHRIS data (R2=0.7749, RMSE=0.1013). Our results demonstrate that HDVI can make better the occurrence of saturation limits with the information of multi-angular observation, and is more appropriate for estimating LAI than either HDS or NDVI at high LAI values. Although the new index needs further evaluation, it also has the potential under the condition of dense canopies. It provides the effective improvement to the NDVI and other vegetation indices that are based on the red and NIR spectral bands.

  8. Vegetation Index and Phenology (VIP) Vegetation Indices 15Days Global 0.05Deg CMG

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The NASA MEaSUREs Vegetation Index and Phenology (VIP) global datasets were created using surface reflectance data from the Advanced Very High Resolution Radiometer...

  9. Vegetation Index and Phenology (VIP) Vegetation Indices Daily Global 0.05Deg CMG

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The NASA MEaSUREs Vegetation Index and Phenology (VIP) global datasets were created using surface reflectance data from the Advanced Very High Resolution Radiometer...

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

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The NASA MEaSUREs Vegetation Index and Phenology (VIP) global datasets were created using surface reflectance data from the Advanced Very High Resolution Radiometer...

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

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The NASA MEaSUREs Vegetation Index and Phenology (VIP) global datasets were created using surface reflectance data from the Advanced Very High Resolution Radiometer...

  12. Desertification Risk Monitoring for North Shaanxi Province, China, Using Normalized Difference Vegetation Index (NDVI)

    Institute of Scientific and Technical Information of China (English)

    2002-01-01

    In this study, the remote sensing is applied to the examination of the relationship between desertification and normalized difference vegetation index (NDVI) in the context of northern Shaanxi Province. This relationship is also examined using spatial analysis methods. A strong negative correlation is found in the largest area desert, indicating that the relationship between desert and NDVI is not a simple linear one and that the correlation coefficient between NDVI and vegetation abundance is significant.The normalized difference vegetation index (NDVI) was compared with other vegetation index-based methodologies. NDVI is a valuable first-cut indicator for such systems, although the analysis and interpretation of its relationship to desertification are complex and also based on the detailed analysis of its reiationship to ecological zone, vegetation type and season. Conclusions thus made would help to upgrade the methodology as an effective tool for early-warning desertification in the northern Shaanxi Province where a drought is a recurring threat. This methodology includes the integration of NDVI with other socio-economic and bio-physical indicators in GIS, the complementation of desert area data with satellite data, and the analysis of the relationship between NDVI and specific climatic zones, for each season and vegetation type.

  13. Multiscaling of vegetative indexes from remote sensing images obtained at different spatial resolutions

    Science.gov (United States)

    Alonso, Carmelo; Tarquis, Ana M.; Zuñiga, Ignacio; Benito, Rosa M.

    2017-04-01

    Vegetation indexes, such as Normalized Difference Vegetation Index (NDVI) and enhanced Vegetation index (EVI), can been used to estimate root zone soil moisture through high resolution remote sensing images. These indexes are based in red (R), near infrared (NIR) and blue (B) wavelengths data. In this work we have studied the scaling properties of both vegetation indexes analyzing the information contained in two satellite data: Landsat-7 and Ikonos. Because of the potential capacity for systematic observations at various scales, remote sensing technology extends possible data archives from present time to over several decades back. For this advantage, enormous efforts have been made by researchers and application specialists to delineate vegetation indexes from local scale to global scale by applying remote sensing imagery. To study the influence of the spatial resolution the vegetation indexes map estimated with Ikonos-2 coded in 8 bits, with a resolution of 4m, have been compared through a multifractal analysis with the ones obtained with Lansat-7 8 bits, of 30 m. resolution, on the same area of study. The scaling behaviour of NDVI and EVI presents several differences that will be discussed based on the multifractal parameters extracted from the analysis. REFERENCES Alonso, C., Tarquis, A. M., Benito, R. M. and Zuñiga, I. Correlation scaling properties between soil moisture and vegetation indices. Geophysical Research Abstracts, 11, EGU2009-13932, 2009. Alonso, C., Tarquis, A. M. and Benito, R. M. Comparison of fractal dimensions based on segmented NDVI fields obtained from different remote sensors. Geophysical Research Abstracts, 14, EGU2012-14342, 2012. Escribano Rodriguez, J., Alonso, C., Tarquis, A.M., Benito, R.M. and Hernandez Diaz-Ambrona, C. Comparison of NDVI fields obtained from different remote sensors. Geophysical Research Abstracts,15, EGU2013-14153, 2013. Lovejoy, S., Tarquis, A., Gaonac'h, H. and Schertzer, D. Single and multiscale remote sensing

  14. Statistical analysis of land surface temperature-vegetation indexes relationship through thermal remote sensing.

    Science.gov (United States)

    Kumar, Deepak; Shekhar, Sulochana

    2015-11-01

    Vegetation coverage has a significant influence on the land surface temperature (LST) distribution. In the field of urban heat islands (UHIs) based on remote sensing, vegetation indexes are widely used to estimate the LST-vegetation relationship. This paper devises two objectives. The first analyzes the correlation between vegetation parameters/indicators and LST. The subsequent computes the occurrence of vegetation parameter, which defines the distribution of LST (for quantitative analysis of urban heat island) in Kalaburagi (formerly Gulbarga) City. However, estimation work has been done on the valuation of the relationship between different vegetation indexes and LST. In addition to the correlation between LST and the normalized difference vegetation index (NDVI), the normalized difference build-up index (NDBI) is attempted to explore the impacts of the green land to the build-up land on the urban heat island by calculating the evaluation index of sub-urban areas. The results indicated that the effect of urban heat island in Kalaburagi city is mainly located in the sub-urban areas or Rurban area especially in the South-Eastern and North-Western part of the city. The correlation between LST and NDVI, indicates the negative correlation. The NDVI suggests that the green land can weaken the effect on urban heat island, while we perceived the positive correlation between LST and NDBI, which infers that the built-up land can strengthen the effect of urban heat island in our case study. Although satellite data (e.g., Landsat TM thermal bands data) has been applied to test the distribution of urban heat islands, but the method still needs to be refined with in situ measurements of LST in future studies.

  15. Non-Lambertian effects on remote sensing of surface reflectance and vegetation index

    Science.gov (United States)

    Lee, T. Y.; Kaufman, Y. J.

    1986-01-01

    This paper discusses the effects of non-Lambertian reflection from a homogeneous surface on remote sensing of the surface reflectance and vegetation index from a satellite. Remote measurement of the surface characteristics is perturbed by atmospheric scattering of sun light. This scattering tends to smooth the angular dependence of non-Lambertian surface reflectances, an effect that is not present in the case of Lambertian surfaces. This effect is calculated to test the validity of a Lambertian assumption used in remote sensing. For the three types of vegetations considered in this study, the assumption of Lambertian surface can be used satisfactorily in the derivation of surface reflectance from remotely measured radiance for a view angle outside the backscattering region. Within the backscattering region, however, the use of the assumption can result in a considerable error in the derived surface reflectance. Accuracy also deteriorates with increasing solar zenith angle. The angular distribution of the surface reflectance derived from remote measurements is smoother than that at the surface. The effect of surface non-Lambertianity on remote sensing of vegetation index is very weak. Since the effect is similiar in the visible and near infrared part of the solar spectrum for the vegetations treated in this study, it is canceled in deriving the vegetation index. The effect of the diffuse skylight on surface reflectance measurements at ground level is also discussed.

  16. Drought and vegetation stress monitoring in Portugal using satellite data

    Directory of Open Access Journals (Sweden)

    C. Gouveia

    2009-02-01

    Full Text Available Remote sensed information on vegetation and soil moisture, namely the Normalised Difference Vegetation Index (NDVI and the Soil Water Index (SWI, is employed to monitor the spatial extent, severity and persistence of drought episodes over Continental Portugal, from 1999 to 2006. The severity of a given drought episode is assessed by evaluating the cumulative impact over time of drought conditions on vegetation. Special attention is given to the drought episodes that have occurred in the last decade, i.e., 1999, 2002 and particularly the major event of 2005. During both the 1999 and 2005 drought episodes negative anomalies of NDVI are observed over large sectors of Southern Portugal for up to nine months (out of eleven of the vegetative cycle. On the contrary, the 2002 event was characterized by negative anomalies in the northern half of Portugal and for a shorter period (eight out of eleven months. The impact of soil moisture on vegetation dynamics is evaluated by analyzing monthly anomalies of SWI and by studying the annual cycle of SWI vs. NDVI. While in the case of the drought episode of 1999 the scarcity of water in the soil persisted until spring, in the recent episode of 2005 the deficit in greenness was already apparent at the end of summer. The impact of dry periods on vegetation is clearly observed in both arable land and forest, and it is found that arable land presents a higher sensitivity. From an operational point of view, obtained results reveal the possibility of using the developed methodology to monitor, in quasi real-time, vegetation stress and droughts in Mediterranean ecosystems.

  17. Drought and vegetation stress monitoring in Portugal using satellite data

    Science.gov (United States)

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

    2009-02-01

    Remote sensed information on vegetation and soil moisture, namely the Normalised Difference Vegetation Index (NDVI) and the Soil Water Index (SWI), is employed to monitor the spatial extent, severity and persistence of drought episodes over Continental Portugal, from 1999 to 2006. The severity of a given drought episode is assessed by evaluating the cumulative impact over time of drought conditions on vegetation. Special attention is given to the drought episodes that have occurred in the last decade, i.e., 1999, 2002 and particularly the major event of 2005. During both the 1999 and 2005 drought episodes negative anomalies of NDVI are observed over large sectors of Southern Portugal for up to nine months (out of eleven) of the vegetative cycle. On the contrary, the 2002 event was characterized by negative anomalies in the northern half of Portugal and for a shorter period (eight out of eleven months). The impact of soil moisture on vegetation dynamics is evaluated by analyzing monthly anomalies of SWI and by studying the annual cycle of SWI vs. NDVI. While in the case of the drought episode of 1999 the scarcity of water in the soil persisted until spring, in the recent episode of 2005 the deficit in greenness was already apparent at the end of summer. The impact of dry periods on vegetation is clearly observed in both arable land and forest, and it is found that arable land presents a higher sensitivity. From an operational point of view, obtained results reveal the possibility of using the developed methodology to monitor, in quasi real-time, vegetation stress and droughts in Mediterranean ecosystems.

  18. Predicting Vegetation Condition from ASCAT Soil Water Index over Southwest India

    Science.gov (United States)

    Pfeil, Isabella Maria; Hochstöger, Simon; Amarnath, Giriraj; Pani, Peejush; Enenkel, Markus; Wagner, Wolfgang

    2017-04-01

    In India, extreme water scarcity events are expected to occur on average every five years. Record-breaking droughts affecting millions of human beings and livestock are common. If the south-west monsoon (summer monsoon) is delayed or brings less rainfall than expected, a season's harvest can be destroyed despite optimal farm management, leading to, in the worst case, life-threatening circumstances for a large number of farmers. Therefore, the monitoring of key drought indicators, such as the healthiness of the vegetation, and subsequent early warning is crucial. The aim of this work is to predict vegetation state from earth observation data instead of relying on models which need a lot of input data, increasing the complexity of error propagation, or seasonal forecasts, that are often too uncertain to be used as a regression component for a vegetation parameter. While precipitation is the main water supply for large parts of India's agricultural areas, vegetation datasets such as the Normalized Difference Vegetation Index (NDVI) provide reliable estimates of vegetation greenness that can be related to vegetation health. Satellite-derived soil moisture represents the missing link between a deficit in rainfall and the response of vegetation. In particular the water available in the root zone plays an important role for near-future vegetation health. Exploiting the added-value of root zone soil moisture is therefore crucial, and its use in vegetation studies presents an added value for drought analyses and decision-support. The soil water index (SWI) dataset derived from the Advanced Scatterometer (ASCAT) on board the Metop satellites represents the water content that is available in the root zone. This dataset shows a strong correlation with NDVI data obtained from measurements of the Moderate Resolution Imaging Spectroradiometer (MODIS), which is exploited in this study. A linear regression function is fit to the multi-year SWI and NDVI dataset with a temporal

  19. 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...

  20. Retrieval of vegetation hydrodynamic parameters from satellite multispectral data

    Science.gov (United States)

    Forzieri, Giovanni; Degetto, Massimo; Righetti, Maurizio; Castelli, Fabio; Preti, Federico

    2013-04-01

    Riparian vegetation plays a crucial role on affecting the floodplain hydraulic roughness, which in turn significantly influences the dynamics of flood waves. This work explores the potential accuracies of retrieving vegetation hydrodynamic parameters through satellite multispectral data. The method is focused on estimation of vegetation height and flexural rigidity for herbaceous patterns and of plant density, tree height, stem diameter, crown base height and crown diameter of high-forest and coppice consociations for arboreal and shrub patterns. The retrieval algorithm performs: (1) classification procedure of riparian corridor; (2) land cover-based Principal Component Analysis of spectral channels; (3) explorative analysis of correlation structure between principal components and biomechanical properties and (4) model identification/estimation/validation for floodplain roughness parameterization. To capture the impacts of stiff/flexible vegetation, a GIS hydrodynamic model has been coupled with a flow resistance external routine that estimates the hydraulic roughness by using simulated water stages and the remote sensing-derived vegetation parameters. The procedure is tested along a 3-km reach of the Avisio river (Trentino Alto Adige, Italy) by comparing extended field surveys and a synchronous SPOT-5 multispectral image acquired on 28/08/2004. Results showed significant correlation values between spectral-derived information and hydrodynamic parameters. Predictive models provided high coefficients of determination, especially for mixed arboreal and shrub land covers. The generated structural parameter maps represent spatially explicit data layers that can be used as inputs to hydrodynamic models to analyze flow resistance effects in different submergence conditions of vegetation. The hydraulic modelling results showed that the new method is able to provide accurate hydraulic output data and to enhance the roughness estimation up to 73% with respect to a

  1. [Construction of age group vegetation index and preliminary application].

    Science.gov (United States)

    Xu, Zhang-hua; Li, Cong-hui; Liu, Jian; Yu, Kun-yong; Gong, Cong-hong; Tang, Meng-ya

    2014-06-01

    In the present paper, one remote sensing index-age group vegetation index (AGVI) was put forward, and its feasibility was verified. Taking 518 groups of pine forest age group data collected in 13 counties (cities) of Sanming, Jiangle, Shaxian, Nanping, Huaan, Yunxiao, Nanping, Anxi, Putian, Changting, Jianyang, Ningde and Fuqing, Fujian Province and HJ-1 CCD multi-spectral image at the same time-phase as the basis, the spectrum differences of blue, green, red, near infrared and NDVI of each age group were analyzed, showing the characteristics of young forest>middle-aged forest>over-mature forest>mature forest>near mature forest at near infrared band and mature forest>near mature forest>over-mature forest>young forest>middle-aged forest at NDVI, thus the age group vegetation index (AGVI) was constructed; the index could increase the absolute and relative spectrum differences among age groups. For the pine forest AGVI, cluster analysis was conducted with K-mean method, showing that the division accuracy of pine forest age group was 80.45%, and the accurate rate was 90.41%. Therefore, the effectiveness of age group vegetation index constructed was confirmed.

  2. MODIS derived vegetation index for drought detection on the San Carlos Apache Reservation

    Science.gov (United States)

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

    2016-01-01

    A variety of vegetation indices derived from remotely sensed data have been used to assess vegetation conditions, enabling the identification of drought occurrences as well as the evaluation of drought impacts. Moderate Resolution Imaging Spectroradiometer (MODIS) Terra 8-day composite data were used to compute the Modified Soil Adjusted Vegetation Index II (MSAVI2) of four dominant vegetation types over a 13-year period (2002 – 2014) on the San Carlos Apache Reservation in Arizona, US. MSAVI2 anomalies were used to identify adverse impacts of drought on vegetation, characterized as mean MSAVI2 below the 13-year average. In terms of interannual variability, we found similar responses between grassland and shrubland, and between woodland and forest vegetation types. We compared MSAVI2 for specific vegetation types with precipitation data at the same time step, and found a lag time of roughly two months for the peak MSAVI2 values following precipitation in a given year. All vegetation types responded to summer monsoon rainfall, while shrubland and annual herbaceous vegetation also displayed a brief spring growing season following winter snowmelt. MSAVI2 values of shrublands corresponded well with precipitation variability both for summer rainfall and winter snowfall, and can be potentially used as a drought indicator on the San Carlos Apache Reservation given its wide geographic distribution. We demonstrated that moderate temporal frequency satellite-based MSAVI2 can provide drought monitoring to inform land management decisions, especially on vegetated tribal land areas where in situ precipitation data are limited.

  3. Long-Term Satellite Detection of Post-Fire Vegetation Trends in Boreal Forests of China

    Directory of Open Access Journals (Sweden)

    Kunpeng Yi

    2013-12-01

    Full Text Available This paper describes the long-term effects on vegetation following the catastrophic fire in 1987 on the northern Great Xing’an Mountain by analyzing the AVHRR GIMMS 15-day composite normalized difference vegetation index (NDVI dataset. Both temporal and spatial characteristics were analyzed for natural regeneration and tree planting scenarios from 1984 to 2006. Regressing post-fire NDVI values on the pre-fire values helped identify the NDVI for burnt pixels in vegetation stands. Stand differences in fire damage were classified into five levels: Very High (VH, High (H, Moderate (M, Low (L and Slight (S. Furthermore, intra-annual and inter-annual post-fire vegetation recovery trajectories were analyzed by deriving a time series of NDVI and relative regrowth index (RRI values for the entire burned area. Finally, spatial pattern and trend analyses were conducted using the pixel-based post-fire annual stands regrowth index (SRI with a nonparametric Mann-Kendall (MK statistics method. The results show that October was a better period compared to other months for distinguishing the post- and pre-fire vegetation conditions using the NDVI signals in boreal forests of China because colored leaves on grasses and shrubs fall down, while the leaves on healthy trees remain green in October. The MK statistics method is robustly capable of detecting vegetation trends in a relatively long time series. Because tree planting primarily occurred in the severely burned area (approximately equal to the Medium, High and Very High fire damage areas following the Daxing’anling fire in 1987, the severely burned area exhibited a better recovery trend than the lightly burned regions. Reasonable tree planting can substantially quicken the recovery and shorten the restoration time of the target species. More detailed satellite analyses and field data will be required in the future for a more convincing validation of the results.

  4. Global changes in dryland vegetation dynamics (1988–2008 assessed by satellite remote sensing: combining a new passive microwave vegetation density record with reflective greenness data

    Directory of Open Access Journals (Sweden)

    N. Andela

    2013-05-01

    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 use 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 seems 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, bringing new insights on vegetation dynamics.

  5. 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.

  6. Estimation of Leaf Area Index Using IRS Satellite Images

    Directory of Open Access Journals (Sweden)

    A Faridhosseini

    2012-12-01

    Full Text Available Estimation of vegetation cover attributes, such as the Leaf Area Index (LAI, is an important step in identifying the amount of water use for some plants. The goal of this study is to investigate the feasibility of using IRS LISS-III data to retrieve LAI. To get a LAI retrieval model based on reflectance and vegetation index, detailed field data were collected in the study area of eastern Iran. In this study, atmospheric corrected IRS LISS-III imagery was used to calculate Normalized Difference Vegetation Index (NDVI. Data of 50 samples of LAI were measured by Sun Scan System – SS1 in the study area. In situ measurements of LAI were related to widely use spectral vegetation indices (NDVI. The best model through analyzing the results was LAI = 19.305×NDVI+5.514 using the method of linear-regression analysis. The results showed that the correlation coefficient R2 was 0.534 and RMSE was 0.67. Thereby, suggesting that, when using remote sensing NDVI for LAI estimation, not only is the choice of NDVI of importance but also prior knowledge of plant architecture and soil background. Hence, some kind of landscape stratification is required before using multi- spectral imagery for large-scale mapping of vegetation biophysical variables.

  7. Vegetation monitoring for Guatemala: a comparison between simulated VIIRS and MODIS satellite data

    Science.gov (United States)

    Boken, Vijendra K.; Easson, Gregory L.; Rowland, James

    2010-01-01

    The advanced very high resolution radiometer (AVHRR) and moderate resolution imaging spectroradiometer (MODIS) data are being widely used for vegetation monitoring across the globe. However, sensors will discontinue collecting these data in the near future. National Aeronautics and Space Administration is planning to launch a new sensor, visible infrared imaging radiometer suite (VIIRS), to continue to provide satellite data for vegetation monitoring. This article presents a case study of Guatemala and compares the simulated VIIRS-Normalized Difference Vegetation Index (NDVI) with MODIS-NDVI for four different dates each in 2003 and 2005. The dissimilarity between VIIRS-NDVI and MODIS-NDVI was examined on the basis of the percent difference, the two-tailed student's t-test, and the coefficient of determination, R 2. The per cent difference was found to be within 3%, the p-value ranged between 0.52 and 0.99, and R 2 exceeded 0.88 for all major types of vegetation (basic grains, rubber, sugarcane, coffee and forests) found in Guatemala. It was therefore concluded that VIIRS will be almost equally capable of vegetation monitoring as MODIS.

  8. Phenological dynamics of arctic tundra vegetation and its implications on satellite imagery interpretation

    Science.gov (United States)

    Juutinen, Sari; Aurela, Mika; Mikola, Juha; Räsänen, Aleksi; Virtanen, Tarmo

    2016-04-01

    Remote sensing is a key methodology when monitoring the responses of arctic ecosystems to climatic warming. The short growing season and rapid vegetation development, however, set demands to the timing of image acquisition in the arctic. We used multispectral very high spatial resolution satellite images to study the effect of vegetation phenology on the spectral reflectance and image interpretation in the low arctic tundra in coastal Siberia (Tiksi, 71°35'39"N, 128°53'17"E). The study site mainly consists of peatlands, tussock, dwarf shrub, and grass tundra, and stony areas with some lichen and shrub patches. We tested the hypotheses that (1) plant phenology is responsive to the interannual weather variation and (2) the phenological state of vegetation has an impact on satellite image interpretation and the ability to distinguish between the plant communities. We used an empirical transfer function with temperature sums as drivers to reconstruct daily leaf area index (LAI) for the different plant communities for years 2005, and 2010-2014 based on measured LAI development in summer 2014. Satellite images, taken during growing seasons, were acquired for two years having late and early spring, and short and long growing season, respectively. LAI dynamics showed considerable interannual variation due to weather variation, and particularly the relative contribution of graminoid dominated communities was sensitive to these phenology shifts. We have also analyzed the differences in the reflectance values between the two satellite images taking account the LAI dynamics. These results will increase our understanding of the pitfalls that may arise from the timing of image acquisition when interpreting the vegetation structure in a heterogeneous tundra landscape. Very high spatial resolution multispectral images are available at reasonable cost, but not in high temporal resolution, which may lead to compromises when matching ground truth and the imagery. On the other hand

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

    Directory of Open Access Journals (Sweden)

    Gabriela Camargos Lima

    2013-08-01

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

  10. Estimating foliar nitrogen in Eucalyptus using vegetation indexes

    Directory of Open Access Journals (Sweden)

    Luiz Felipe Ramalho de Oliveira

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

  11. Higher northern latitude normalized difference vegetation index and growing season trends from 1982 to 1999

    Science.gov (United States)

    Tucker, C. J.; Slayback, D. A.; Pinzon, J. E.; Los, S. O.; Myneni, R. B.; Taylor, M. G.

    2001-01-01

    Normalized difference vegetation index data from the polar-orbiting National Oceanic and Atmospheric Administration meteorological satellites from 1982 to 1999 show significant variations in photosynthetic activity and growing season length at latitudes above 35 degrees N. Two distinct periods of increasing plant growth are apparent: 1982-1991 and 1992-1999, separated by a reduction from 1991 to 1992 associated with global cooling resulting from the volcanic eruption of Mt. Pinatubo in June 1991. The average May to September normalized difference vegetation index from 45 degrees N to 75 degrees N increased by 9% from 1982 to 1991, decreased by 5% from 1991 to 1992, and increased by 8% from 1992 to 1999. Variations in the normalized difference vegetation index were associated with variations in the start of the growing season of -5.6, +3.9, and -1.7 days respectively, for the three time periods. Our results support surface temperature increases within the same period at higher northern latitudes where temperature limits plant growth.

  12. Effects of saltwater intrusion on pinewood vegetation using satellite ASTER data: the case study of Ravenna (Italy).

    Science.gov (United States)

    Barbarella, M; De Giglio, M; Greggio, N

    2015-04-01

    The San Vitale pinewood (Ravenna, Italy) is part of the remaining wooded areas within the southeastern Po Valley. Several studies demonstrated a widespread saltwater intrusion in the phreatic aquifer caused by natural and human factors in this area as the whole complex coastal system. Groundwater salinization affects soils and vegetation, which takes up water from the shallow aquifer. Changes in groundwater salinity induce variations of the leaf properties and vegetation cover, recognizable by satellite sensors as a response to different spectral bands. A procedure to identify stressed areas from satellite remote sensing data, reducing the expensive and time-consuming ground monitoring campaign, was developed. Multispectral Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data, acquired between May 2005 and August 2005, were used to calculate Normalized Difference Vegetation Index (NDVI). Within the same vegetation type (thermophilic deciduous forest), the areas with the higher vegetation index were taken as reference to identify the most stressed areas using a statistical approach. To confirm the findings, a comparison was conducted using contemporary groundwater salinity data. The results were coherent in the areas with highest and lowest average NDVI values. Instead, to better understand the behavior of the intermediate areas, other parameters influencing vegetation (meteorological data, water table depth, and tree density) were added for the interpretation of the results.

  13. Estimating the biomass of unevenly distributed aquatic vegetation in a lake using the normalized water-adjusted vegetation index and scale transformation method.

    Science.gov (United States)

    Gao, Yongnian; Gao, Junfeng; Wang, Jing; Wang, Shuangshuang; Li, Qin; Zhai, Shuhua; Zhou, Ya

    2017-12-01

    Satellite remote sensing is advantageous for the mapping and monitoring of aquatic vegetation biomass at large spatial scales. We proposed a scale transformation (CT) method of converting the field sampling-site biomass from the quadrat to pixel scale and a new normalized water-adjusted vegetation index (NWAVI) based on remotely sensed imagery for the biomass estimation of aquatic vegetation (excluding emergent vegetation). We used a modeling approach based on the proposed CT method and NWAVI as well as statistical analyses including linear, quadratic, logarithmic, cubic, exponential, inverse and power regression to estimate the aquatic vegetation biomass, and we evaluated the performance of the biomass estimation. We mapped the spatial distribution and temporal change of the aquatic vegetation biomass using a geographic information system in a test lake in different months. The exponential regression models based on CT and the NWAVI had optimal adjusted R(2), F and Sig. values in both May and August 2013. The scatter plots of the observed versus the predicted biomass showed that most of the validated field sites were near the 1:1 line. The RMSE, ARE and RE values were small. The spatial distribution and change of the aquatic vegetation biomass in the study area showed clear variability. Among the NWAVI-based and other vegetation index-based models, the CT and NWAVI-based models had the largest adjusted R(2), F and the smallest ARE values in both tests. The proposed modeling scheme is effective for the biomass estimation of aquatic vegetation in lakes. It indicated that the proposed method can provide a most accurate spatial distribution map of aquatic vegetation biomass for lake ecological management. More accurate biomass maps of aquatic vegetation are essential for implementing conservation policy and for reducing uncertainties in our understanding of the lake carbon cycle. Copyright © 2017 Elsevier B.V. All rights reserved.

  14. Vegetation coupling to global climate: Trajectories of vegetation change and phenology modeling from satellite observations

    Science.gov (United States)

    Fisher, Jeremy Isaac

    Important systematic shifts in ecosystem function are often masked by natural variability. The rich legacy of over two decades of continuous satellite observations provides an important database for distinguishing climatological and anthropogenic ecosystem changes. Examples from semi-arid Sudanian West Africa and New England (USA) illustrate the response of vegetation to climate and land-use. In Burkina Faso, West Africa, pastoral and agricultural practices compete for land area, while degradation may follow intensification. The Nouhao Valley is a natural experiment in which pastoral and agricultural land uses were allocated separate, coherent reserves. Trajectories of annual net primary productivity were derived from 18 years of coarse-grain (AVHRR) satellite data. Trends suggested that pastoral lands had responded rigorously to increasing rainfall after the 1980's droughts. A detailed analysis at Landsat resolution (30m) indicated that the increased vegetative cover was concentrated in the river basins of the pastoral region, implying a riparian wood expansion. In comparison, riparian cover was reduced in agricultural regions. We suggest that broad-scale patterns of increasing semi-arid West African greenness may be indicative of climate variability, whereas local losses may be anthropogenic in nature. The contiguous deciduous forests, ocean proximity, topography, and dense urban developments of New England provide an ideal landscape to examine influences of climate variability and the impact of urban development vegetation response. Spatial and temporal patterns of interannual climate variability were examined via green leaf phenology. Phenology, or seasonal growth and senescence, is driven by deficits of light, temperature, and water. In temperate environments, phenology variability is driven by interannual temperature and precipitation shifts. Average and interannual phenology analyses across southern New England were conducted at resolutions of 30m (Landsat

  15. [MTCARI: A kind of vegetation index monitoring vegetation leaf chlorophyll content based on hyperspectral remote sensing].

    Science.gov (United States)

    Meng, Qing-ye; Dong, Heng; Qin, Qi-ming; Wang, Jin-liang; Zhao, Jiang-hua

    2012-08-01

    The chlorophyll content of plant has relative correlation with photosynthetic capacity and growth levels of plant. It affects the plant canopy spectra, so the authors can use hyperspectral remote sensing to monitor chlorophyll content. By analyzing existing mature vegetation index model, the present research pointed out that the TCARI model has deficiencies, and then tried to improve the model. Then using the PROSPECT+SAIL model to simulate the canopy spectral under different levels of chlorophyll content and leaf area index (LAI), the related constant factor has been calculated. The research finally got modified transformed chlorophyll absorption ratio index (MTCARI). And then this research used optimized soil background adjust index (OSAVI) to improve the model. Using the measured data for test and verification, the model has good reliability.

  16. Satellite image analysis for surveillance, vegetation and climate change

    Energy Technology Data Exchange (ETDEWEB)

    Cai, D Michael [Los Alamos National Laboratory

    2011-01-18

    Recently, many studies have provided abundant evidence to show the trend of tree mortality is increasing in many regions, and the cause of tree mortality is associated with drought, insect outbreak, or fire. Unfortunately, there is no current capability available to monitor vegetation changes, and correlate and predict tree mortality with CO{sub 2} change, and climate change on the global scale. Different survey platforms (methods) have been used for forest management. Typical ground-based forest surveys measure tree stem diameter, species, and alive or dead. The measurements are low-tech and time consuming, but the sample sizes are large, running into millions of trees, covering large areas, and spanning many years. These field surveys provide powerful ground validation for other survey methods such as photo survey, helicopter GPS survey, and aerial overview survey. The satellite imagery has much larger coverage. It is easier to tile the different images together, and more important, the spatial resolution has been improved such that close to or even higher than aerial survey platforms. Today, the remote sensing satellite data have reached sub-meter spatial resolution for panchromatic channels (IKONOS 2: 1 m; Quickbird-2: 0.61 m; Worldview-2: 0.5 m) and meter spatial resolution for multi-spectral channels (IKONOS 2: 4 meter; Quickbird-2: 2.44 m; Worldview-2: 2 m). Therefore, high resolution satellite imagery can allow foresters to discern individual trees. This vital information should allow us to quantify physiological states of trees, e.g. healthy or dead, shape and size of tree crowns, as well as species and functional compositions of trees. This is a powerful data resource, however, due to the vast amount of the data collected daily, it is impossible for human analysts to review the imagery in detail to identify the vital biodiversity information. Thus, in this talk, we will discuss the opportunities and challenges to use high resolution satellite imagery and

  17. Leaf area index retrieval based on canopy reflectance and vegetation index in easternChina

    Institute of Scientific and Technical Information of China (English)

    JIANGJianjun; CHENSuozhong; CAOShunxian; WUHongan; ZHANGLi; ZHANGHailong

    2005-01-01

    The aim of this paper is to investigate the feasibility of using Landsat TM data to retrieve leaf area index (LAI). To get a LAI retrieval model based ground reflectance and vegetation index,detailed field data were collected in the study area of eastern China, dominated by bamboo, tea plant and greengage. Plant canopy reflectance of Landsat TM wavelength bands has been inversed using software of 6S. LAI is an important ecological parameter. In this paper, atmospheric corrected Landsat TM imagery was utilized to calculate different vegetation indices (Ⅵ), such as simple ratio vegetationin dex (SR), shortwave infrared modified simple ratio (MSR), and normalized difference vegetation index (NDⅥ). Data of 53 samples of LAI were measured by LAI-2000 (LI-COR) in the study area.LAI was modeled based on different reflectances of bands and different vegetation indices from Landsat TM and LAI samples data. There are certainly correlations between LAI and the reflectance of TM3, TM4, TM5 and TM7. The best model through analyzing the results is LAI = 1.2097*MSR+0.4741 using the method of regression analysis. The result shows that the correlation coefficient R2 is 0.5157, and average accuracy is 85.75%. However, whether the model of this paper is suitable for application in subtropics needs to be verified in the future.

  18. Using normalized difference vegetation index to estimate carbon fluxes from small rotationally grazed pastures

    Science.gov (United States)

    Skinner, R.H.; Wylie, B.K.; Gilmanov, T.G.

    2011-01-01

    Satellite-based normalized difference vegetation index (NDVI) data have been extensively used for estimating gross primary productivity (GPP) and yield of grazing lands throughout the world. However, the usefulness of satellite-based images for monitoring rotationally-grazed pastures in the northeastern United States might be limited because paddock size is often smaller than the resolution limits of the satellite image. This research compared NDVI data from satellites with data obtained using a ground-based system capable of fine-scale (submeter) NDVI measurements. Gross primary productivity was measured by eddy covariance on two pastures in central Pennsylvania from 2003 to 2008. Weekly 250-m resolution satellite NDVI estimates were also obtained for each pasture from the moderate resolution imaging spectroradiometer (MODIS) sensor. Ground-based NDVI data were periodically collected in 2006, 2007, and 2008 from one of the two pastures. Multiple-regression and regression-tree estimates of GPP, based primarily on MODIS 7-d NDVI and on-site measurements of photosynthetically active radiation (PAR), were generally able to predict growing-season GPP to within an average of 3% of measured values. The exception was drought years when estimated and measured GPP differed from each other by 11 to 13%. Ground-based measurements improved the ability of vegetation indices to capture short-term grazing management effects on GPP. However, the eMODIS product appeared to be adequate for regional GPP estimates where total growing-season GPP across a wide area would be of greater interest than short-term management-induced changes in GPP at individual sites.

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

    Science.gov (United States)

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

    2013-01-01

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

  20. Vegetation index methods for estimating evapotranspiration by remote sensing

    Science.gov (United States)

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

    2010-01-01

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

  1. [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.

  2. Poverty, health and satellite-derived vegetation indices: their inter-spatial relationship in West Africa.

    Science.gov (United States)

    Sedda, Luigi; Tatem, Andrew J; Morley, David W; Atkinson, Peter M; Wardrop, Nicola A; Pezzulo, Carla; Sorichetta, Alessandro; Kuleszo, Joanna; Rogers, David J

    2015-03-01

    Previous analyses have shown the individual correlations between poverty, health and satellite-derived vegetation indices such as the normalized difference vegetation index (NDVI). However, generally these analyses did not explore the statistical interconnections between poverty, health outcomes and NDVI. In this research aspatial methods (principal component analysis) and spatial models (variography, factorial kriging and cokriging) were applied to investigate the correlations and spatial relationships between intensity of poverty, health (expressed as child mortality and undernutrition), and NDVI for a large area of West Africa. This research showed that the intensity of poverty (and hence child mortality and nutrition) varies inversely with NDVI. From the spatial point-of-view, similarities in the spatial variation of intensity of poverty and NDVI were found. These results highlight the utility of satellite-based metrics for poverty models including health and ecological components and, in general for large scale analysis, estimation and optimisation of multidimensional poverty metrics. However, it also stresses the need for further studies on the causes of the association between NDVI, health and poverty. Once these relationships are confirmed and better understood, the presence of this ecological component in poverty metrics has the potential to facilitate the analysis of the impacts of climate change on the rural populations afflicted by poverty and child mortality. © The Author 2015. Published by Oxford University Press on behalf of Royal Society of Tropical Medicine and Hygiene. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  3. Amazon vegetation greenness as measured by satellite sensors over the last decade

    OpenAIRE

    Atkinson, P.M.; Dash, J.; Jeganathan, C.

    2011-01-01

    [1] During the last decade two major drought events, one in 2005 and another in 2010, occurred in the Amazon basin. Several studies have claimed the ability to detect the effect of these droughts on Amazon vegetation response, measured through satellite sensor vegetation indices (VIs). Such monitoring capability is important as it potentially links climate changes (increasing frequency and severity of drought), vegetation response as observed through vegetation greenness, and land-atmosphere ...

  4. Assessment of spatially distributed values of Kc using vegetation indices derived from medium resolution satellite data

    Science.gov (United States)

    Greco, M.; Simoniello, T.; Lanfredi, M.; Russo, A. L.

    2010-09-01

    In the last years, the theme of suitable assessment of irrigation water supply has been raised relevant interest for both general principles of sustainable development and optimization of water resources techniques and management. About 99% of the water used in agriculture is lost by crops as evapotranspiration (ET). Thus, it becomes crucial to drive direct or indirect measurement in order to perform a suitable evaluation of water loss by evapotranspiration (i.e. actual evapotranspiration) as well as crop water status and its effect on the production. The main methods used to measure evapotranspiration are available only at field scale (Bowen ratio, eddy correlation system, soil water balance) confined to a small pilot area, generally due to expense and logistical constraints. This led over the last 50 years to the development of a large number of empirical methods to estimate evapotranspiration through different climatic and meteorological variables as well as combining models, based on aerodynamic theory and energy balance, taking into account both canopy properties and meteorological conditions. Among these, the Penman-Monteith equation seems to give the best results providing a robust and consistent method world wide accepted. Such conventional methods only provide accurate evapotranspiration assessment for a homogeneous region nearby the meteorological gauge station and cannot be extrapolated to other different sites; whereas remote sensing techniques allow for filling up such a gap. Some of these satellite techniques are based on the use of thermal band signals as inputs for energy balance equations. Another common approach is mainly based on the FAO method for estimating crop evapotranspiration, in which evapotranspiration data are multiplied by crop coefficients, Kc, derived from satellite multispectral vegetation indices obtained. The rationale behind such a link considers that Kc and vegetation indices are sensitive to both leaf area index and fractional

  5. Vegetation

    DEFF Research Database (Denmark)

    Epstein, H.E.; Walker, D.A.; Bhatt, U.S.;

    2012-01-01

    • Over the past 30 years (1982-2011), the Normalized Difference Vegetation Index (NDVI), an index of green vegetation, has increased 15.5% in the North American Arctic and 8.2% in the Eurasian Arctic. In the more southern regions of Arctic tundra, the estimated aboveground plant biomass has...

  6. Ecological restoration of groundwater-dependent vegetation in the arid Ejina Delta: evidences from satellite evapotranspiration

    Science.gov (United States)

    Kai, Lu; Garcia, Monica; Yu, Jingjie; Zhang, Yichi; Wang, Ping; Wang, Sheng; Liu, Xiao

    2017-04-01

    The ecological water conveyance project (EWCP) in the Ejina delta, a typical hyper-arid area of China, aimed to restore degraded phreatophytic ecosystems. We assessed the degree of ecosystem recovery using as an ecohydrological indicator a ratio between actual and potential evapotranspiration derived from MODIS since the beginning of the project in 2001. The selected indicator was the Temperature Vegetation Dryness Index (TVDI) which was validated with Eddy covariance (EC) data confirming its applicability to monitor groundwater dependent vegetation. The spatial analyses of the evapotranspiration ratio show drying trends (2000-2015) which are stronger and also cover larger extensions than the wetting trends. Thus, the condition of key riparian areas relying mostly on surface water improved since the project began. However, groundwater dependent ecosystems located in lower river Xihe reaches present drying trends. It seems that despite of the runoff supplemented by the EWCP project, there is nowadays more inequality in the access to water by groundwater dependent ecosystems in the Ejina Delta. The study shows that energy-evaporation indices, relying on radiometric satellite temperature like the TVDI, can detect degradation signals that otherwise might go undetected by NDVI analyses especially in arid regions, where vegetation indices are greatly affected by the soil background signals. Additionally, they can provide timely information to water managers on how much water to allocate for a sustainable restoration program.

  7. New Vegetation Index and Its Application in Estimating Leaf Area Index of Rice

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    Leaf area index (LAI) is an important characteristic of land surface vegetation system, and is also a key parameter for the models of global water balancing and carbon circulation. By using the reflectance values of Landsat-5 blue, green and red channels simulated from rice reflectance spectrum, the sensitivities of the bands to LAI were analyzed, and the response and capability to estimate LAI of various NDVIs (normalized difference vegetation indices), which were established by substituting the red band of general NDVI with all possible combinations of red, green and blue bands, were assessed. Finally,the conclusion was tested by rice data at different conditions. The sensitivities of red, green and blue bands to LAI were different under various conditions. When LAI was less than 3, red and blue bands were more sensitive to LAI. Though green band in the circumstances was less sensitive to LAI than red and blue bands, it was sensitive to LAI in a wider range. When the vegetation indices were constituted by all kinds of combinations of red, green and blue bands, the premise for making the sensitivity of these vegetation indices to LAI be meaningful was that the value of one of the combinations was greater than 0.024, i.e. visible reflectance (VIS)>0.024. Otherwise, the vegetation indices would be saturated, resulting in lower estimation accuracy of LAI. Comparison on the capabilities of the vegetation indices derived from all kinds of combinations of red, green and blue bands to LAI estimation showed that GNDVI (Green NDVI) and GBNDVI (Green-Blue NDVI) had the best relations with LAI. The capabilities of GNDVI and GBNDVI to LAI estimation were tested under different circumstances, and the same result was acquired. It suggested that GNDVI and GBNDVI performed better to predict LAI than the conventional NDVI.

  8. Numerical Simulation of the Impact of Vegetation Index on the Interannual Variation of Summer Precipitation in the Yellow River Basin

    Institute of Scientific and Technical Information of China (English)

    2005-01-01

    Two sets of numerical experiments using the coupled National Center for Environmental Prediction General Circulation Model (NCEP/GCM T42L18) and the Simplified Simple Biosphere land surface scheme (SSiB) were carried out to investigate the climate impacts of fractional vegetation cover (FVC)and leaf area index (LAI) on East Asia summer precipitation, especially in the Yellow River Basin (YRB).One set employed prescribed FVC and LAI which have no interannual variations based on the climatology of vegetation distribution; the other with FVC and LAI derived from satellite observations of the International Satellite Land Surface Climate Project (ISLSCP) for 1987 and 1988. The simulations of the two experiments were compared to study the influence of FVC, LAI on summer precipitation interannual variation in the YRB. Compared with observations and the NCEP reanalysis data, the experiment that included both the effects of satellite-derived vegetation indexes and sea surface temperature (SST)produced better seasonal and interannual precipitation variations than the experiment with SST but no interannual variations in FVC and LAI, indicating that better representations of the vegetation index and its interannual variation may be important for climate prediction. The difference between 1987 and 1988indicated that with the increase of FVC and LAI, especially around the YRB, surface albedo decreased,net surface radiation increased, and consequently local evaporation and precipitation intensified. Further more, surface sensible heat flux, surface temperature and its diurnal variation decreased around the YRB in response to more vegetation. The decrease of surface-emitting longwave radiation due to the cooler surface outweighed the decrease of surface solar radiation income with more cloud coverage, thus maintaining the positive anomaly of net surface radiation. Further study indicated that moisture flux variations associated with changes in the general circulation also

  9. Use of satellite imagery to map and monitor vegetation in New Zealand

    OpenAIRE

    Stephens, P. R.; Dymond, J. R.; Brown, L J

    1995-01-01

    研究概要:Land resource and environmental decision makers require quantitative information on the spatial distribution of vegetation types and their condition, and changes in these over time. Such vegetation mapping and monitoring is often required to be undertaken quickly. Remotely-sensed satellite imagery, in conjunction with other data sources, have been used to satisfy this need. This paper describes the uses of satellite imagery by reference to three regional mapping projects in New Zealand. ...

  10. An efficient unsupervised index based approach for mapping urban vegetation from IKONOS imagery

    Science.gov (United States)

    Anchang, Julius Y.; Ananga, Erick O.; Pu, Ruiliang

    2016-08-01

    Despite the increased availability of high resolution satellite image data, their operational use for mapping urban land cover in Sub-Saharan Africa continues to be limited by lack of computational resources and technical expertise. As such, there is need for simple and efficient image classification techniques. Using Bamenda in North West Cameroon as a test case, we investigated two completely unsupervised pixel based approaches to extract tree/shrub (TS) and ground vegetation (GV) cover from an IKONOS derived soil adjusted vegetation index. These included: (1) a simple Jenks Natural Breaks classification and (2) a two-step technique that combined the Jenks algorithm with agglomerative hierarchical clustering. Both techniques were compared with each other and with a non-linear support vector machine (SVM) for classification performance. While overall classification accuracy was generally high for all techniques (>90%), One-Way Analysis of Variance tests revealed the two step technique to outperform the simple Jenks classification in terms of predicting the GV class. It also outperformed the SVM in predicting the TS class. We conclude that the unsupervised methods are technically as good and practically superior for efficient urban vegetation mapping in budget and technically constrained regions such as Sub-Saharan Africa.

  11. Sources of Divergence in Remote Sensing of Vegetation Phenology From Multiple Long Term Satellite Data Records

    Science.gov (United States)

    Barreto, A.; Didan, K.; Miura, T.

    2008-12-01

    Changes in vegetation phenology depict an integrated response to change in environmental factors and provide valuable information to global change research. Typically, remote sensing of vegetation phenology is based on the analysis of vegetation index temporal profiles, because of their simplicity, stability, and inherent resistant to noise. Most phenology estimates are, however, limited to using one sensor owing to the inter-sensor continuity challenges. Although, phenology is used for a variety of research and application topics, the central premise remains the study of vegetation dynamics change in response to change in climate and other factors. Consequently, the consistency and length of data records are key requirements. With satellite missions lasting few years only, long term phenology measures will have to be based on a mixture of satellite data records. In this study we compared phenology parameters from the AVHRR-GIMMS and MODIS NDVI records (1982- 2007). We analyzed both records globally using a cluster approach to abate noise and focus on the landscape level vegetation dynamic. The cluster approach, assumes that phenology is controlled by a complex set of factors that could be encapsulated by homogeneous climate, soil, elevational gradient, sun- shade exposure, and biophysical capacity. We applied this method to each of the sensors and examined three fundamental phenology parameters: the start and end of the growing season and the cumulative seasonal signal. These parameters are sensitive to, and are capable of capturing changes in the underlying environmental factors. Our results indicate that a large divergence exist over the dense forest of the tropics. This divergence was attributed to MODIS saturation rather than NDVI saturation. Boreal forests exhibited also large disagreement owing to snow cover and related differences in data processing. Furthermore, agricultural areas showed the most irregular phenological signals. This noise resulted from the

  12. Principle and application of three-band gradient difference vegetation index

    Institute of Scientific and Technical Information of China (English)

    TANG; Shihao; ZHU; Qijiang; WANG; Jindi; ZHOU; Yuyu; ZHAO

    2005-01-01

    Vegetation index is a simple, effective and experiential measurement of terrestrial vegetation activity, and plays a very important role in qualitative and quantitative remote sensing. Aiming at shortages of current vegetation indices, and starting from the analysis of vegetation spectral characteristics, we put forward a new vegetation index, the three-band gradient difference vegetation index (TGDVI), and established algorithms to inverse crown cover fraction and leaf area index (LAI) from it. Theoretical analysis and model simulation show that TGDVI has high saturation point and the ability to remove the influence of background to some degree, and the explicit functional relation with crown cover fraction and LAI can be established. Moreover, study shows that TGDVI also has the ability to partly remove the influence of thin cloud. Experiment in the Shunyi District, Beijing, China shows that reasonable result can be reached using the vegetation index to retrieve LAI. We also theoretically analyzed the reason why the normalized difference vegetation index (NDVI) owns the low saturation point, and show that it is determined by the definition of NDVI and the characteristic of vegetation spectra, and is unavoidable to some degree. Meanwhile, through model simulation, we also indicate that the relationship between simple ratio vegetation index (SR) and LAI closes to a piecewise linear one instead of a linear one, which is mainly caused by the influence of background and different change rates of reflectance in red and infrared bands with LAI increasing.

  13. Estimation of vegetation cover resilience from satellite time series

    Directory of Open Access Journals (Sweden)

    T. Simoniello

    2008-07-01

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

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

  14. Satellite NDVI Assisted Monitoring of Vegetable Crop Evapotranspiration in California’s San Joaquin Valley

    Directory of Open Access Journals (Sweden)

    Thomas J. Trout

    2012-02-01

    Full Text Available Reflective bands of Landsat-5 Thematic Mapper satellite imagery were used to facilitate the estimation of basal crop evapotranspiration (ETcb, or potential crop water use, in San Joaquin Valley fields during 2008. A ground-based digital camera measured green fractional cover (Fc of 49 commercial fields planted to 18 different crop types (row crops, grains, orchard, vineyard of varying maturity over 11 Landsat overpass dates. Landsat L1T terrain-corrected images were transformed to surface reflectance and converted to normalized difference vegetation index (NDVI. A strong linear relationship between NDVI and Fc was observed (r2 = 0.96, RMSE = 0.062. The resulting regression equation was used to estimate Fc for crop cycles of broccoli, bellpepper, head lettuce, and garlic on nominal 7–9 day intervals for several study fields. Prior relationships developed by weighing lysimeter were used to transform Fc to fraction of reference evapotranspiration, also known as basal crop coefficient (Kcb. Measurements of grass reference evapotranspiration from the California Irrigation Management Information System were then used to calculate ETcb for each overpass date. Temporal profiles of Fc, Kcb, and ETcb were thus developed for the study fields, along with estimates of seasonal water use. Daily ETcb retrieval uncertainty resulting from error in satellite-based Fc estimation was < 0.5 mm/d, with seasonal uncertainty of 6–10%. Results were compared with FAO-56 irrigation guidelines and prior lysimeter observations for reference.

  15. Constrained projections of high northern latitudinal photosynthesis increase by satellite observations of vegetation greenness

    Science.gov (United States)

    Winkler, Alexander J.; Myneni, Ranga; Brovkin, Victor

    2017-04-01

    Satellite observations of the last three decades provide strong evidence that the Earth is greening. Especially in northern high latitudes, a substantial increase of the leaf area index (LAI), an indicator of greening, is observed. For these regions, it is assumed that plant growth benefits from higher temperature (radiative effect) and rising atmospheric CO2 concentration (CO2 fertilization effect). This greening trend, in terms of increasing LAI, is also simulated by various global ecosystem models. We also found a persistent greening trend analyzing historical simulations of Earth system models (ESM) participating in Phase 5 of the Coupled Model Intercomparison Project (CMIP5). However, a wide spread in magnitude of an associated increase of terrestrial gross primary production (GPP) among the ESMs is found, and thus contributes to pronounced uncertainties in projections of future climate change. Here we demonstrate that the tight correlation between enhanced GPP of high northern latitudinal ecosystems and their LAI sensitivity to both key environmental factors, temperature and CO2 concentration, opens up the possibility of an Emergent Constraint on plant photosynthesis. Combining this almost linear relationship across the ensemble of CMIP5 models with the LAI trends in the long-term satellite records, we are able to constrain projections of vegetation growth increase for respective ecosystems.

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

    Science.gov (United States)

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

    2013-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Russell L. Scott

    2013-08-01

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

  18. Application of a simple dynamic vegetation model to an experimental plot and validation through satellite data and field observations

    Science.gov (United States)

    Ruiz-Pérez, Guiomar; Pasquato, Marta; Medici, Chiara; González-Sanchis, María; Molina, Antonio; Fernandes, Tarcísio José Gualberto; del Campo, Antonio; Francés, Félix

    2014-05-01

    It is well known that the vegetation plays a key role in the catchment's water balance particularly for semi-arid areas that generally are water-controlled ecosystems. For this reason, the number of hydrological models which include vegetation as a state variable has increased substantially in the last decade. However, many of the available dynamic vegetation models are quite complex.To cope with the difficulty of estimating a large number of parameters and inputs, the authors focused on the use of a parsimonious model called LUE-model. This model is based on the amount of photosynthetically active radiation absorbed by green vegetation (APAR) and the Light Use Efficiency index (the efficiency by which that radiation is converted to plant biomass increment) in order to compute the gross primary production (GPP). The advantages of this simple conceptualization are: (1) the low number of parameters, (2) it could be easily coupled with a hydrological model and, (3) as it is based on APAR, it is directly connected with satellite data. This model has been calibrated and validated using remote sensing data and afterwards further tested against field observations. Plant transpiration and soil moisture were obtained in an experimental plot of a semi-arid catchment (La Hunde, East of Spain), during the period from 27/03/2009 to 31/05/2011, covered by Aleppo pine.The satellite data used in this study were: the Normalized Difference Vegetation Index (NDVI) and the Enhanced Vegetation Index (EVI), both included in the products MOD13Q1 and MYD13Q1. Concerning NDVI, its own definition links this index to the "greenness" of the target, so that it appears highly linked to chlorophyll content and vegetation condition. Recent studies about Aleppo pine have shown that NDVI is sensitive to water stress, because the photosynthetic pigment is it. For this reason, the model simulated LAI was corrected by a plant water-stress factor. After such correction, the correlation coefficient with

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

    Science.gov (United States)

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

    2015-04-01

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

  20. 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

    2013-01-01

    of these changes. This study investigates the ability to use automatic digital camera images (DCIs) as proxy data for gross primary production (GPP) in a complex low Arctic wetland site. Vegetation greenness computed from DCIs was found to correlate significantly (R2 = 0.62, p ... 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 (R2 = 0.85, p cameras may be used as a cost-effective proxy for potential GPP in remote Arctic regions....

  1. Advantages of using satellite soil moisture estimates over precipitation products to assess regional vegetation water availability and activity

    Science.gov (United States)

    Chen, Tiexi

    2017-04-01

    To improve the understanding of water-vegetation relationships, direct comparative studies assessing the utility of satellite remotely sensed soil moisture, gridded precipitation products, and land surface model output are needed. A case study was investigated for a water-limited, lateral inflow receiving area in northeastern Australia during December 2008 to May 2009. In January 2009, monthly precipitation showed strong positive anomalies, which led to strong positive soil moisture anomalies. The precipitation anomalies disappeared within a month. In contrast, the soil moisture anomalies persisted for months. Positive anomalies of Normalized Difference Vegetation Index (NDVI) appeared in February, in response to water supply, and then persisted for several months. In addition to these temporal characteristics, the spatial patterns of NDVI anomalies were more similar to soil moisture patterns than to those of precipitation and land surface model output. The long memory of soil moisture mainly relates to the presence of clay-rich soils. Modeled soil moisture from four of five global land surface models failed to capture the memory length of soil moisture and all five models failed to present the influence of lateral inflow. This case study indicates that satellite-based soil moisture is a better predictor of vegetation water availability than precipitation in environments having a memory of several months and thus is able to persistently affect vegetation dynamics. These results illustrate the usefulness of satellite remotely sensed soil moisture in ecohydrology studies. This case study has the potential to be used as a benchmark for global land surface model evaluations. The advantages of using satellite remotely sensed soil moisture over gridded precipitation products are mainly expected in lateral-inflow and/or clay-rich regions worldwide.

  2. Automatic Extraction of Mangrove Vegetation from Optical Satellite Data

    Science.gov (United States)

    Agrawal, Mayank; Sushma Reddy, Devireddy; Prasad, Ram Chandra

    2016-06-01

    Mangrove, the intertidal halophytic vegetation, are one of the most significant and diverse ecosystem in the world. They protect the coast from sea erosion and other natural disasters like tsunami and cyclone. In view of their increased destruction and degradation in the current scenario, mapping of this vegetation is at priority. Globally researchers mapped mangrove vegetation using visual interpretation method or digital classification approaches or a combination of both (hybrid) approaches using varied spatial and spectral data sets. In the recent past techniques have been developed to extract these coastal vegetation automatically using varied algorithms. In the current study we tried to delineate mangrove vegetation using LISS III and Landsat 8 data sets for selected locations of Andaman and Nicobar islands. Towards this we made an attempt to use segmentation method, that characterize the mangrove vegetation based on their tone and the texture and the pixel based classification method, where the mangroves are identified based on their pixel values. The results obtained from the both approaches are validated using maps available for the region selected and obtained better accuracy with respect to their delineation. The main focus of this paper is simplicity of the methods and the availability of the data on which these methods are applied as these data (Landsat) are readily available for many regions. Our methods are very flexible and can be applied on any region.

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

    Science.gov (United States)

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

    2011-02-01

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

  4. Evaluation of soil and vegetation response to drought using SMOS soil moisture satellite observations

    Science.gov (United States)

    Piles, Maria; Sánchez, Nilda; Vall-llossera, Mercè; Ballabrera, Joaquim; Martínez, Justino; Martínez-Fernández, José; Camps, Adriano; Font, Jordi

    2014-05-01

    Soil moisture plays an important role in determining the likelihood of droughts and floods that may affect an area. Knowledge of soil moisture distribution as a function of time and space is highly relevant for hydrological, ecological and agricultural applications, especially in water-limited or drought-prone regions. However, measuring soil moisture is challenging because of its high variability; point-scale in-situ measurements are scarce being remote sensing the only practical means to obtain regional- and global-scale soil moisture estimates. The ESA's Soil Moisture and Ocean Salinity (SMOS) is the first satellite mission ever designed to measuring the Earth's surface soil moisture at near daily time scales with levels of accuracy previously not attained. Since its launch in November 2009, significant efforts have been dedicated to validate and fine-tune the retrieval algorithms so that SMOS-derived soil moisture estimates meet the standards required for a wide variety of applications. In this line, the SMOS Barcelona Expert Center (BEC) is distributing daily, monthly, and annual temporal averages of 0.25-deg global soil moisture maps, which have proved useful for assessing drought and water-stress conditions. In addition, a downscaling algorithm has been developed to combine SMOS and NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) data into fine-scale (stress conditions. In previous research, SMOS-derived Soil Moisture Anomalies (SSMA), calculated in a ten-day basis, were shown to be in close relationship with well-known drought indices (the Standardized Precipitation Index and the Standardized Precipitation Evapotranspiration Index). In this work, SSMA have been calculated for the period 2010-2013 in representative arid, semi-arid, sub-humid and humid areas across global land biomes. The SSMA reflect the cumulative precipitation anomalies and is known to provide 'memory' in the climate and hydrological system; the water retained in the soil

  5. Detecting inter-annual variability in the phenological characteristics of southern Africa’s vegetation using satellite imagery

    CSIR Research Space (South Africa)

    Wessels, Konrad J

    2011-01-01

    Full Text Available Vegetation phenology refers to the timing of seasonal biological events (for example, bud burst, leaf unfolding, vegetation growth and leaf senescence) and biotic and abiotic forces that control these. Daily, coarse-resolution satellite imagery...

  6. 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.

  7. Inversion of Biochemical Parameters by Selection of Proper Vegetation Index in Winter Wheat

    Institute of Scientific and Technical Information of China (English)

    HUANG Wen-jiang; WANG Ji-hua; LIU Liang-yun; ZHAO Chun-jiang; WANG Zhi-jie; WANG Jin-di

    2004-01-01

    Recent studies have demonstrated the application of vegetation indices from canopy reflected spectrum for inversion of chlorophyll concentration.Some indices are both response to variations of vegetation and environmental factors.Canopy chlorophyll concentration,an indicator of photosynthesis activity,is related to nitrogen concentration in green vegetation and serves as an indicator of the crop response to soil nitrogen fertilizer application.The combination of normalized difference vegetation index (NDVI) and photochemical reflectance index (PRI) can reduce the effect of leaf area index (LAI) and soil background.The canopy chlorophyll inversion index (CCII) was proved to be sensitive to chlorophyll concentration and very resistant to the other variations.This paper introduced the ratio of TCARI/OSAVI to make accurate predictions of winter wheat chlorophyll concentration under different cultivars.It indicated that canopy chlorophyll concentration could be evaluated by some combined vegetation indices.

  8. Multiscale Estimation of Leaf Area Index from Satellite Observations Based on an Ensemble Multiscale Filter

    Directory of Open Access Journals (Sweden)

    Jingyi Jiang

    2016-03-01

    Full Text Available Currently, multiple leaf area index (LAI products retrieved from remote sensing data are widely used in crop growth monitoring, land-surface process simulation and studies of climate change. However, most LAI products are only retrieved from individual satellite observations, which may result in spatial-temporal discontinuities and low accuracy in these products. In this paper, a new method was developed to simultaneously retrieve multiscale LAI data from satellite observations with different spatial resolutions based on an ensemble multiscale filter (EnMsF. The LAI average values corresponding to the date of satellite observations were calculated from the multi-year Moderate Resolution Imaging Spectroradiometer (MODIS LAI product and were used as a priori knowledge for LAI in order to construct an initial ensemble multiscale tree (EnMsT. Satellite observations obtained at different spatial resolutions were then applied to update the LAI values at each node of the EnMsT using a two-sweep filtering procedure. Next, the retrieved LAI values at the finest scale were used as a priori knowledge for LAI for the new round of construction and updating of the EnMsT, until the sum of the difference of LAI values at each node of the EnMsT between two adjacent updates is less than a given threshold. The method was tested using Thematic Mapper (TM or Enhanced Thematic Mapper Plus (ETM+ surface reflectance data and MODIS surface reflectance data from five sites that have different vegetation types. The results demonstrate that the retrieved LAI values for each spatial resolution were in good agreement with the aggregated LAI reference map values for the corresponding spatial resolution. The retrieved LAI values at the coarsest scale provided better accuracy with the aggregated LAI reference map values (root mean square error (RMSE = 0.45 compared with that obtained from the MODIS LAI values (RMSE = 1.30.

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

    Science.gov (United States)

    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 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 (R (sup 2) equals 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 (R (sup 2) is greater than 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.

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

    Directory of Open Access Journals (Sweden)

    Laura Ulsig

    2017-01-01

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

  11. Demonstration on the indexes design of gravity satellite orbit parameters in the low-low satellite-to-satellite tracking mode

    Directory of Open Access Journals (Sweden)

    Liu Xiaogang

    2013-02-01

    Full Text Available Combining with the exigent demand of the development of satellite gravimetry system in China, aiming at the determination of technical indexes of gravity satellite orbit parameters, on the basis of the numerical experiments and results analysis, the design indexes of gravity satellite orbit height, inter-satellite range and the orbit inclination are analyzed and calculated, and the issues towards twin gravity satellites such as coherence requirement of the orbit semi-major axes, control requirement of the pitch angle and time interval requirement to keep twin satellites formation in mobility are discussed. Results show that the satellite orbit height is 400 km to 500 km, the inter-satellite range is about 220 km, the satellite orbit inclination is between polar orbit and sun-synchronous orbit, the semi-major axes difference of twin satellites orbit is within ±70. 146 m, the pitch angle of twin satellites is about 0.9 degree, and the time interval to keep twin satellites formation in mobility is 7 days to 15 days.

  12. Single Tree Vegetation Depth Estimation Tool for Satellite Services Link Design

    OpenAIRE

    HASIRCI, Z.; Cavdar, I. H.; Ozturk, M

    2016-01-01

    Attenuation caused by tree shadowing is an important factor for describing the propagation channel of satellite services. Thus, vegetation effects should be determined by experimental studies or empirical formulations. In this study, tree types in the Black Sea Region of Turkey are classified based on their geometrical shapes into four groups such as conic, ellipsoid, spherical and hemispherical. The variations of the vegetation depth according to different tree shapes are calculated with ...

  13. Validating a Dynamic Global Vegetation Model with Remotely Sensed Vegetation Index

    Directory of Open Access Journals (Sweden)

    Jiaxin Jin

    2013-02-01

    Full Text Available The present study aims to evaluate the ability of IBIS model to capture the difference in vegetation characteristics among six major biomes in the Northeast China Transect and to calibrate the simulated LAI by IBIS, using the product of MODIS LAI (Leaf Area Index. The results showed that IBIS simulated a little lower growing season LAI over temperate evergreen conifer forest and boreal evergreen forest, while it overestimated LAI relative to MODIS in non-growing season. IBIS performed poorly on LAI over savanna, grassland and shrub land, compared with MODIS and it nearly simulated higher LAI throughout the year. Based on regression analysis, the simulating LAI by IBIS (Integrated Biosphere Simulator presented a significant linear correlation with that from MODIS over temperate evergreen conifer forest in spring and winter, boreal evergreen forest throughout the year and grassland from summer to early autumn. Therefore, it was help to adjust the model parameters over these plant functional types to calibrate the estimated LAI in a large spatial scale.

  14. EROS MODIS Normalized Difference Vegetation Index: 2001-Present

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — eMODIS processes calibrated radiance data (level-1B) acquired by the MODIS sensors on the EOS Terra and Aqua satellites by combining MODIS Land Science Collection 5...

  15. eMODIS Normalized Difference Vegetation Index Version 6

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — eMODIS processes calibrated radiance data (level-1B) acquired by the MODIS sensors on the EOS Aqua satellite by combining MODIS Land Science Collection 6...

  16. 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

  17. Reviews and syntheses: Australian vegetation phenology: new insights from satellite remote sensing and digital repeat photography

    Science.gov (United States)

    Moore, Caitlin E.; Brown, Tim; Keenan, Trevor F.; Duursma, Remko A.; van Dijk, Albert I. J. M.; Beringer, Jason; Culvenor, Darius; Evans, Bradley; Huete, Alfredo; Hutley, Lindsay B.; Maier, Stefan; Restrepo-Coupe, Natalia; Sonnentag, Oliver; Specht, Alison; Taylor, Jeffrey R.; van Gorsel, Eva; Liddell, Michael J.

    2016-09-01

    Phenology is the study of periodic biological occurrences and can provide important insights into the influence of climatic variability and change on ecosystems. Understanding Australia's vegetation phenology is a challenge due to its diverse range of ecosystems, from savannas and tropical rainforests to temperate eucalypt woodlands, semi-arid scrublands, and alpine grasslands. These ecosystems exhibit marked differences in seasonal patterns of canopy development and plant life-cycle events, much of which deviates from the predictable seasonal phenological pulse of temperate deciduous and boreal biomes. Many Australian ecosystems are subject to irregular events (i.e. drought, flooding, cyclones, and fire) that can alter ecosystem composition, structure, and functioning just as much as seasonal change. We show how satellite remote sensing and ground-based digital repeat photography (i.e. phenocams) can be used to improve understanding of phenology in Australian ecosystems. First, we examine temporal variation in phenology on the continental scale using the enhanced vegetation index (EVI), calculated from MODerate resolution Imaging Spectroradiometer (MODIS) data. Spatial gradients are revealed, ranging from regions with pronounced seasonality in canopy development (i.e. tropical savannas) to regions where seasonal variation is minimal (i.e. tropical rainforests) or high but irregular (i.e. arid ecosystems). Next, we use time series colour information extracted from phenocam imagery to illustrate a range of phenological signals in four contrasting Australian ecosystems. These include greening and senescing events in tropical savannas and temperate eucalypt understorey, as well as strong seasonal dynamics of individual trees in a seemingly static evergreen rainforest. We also demonstrate how phenology links with ecosystem gross primary productivity (from eddy covariance) and discuss why these processes are linked in some ecosystems but not others. We conclude that

  18. Soil moisture and evapotranspiration of wetlands vegetation habitats retrieved from satellite images

    Science.gov (United States)

    Dabrowska-Zielinska, K.; Budzynska, M.; Kowalik, W.; Turlej, K.

    2010-08-01

    The research has been carried out in Biebrza Ramsar Convention test site situated in the N-E part of Poland. Data from optical and microwave satellite images have been analysed and compared to the detailed soil-vegetation ground truth measurements conducted during the satellite overpasses. Satellite data applied for the study include: ENVISAT.ASAR, ENVISAT.MERIS, ALOS.PALSAR, ALOS.AVNIR-2, ALOS.PRISM, TERRA.ASTER, and NOAA.AVHRR. Optical images have been used for classification of wetlands vegetation habitats and vegetation surface roughness expressed by LAI. Also, heat fluxes have been calculated using NOAA.AVHRR data and meteorological data. Microwave images have been used for the assessment of soil moisture. For each of the classified wetlands vegetation habitats the relationship between soil moisture and backscattering coefficient has been examined, and the best combination of microwave variables (wave length, incidence angle, polarization) has been used for mapping and monitoring of soil moisture. The results of this study give possibility to improve models of water cycle over wetlands ecosystems by adding information about soil moisture and surface heat fluxes derived from satellite images. Such information is very essential for better protection of the European sensitive wetland ecosystems. ENVISAT and ALOS images have been obtained from ESA for AO ID 122 and AOALO.3742 projects.

  19. A method for canopy water content estimation for highly vegetated surfaces-shortwave infrared perpendicular water stress index

    Institute of Scientific and Technical Information of China (English)

    GHULAM; Abduwasit; LI; Zhao-Liang; QIN; QiMing; TONG; QingXi; WANG; JiHua; KASIMU; Alimujiang; ZHU; Lin

    2007-01-01

    In this paper, a new method for canopy water content (FMC) estimation for highly vegetated surfaces- shortwave infrared perpendicular water stress index (SPSI) is developed using NIR, SWIR wavelengths of Enhanced Thematic Mapper Plus (ETM+) on the basis of spectral features and distribution of surface targets with different water conditions in NIR-SWIR spectral space. The developed method is further explored with radiative transfer simulations using PROSPECT, Lillesaeter, SailH and 6S. It is evident from the results of validation derived from satellite synchronous field measurements that SPSI is highly correlated with FMC, coefficient of determination (R squared) and root mean square error are 0.79 and 26.41%. The paper concludes that SPSI has a potential in vegetation water content estimation in terms of FMC.

  20. Modified soil adjusted vegetation index for the Death Valley regional flow system, Nevada and California

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The raster-based Modified Soil Adjusted Vegetation Index was derived from Landsat Thematic Mapper imagery data acquired during June 1992 for the Death Valley...

  1. Vegetation Index and Phenology (VIP) Phenology EVI2 Yearly Global 0.05Deg CMG

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The NASA MEaSUREs Vegetation Index and Phenology (VIP) global datasets were created using surface reflectance data from the Advanced Very High Resolution Radiometer...

  2. 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...

  3. Modified soil adjusted vegetation index of the Sarcobatus Flat area of the Death Valley

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The raster-based Modified Soil Adjusted Vegetation Index was derived from Landsat Thematic Mapper imagery data acquired during June 1989 for Sarcobatus Flat. The...

  4. Limits to detectability of land degradation by trend analysis of vegetation index data

    CSIR Research Space (South Africa)

    Wessels, Konrad J

    2012-10-01

    Full Text Available This paper demonstrates a simulation approach for testing the sensitivity of linear and non-parametric trend analysis methods applied to remotely sensed vegetation index data for the detection of land degradation. The intensity, rate and timing...

  5. Vegetation Index and Phenology (VIP) Phenology NDVI Yearly Global 0.05Deg CMG

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The NASA MEaSUREs Vegetation Index and Phenology (VIP) global datasets were created using surface reflectance data from the Advanced Very High Resolution Radiometer...

  6. Sensitivity of the Enhanced Vegetation Index (EVI and Normalized Difference Vegetation Index (NDVI to Topographic Effects: A Case Study in High-density Cypress Forest

    Directory of Open Access Journals (Sweden)

    Guoyu Qiu

    2007-11-01

    Full Text Available Vegetation indices play an important role in monitoring variations in vegetation.The Enhanced Vegetation Index (EVI proposed by the MODIS Land Discipline Groupand the Normalized Difference Vegetation Index (NDVI are both global-based vegetationindices aimed at providing consistent spatial and temporal information regarding globalvegetation. However, many environmental factors such as atmospheric conditions and soilbackground may produce errors in these indices. The topographic effect is another veryimportant factor, especially when the indices are used in areas of rough terrain. In thispaper, we theoretically analyzed differences in the topographic effect on the EVI and theNDVI based on a non-Lambertian model and two airborne-based images acquired from amountainous area covered by high-density Japanese cypress plantation were used as a casestudy. The results indicate that the soil adjustment factor “L” in the EVI makes it moresensitive to topographic conditions than is the NDVI. Based on these results, we stronglyrecommend that the topographic effect should be removed in the reflectance data beforethe EVI was calculated—as well as from other vegetation indices that similarly include a term without a band ratio format (e.g., the PVI and SAVI—when these indices are used in the area of rough terrain, where the topographic effect on the vegetation indices having only a band ratio format (e.g., the NDVI can usually be ignored.

  7. Atmospheric correction for satellite remotely sensed data intended for agricultural applications: impact on vegetation indices

    Directory of Open Access Journals (Sweden)

    D. G. Hadjimitsis

    2010-01-01

    Full Text Available Solar radiation reflected by the Earth's surface to satellite sensors is modified by its interaction with the atmosphere. The objective of applying an atmospheric correction is to determine true surface reflectance values and to retrieve physical parameters of the Earth's surface, including surface reflectance, by removing atmospheric effects from satellite images. Atmospheric correction is arguably the most important part of the pre-processing of satellite remotely sensed data. Such a correction is especially important in cases where multi-temporal images are to be compared and analyzed. For agricultural applications, in which several vegetation indices are applied for monitoring purposes, multi-temporal images are used. The integration of vegetation indices from remotely sensed images with other hydro-meteorological data is widely used for monitoring natural hazards such as droughts. Indeed, the most important task is to retrieve the true values of the vegetation status from the satellite-remotely sensed data. Any omission of considering the effects of the atmosphere when vegetation indices from satellite images are used, may lead to major discrepancies in the final outcomes. This paper highlights the importance of considering atmospheric effects when vegetation indices, such as DVI, NDVI, SAVI, MSAVI and SARVI, are used (or considered and presents the results obtained by applying the darkest-pixel atmospheric correction method on ten Landsat TM/ETM+ images of Cyprus acquired from July to December 2008. Finally, in this analysis, an attempt is made to determine evapotranspiration and to examine its dependence on the consideration of atmospheric effects when multi-temporal image data are used. It was found that, without applying any atmospheric correction, the real daily evapotranspiration was less than the one found after applying the darkest pixel atmospheric correction method.

  8. Modeling vegetation reflectance from satellite and in-situ monitoring data

    Science.gov (United States)

    Zoran, Maria; Florin Zoran, Liviu; Ionescu Golovanov, Carmen; Dida, Adrian

    2010-05-01

    Vegetation can be distinguished using remote sensing data from most other (mainly inorganic) materials by virtue of its notable absorption in the red and blue segments of the visible spectrum, its higher green reflectance and, especially, its very strong reflectance in the near-IR. Different types of vegetation show often distinctive variability from one another owing to such parameters as leaf shape and size, overall plant shape, water content, and associated background (e.g., soil types and spacing of the plants (density of vegetative cover within the scene). Different three-dimensional numerical models explicitly represent the vegetation canopy and use numerical methods to calculate reflectance. These models are computationally intensive and are therefore not generally suited to the correction of satellite imagery containing millions of pixels. Physically based models do provide understanding and are potentially more robust in extrapolation. They consider the vegetation canopy to comprise thin layers of leaves, suspended in air like sediment particles in water forming a turbid medium. Monitoring of vegetation cover changes by remote sensing data is one of the most important applications of satellite imagery. Vegetation reflectance has variations with sun zenith angle, view zenith angle, and terrain slope angle. To provide corrections of these effects, for visible and near-infrared light, was used a three parameters model and developed a simple physical model of vegetation reflectance, by assuming homogeneous and closed vegetation canopy with randomly oriented leaves. Multiple scattering theory was used to extend the model to function for both near-infrared and visible light. This vegetation reflectance model may be used to correct satellite imagery for bidirectional and topographic effects. For two ASTER images over Cernica forested area, placed to the East of Bucharest town , Romania, acquired within minutes from one another ,a nadir and off-nadir for band 3

  9. Using Small Drone (UAS) Imagery to Bridge the Gap Between Field- and Satellite-Based Measurements of Vegetation Structure and Change

    Science.gov (United States)

    Mayes, M. T.; Estes, L. D.; Gago, X.; Debats, S. R.; Caylor, K. K.; Manfreda, S.; Oudemans, P.; Ciraolo, G.; Maltese, A.; Nadal, M.; Estrany, J.

    2016-12-01

    Leaf area is an important ecosystem variable that relates to vegetation biomass, productivity, water and nutrient use in natural and agricultural systems globally. Since the 1980s, optical satellite image-based estimates of leaf area based on indices such as Normalized Difference Vegetation Index (NDVI) have greatly improved understanding of vegetation structure, function, and responses to disturbance at landscape (10^3 km2) to continental (10^6 km2) spatial scales. However, at landscape scales, satellites have failed to capture many leaf area patterns indicative of vegetation succession, crop types, stress and other conditions important for ecological processes. Small drones (UAS - unmanned aerial systems) offer new means for assessing leaf area and vegetation structure at higher spatial resolutions (changes and variability, including vegetation recovery from fire (Mallorca), and leaf-area and biomass variability due to orchard type and agro-ecosystem management (Matera, New Jersey). Finally, we highlight promising ways forward for improving field data collection and the use of UAS observations to monitor vegetation leaf-area and biomass change at landscape scales in natural and agricultural systems.

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

    Directory of Open Access Journals (Sweden)

    Samuel T. Smallidge

    2010-01-01

    Full Text Available 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.

  11. Model-simulated and Satellite-derived Leaf Area Index (LAI) Comparisons Across Multiple Spatial Scales

    Science.gov (United States)

    Iiames, J. S., Jr.; Cooter, E. J.

    2016-12-01

    Leaf Area Index (LAI) is an important parameter in assessing vegetation structure for characterizing forest canopies over large areas at broad spatial scales using satellite remote sensing data. However, satellite-derived LAI products can be limited by obstructed atmospheric conditions yielding sub-optimal values, or complete non-returns. The United States Environmental Protection Agency's Exposure Methods and Measurements and Computational Exposure Divisions are investigating the viability of supplemental modelled LAI inputs into satellite-derived data streams to support various regional and local scale air quality models for retrospective and future climate assessments. In this present study, one-year (2002) of plot level stand characteristics at four study sites located in Virginia and North Carolina (USA) are used to calibrate species-specific plant parameters in a semi-empirical biogeochemical model. The Environmental Policy Integrated Climate (EPIC) model was designed primarily for managed agricultural field crop ecosystems, but also includes managed woody species that span both xeric and mesic sites (e.g., mesquite, pine, oak, etc.). LAI was simulated using EPIC at a 4 km2 and 12 km2 grid coincident with the regional Community Multiscale Air Quality Model (CMAQ) grid. LAI comparisons were made between model-simulated and MODIS-derived LAI. Field/satellite-upscaled LAI was also compared to the corresponding MODIS LAI value. Preliminary results show field/satellite-upscaled LAI (1 km2) was 1.5 to 3 times smaller than that with the corresponding 1 km2 MODIS LAI for all four sites across all dates, with the largest discrepancies occurring at leaf-out and leaf senescence periods. Simulated LAI/MODIS LAI comparison results will be presented at the conference. Disclaimer: This work is done in support of EPA's Sustainable Healthy Communities Research Program. The U.S. Environmental Protection Agency funded and conducted the research described in this paper. Although

  12. A Normalized Difference Vegetation Index (NDVI Time-Series of Idle Agriculture Lands: A Preliminary Study

    Directory of Open Access Journals (Sweden)

    Andrew K Skidmore

    2011-01-01

    Full Text Available In this paper, the NDVI time-series collected from the study area between year 2003 and 2005 of all land cover types are plotted and compared. The study area is the agricultural zones in Banphai District, Khonkean, Thailand. The LANDSAT satellite images of different dates were first transformed into a time series of Normalized Difference Vegetation Index (NDVI images before the investigation. It can be visually observed that the NDVI time series of the Idle Agriculture Land (IAL has the NDVI values closed to zero. In other words, the trend of the NDVI values remains, approximately, unchanged about the zero level for the whole period of the study time. In contrast, the non-idle areas hold a higher level of the NDVI variation. The NDVI values above 0.5 can be found in these non-idle areas during the growing seasons. Thus, it can be hypothesized that the NDVI time-series of the different land cover types can be used for IAL classification. This outcome is a prerequisite to the follow-up study of the NDVI pattern classification that will be done in the near future.

  13. Assessing intra-annual vegetation regrowth after fire using the pixel based regeneration index

    NARCIS (Netherlands)

    Lhermitte, S.; Verbesselt, J.; Verstraeten, W.W.; Veraverbeke, S.; Coppin, P.

    2011-01-01

    Several remote sensing studies have discussed the potential of satellite imagery as an alternative for extensive field sampling to quantify fire-vegetation impact over large areas. Most studies depend on Landsat image availability with infrequent image acquisition dates and consequently are limited

  14. Satellite-Based Assessment of the spatial extent of Aquatic Vegetation in Lake Victoria

    Science.gov (United States)

    Clark, W.; Aligeti, N.; Jeyaprakash, T.; Martins, M.; Stodghill, J.; Winstanley, H.

    2011-12-01

    Lake Victoria in Africa is the second largest freshwater lake in the world and is known for its abundance of aquatic wildlife. In particular over 200 different fish species are caught and sold by local fisherman. The lake is a major contributor to the local economy as a corridor of transportation, source of drinking water, and source of hydropower. However, the invasion of aquatic vegetation such as water hyacinth in the lake has disrupted each of these markets. Aquatic vegetation now covers a substantial area of the coastline blocking waterways, disrupting hydropower, hindering the collection of drinking water and decreasing the profitability of fishing. The vegetation serves as a habitat for disease carrying mosquitoes as well as snakes and snails that spread the parasitic disease bilharzia. The current control measures of invasive aquatic vegetation rely on biological, chemical and mechanical control. The objective of this study was to utilize remote sensing to map aquatic vegetation within Lake Victoria from 2000 to 2011. MODIS, Landsat 4-5TM, and Landsat 7-ETM imagery was employed to perform change detections in vegetation and identify the extent of aquatic vegetation throughout the years. The efficiency of containment efforts were evaluated and ideal time for application of such efforts were suggested. A methodology for aquatic vegetation surveillance was created. The results of this project were presented as a workshop to the Lake Victoria Fisheries Organization, SERVIR, and other partner organizations. The workshop provided instruction into the use of NASA and other satellite derived products. Time series animations of the spatial extent of aquatic vegetation within the lake were created. By identifying seasons of decreased aquatic vegetation, ideal times to employ control efforts were identified. SERVIR will subsequently utilize the methodologies and mapping results of this study to develop operational aquatic vegetation surveillance for Lake Victoria.

  15. Mutual influence between climate and vegetation cover through satellite data in Egypt

    Science.gov (United States)

    El-Shirbeny, Mohammed A.; Aboelghar, Mohamed A.; Arafat, Sayed M.; El-Gindy, Abdel-Ghany M.

    2011-11-01

    The effect of vegetation cover on climatic change has not yet observed in Egypt. In the current study, Ismailia Governorate was selected as a case study to assess the impact of the vegetation cover expansion on both land surface and air temperature during twenty-eight years from 1983 to 2010. This observation site was carefully selected as a clear example for the highly rate of reclamation and vegetation expansion process in Egypt. Land Surface Temperature (LST) that were extracted from NOAA/AVHRR satellite data and air temperature (Tair) data that were collected from ground stations, were correlated with the expansion of vegetation cover that was delineated using Landsat TM and Landsat ETM+ data. The result showed that (LST) decreased by about 2.3°C while (Tair) decreased by about 1.6°C with the expansion of the cultivated land during twenty-eight years.

  16. Single Tree Vegetation Depth Estimation Tool for Satellite Services Link Design

    Directory of Open Access Journals (Sweden)

    Z. Hasirci

    2016-04-01

    Full Text Available Attenuation caused by tree shadowing is an important factor for describing the propagation channel of satellite services. Thus, vegetation effects should be determined by experimental studies or empirical formulations. In this study, tree types in the Black Sea Region of Turkey are classified based on their geometrical shapes into four groups such as conic, ellipsoid, spherical and hemispherical. The variations of the vegetation depth according to different tree shapes are calculated with ray tracing method. It is showed that different geometrical shapes have different vegetation depths even if they have same foliage volume for different elevation angles. The proposed method is validated with the related literature in terms of average single tree attenuation. On the other hand, due to decrease system requirements (speed, memory usage etc. of ray tracing method, an artificial neural network is proposed as an alternative. A graphical user interface is created for the above processes in MATLAB environment named vegetation depth estimation tool (VdET.

  17. Can key vegetation parameters be retrieved at the large-scale using LAI satellite products and a generic modelling approach ?

    Science.gov (United States)

    Dewaele, Helene; Calvet, Jean-Christophe; Carrer, Dominique; Laanaia, Nabil

    2016-04-01

    In the context of climate change, the need to assess and predict the impact of droughts on vegetation and water resources increases. The generic approaches permitting the modelling of continental surfaces at large-scale has progressed in recent decades towards land surface models able to couple cycles of water, energy and carbon. A major source of uncertainty in these generic models is the maximum available water content of the soil (MaxAWC) usable by plants which is constrained by the rooting depth parameter and unobservable at the large-scale. In this study, vegetation products derived from the SPOT/VEGETATION satellite data available since 1999 are used to optimize the model rooting depth over rainfed croplands and permanent grasslands at 1 km x 1 km resolution. The inter-annual variability of the Leaf Area Index (LAI) is simulated over France using the Interactions between Soil, Biosphere and Atmosphere, CO2-reactive (ISBA-A-gs) generic land surface model and a two-layer force-restore (FR-2L) soil profile scheme. The leaf nitrogen concentration directly impacts the modelled value of the maximum annual LAI. In a first step this parameter is estimated for the last 15 years by using an iterative procedure that matches the maximum values of LAI modelled by ISBA-A-gs to the highest satellite-derived LAI values. The Root Mean Square Error (RMSE) is used as a cost function to be minimized. In a second step, the model rooting depth is optimized in order to reproduce the inter-annual variability resulting from the drought impact on the vegetation. The evaluation of the retrieved soil rooting depth is achieved using the French agricultural statistics of Agreste. Retrieved leaf nitrogen concentrations are compared with values from previous studies. The preliminary results show a good potential of this approach to estimate these two vegetation parameters (leaf nitrogen concentration, MaxAWC) at the large-scale over grassland areas. Besides, a marked impact of the

  18. Introducing a rain-adjusted vegetation index (RAVI) for improvement of long-term trend analyses in vegetation dynamics

    Science.gov (United States)

    Wessollek, Christine; Karrasch, Pierre; Osunmadewa, Babatunde

    2015-10-01

    It seems to be obvious that precipitation has a major impact on greening during the rainy season in semi-arid regions. First results1 imply a strong dependence of NDVI on rainfall. Therefore it will be necessary to consider specific rainfall events besides the known ordinary annual cycle. Based on this fundamental idea, the paper will introduce the development of a rain adjusted vegetation index (RAVI). The index is based on the enhancement of the well-known normalized difference vegetation index (NDVI2) by means of TAMSAT rainfall data and includes a 3-step procedure of determining RAVI. Within the first step both time series were analysed over a period of 29 years to find best cross correlation values between TAMSAT rainfall and NDVI signal itself. The results indicate the strongest correlation for a weighted mean rainfall for a period of three months before the corresponding NDVI value. Based on these results different mathematical models (linear, logarithmic, square root, etc.) are tested to find a functional relation between the NDVI value and the 3-months rainfall period before (0.8). Finally, the resulting NDVI-Rain-Model can be used to determine a spatially individual correction factor to transform every NDVI value into an appropriate rain adjusted vegetation index (RAVI).

  19. Satellite remote sensing of rangelands in Botswana. II - NOAA AVHRR and herbaceous vegetation

    Science.gov (United States)

    Prince, S. D.; Tucker, C. J.

    1986-01-01

    The relation between the normalized difference vegetation index (NDVI) and the herbaceous vegetation in Tamasane, Shakwe, and Masama in eastern Botswana is studied using 1983-1984 AVHRR data. The procedures for Landsat MSS interpolation of ground measurements and the data processing of the AVHRR data are described. The temporal sequence AVHRR global-area coverage (GAC) composite NDVI is examined. The AVHRR GAC composite NDVI and biomass and Landsat MSS interpolations of field measurements are analyzed and compared.

  20. How can satellite imagery be used for mineral exploration in thick vegetation areas?

    Science.gov (United States)

    Hede, Arie Naftali Hawu; Koike, Katsuaki; Kashiwaya, Koki; Sakurai, Shigeki; Yamada, Ryoichi; Singer, Donald A.

    2017-02-01

    The Hokuroku district, northern Japan, is globally recognized for rich ore deposits (kuroko and vein types), which have been thoroughly explored under thick vegetation cover. This situation is ideal to evaluate the effects of ore deposits on vegetation anomalies through geobotanical remote sensing. Here we present novel methods to detect vegetation anomalies caused by ore deposits and verify their usefulness by comparing the anomalies with a deposit potential map produced from multiple geological data. We use the reflectance spectra of Landsat ETM+ images acquired in summer and autumn to calculate a vegetation index for plant physiological activity. A key variable to detect the anomalies is a variation of vegetation index with time at each pixel. Difference in variation is enlarged by a sequence of image enhancement methods for the detection. We find that the vegetation anomalies, defined by the large ratios, correspond well to the high potential zones of ore deposits and known major deposits. Consequently, our methods can extend the applicability of remote sensing-based mineral exploration to the areas covered by thick vegetation, in addition to traditional arid and semiarid areas.

  1. Spatio-temporal multi-modality ontology for indexing and retrieving satellite images

    OpenAIRE

    MESSOUDI, Wassim; FARAH, Imed Riadh; SAHEB ETTABAA, Karim; Ben Ghezala, Henda; SOLAIMAN, Basel

    2009-01-01

    International audience; This paper presents spatio-temporal multi-modality ontology for indexing and retrieving satellite images in the high level to improve the quality of the system retrieval and to perform semantic in the retrieval process.Our approach is based on three modules: (1) regions and features extraction, (2) ontological indexing and (3) semantic image retrieval. The first module allows extracting regions from the satellite image using the fuzzy c-means FCM) segmentation algorith...

  2. Use of satellite imagery to identify vegetation cover changes following the Waldo Canyon Fire event, Colorado, 2012-2013

    Science.gov (United States)

    Cole, Christopher J.; Friesen, Beverly A.; Wilson, Earl M.

    2014-01-01

    The Waldo Canyon Fire of 2012 was one of the most destructive wildfire events in Colorado history. The fire burned a total of 18,247 acres, claimed 2 lives, and destroyed 347 homes. The Waldo Canyon Fire continues to pose challenges to nearby communities. In a preliminary emergency assessment conducted in 2012, the U.S. Geological Survey (USGS) concluded that drainage basins within and near the area affected by the Waldo Canyon Fire pose a risk for future debris flow events. Rainfall over burned, formerly vegetated surfaces resulted in multiple flood and debris flow events that affected the cities of Colorado Springs and Manitou Springs in 2013. One fatality resulted from a mudslide near Manitou Springs in August 2013. Federal, State, and local governments continue to monitor these hazards and other post-fire effects, along with the region’s ecological recovery. At the request of the Colorado Springs Office of Emergency Management, the USGS Special Applications Science Center developed a geospatial product to identify vegetation cover changes following the 2012 Waldo Canyon Fire event. Vegetation cover was derived from July 2012 WorldView-2 and September 2013 QuickBird multispectral imagery at a spatial resolution of two meters. The 2012 image was collected after the fire had reached its maximum extent. Per-pixel increases and decreases in vegetation cover were identified by measuring spectral changes that occurred between the 2012 and 2013 image dates. A Normalized Difference Vegetation Index (NDVI), and Green-Near Infrared Index (GRNIR) were computed from each image. These spectral indices are commonly used to characterize vegetation cover and health condition, due to their sensitivity to detect foliar chlorophyll content. Vector polygons identifying surface-cover feature boundaries were derived from the 2013 imagery using image segmentation software. This geographic software groups similar image pixels into vector objects based upon their spatial and spectral

  3. How Universal Is the Relationship between Remotely Sensed Vegetation Indices and Crop Leaf Area Index? A Global Assessment

    Directory of Open Access Journals (Sweden)

    Yanghui Kang

    2016-07-01

    Full Text Available Leaf Area Index (LAI is a key variable that bridges remote sensing observations to the quantification of agroecosystem processes. In this study, we assessed the universality of the relationships between crop LAI and remotely sensed Vegetation Indices (VIs. We first compiled a global dataset of 1459 in situ quality-controlled crop LAI measurements and collected Landsat satellite images to derive five different VIs including Simple Ratio (SR, Normalized Difference Vegetation Index (NDVI, two versions of the Enhanced Vegetation Index (EVI and EVI2, and Green Chlorophyll Index (CIGreen. Based on this dataset, we developed global LAI-VI relationships for each crop type and VI using symbolic regression and Theil-Sen (TS robust estimator. Results suggest that the global LAI-VI relationships are statistically significant, crop-specific, and mostly non-linear. These relationships explain more than half of the total variance in ground LAI observations (R2 > 0.5, and provide LAI estimates with RMSE below 1.2 m2/m2. Among the five VIs, EVI/EVI2 are the most effective, and the crop-specific LAI-EVI and LAI-EVI2 relationships constructed by TS, are robust when tested by three independent validation datasets of varied spatial scales. While the heterogeneity of agricultural landscapes leads to a diverse set of local LAI-VI relationships, the relationships provided here represent global universality on an average basis, allowing the generation of large-scale spatial-explicit LAI maps. This study contributes to the operationalization of large-area crop modeling and, by extension, has relevance to both fundamental and applied agroecosystem research.

  4. 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.

  5. [Evaluating the utility of MODIS vegetation index for monitoring agricultural drought].

    Science.gov (United States)

    Li, Hua-Peng; Zhang, Shu-Qing; Gao, Zi-Qiang; Sun, Yan

    2013-03-01

    The exclusive shortwave bands provided by MODIS sensors offer new opportunities for agricultural drought monitoring, since they are very sensitive to vegetation moisture. In the present work, we selected Songnen Plain in Northeast China as study area aiming at monitoring agricultural drought of dry farmland here. Four types of vegetation water indices and vegetation greenness indices were calculated from the 8-day composite MODIS product (MODO9A1) in vegetation growing season between 2001 and 2010, respectively. Multi-scale standardized precipitation index (SPI) derived from precipitation data of weather stations was used as reference data to estimate drought sensitivity of various vegetation indices, and a pixel-to-weather station paired correlation approach was used to calculate the Pearson correlation coefficient between vegetation index and SPIs. The result indicated that vegetation water indices established by near infrared and shortwave infrared bands outperformed vegetation greenness indices based on visible and near infrared bands. Of these indices, NDII7 performs the best with highest correlation coefficients across all SPIs. The authors' results demonstrated the potential of MODIS shortwave spectral bands in monitoring agricultural drought, and this provides new insights to future research.

  6. Evaluation of vegetation post-fire resilience in the Alpine region using descriptors derived from MODIS spectral index time series

    Science.gov (United States)

    Di Mauro, Biagio; Fava, Francesco; Busetto, Lorenzo; Crosta, Giovanni Franco; Colombo, Roberto

    2013-04-01

    In this study a method based on the analysis of MODerate-resolution Imaging Spectroradiometer (MODIS) time series is proposed to estimate the post-fire resilience of mountain vegetation (broadleaf forest and prairies) in the Italian Alps. Resilience is defined herewith as the ability of a dynamical system to counteract disturbances. It can be quantified by the amount of time the disturbed system takes to resume, in statistical terms, an ecological functionality comparable with its undisturbed behavior. Satellite images of the Normalized Difference Vegetation Index (NDVI) and of the Enhanced Vegetation Index (EVI) with spatial resolution of 250m and temporal resolution of 16 days in the 2000-2012 time period were used. Wildfire affected areas in the Lombardy region between the years 2000 and 2010 were analysed. Only large fires (affected area >40ha) were selected. For each burned area, an undisturbed adjacent control site was located. Data pre-processing consisted in the smoothing of MODIS time series for noise removal and then a double logistic function was fitted. Land surface phenology descriptors (proxies for growing season start/end/length and green biomass) were extracted in order to characterize the time evolution of the vegetation. Descriptors from a burned area were compared to those extracted from the respective control site by means of the one-way analysis of variance. According to the number of subsequent years which exhibit statistically meaningful difference between burned and control site, five classes of resilience were identified and a set of thematic maps was created for each descriptor. The same method was applied to all 84 aggregated events and to events aggregated by main land cover. EVI index results more sensitive to fire impact than NDVI index. Analysis shows that fire causes both a reduction of the biomass and a variation in the phenology of the Alpine vegetation. Results suggest an average ecosystem resilience of 6-7 years. Moreover

  7. Vegetation mapping with satellite data of the Forsmark and Tierp regions

    Energy Technology Data Exchange (ETDEWEB)

    Boresjoe-Bronge, Laine; Wester, Kjell [SwedPower, Stockholm (Sweden)

    2002-04-01

    SKB (Swedish Nuclear Fuel and Waste Management Co) performs a siting program for deep repository of spent nuclear fuel that includes survey of three potential sites. The SKB siting process has now reached the site investigation phase. There are several fields of investigations performed in this phase. One of them is description of the surface ecosystems. The surface ecosystems are mapped both on a regional (50-100 km{sup 2} ) and a local level (1 km{sup 2} ). Two inventory methods are used, remote sensing (satellite data/aerial photographs) for the regional level, and field inventory for the detailed level. As a part of the surface ecosystem characterisation on the regional level vegetation mapping using satellite data has been performed over the three potential deep depository sites, Forsmark, Tierp and Oskarshamn. The user requirements for the vegetation mapping of the potential sites are the following: Dominated species in the tree layer, shrub layer, field layer and ground layer shall be described both on regional and local level; Dominated species in all layers shall be quantified regarding share and percentage of ground cover, or absence of cover (vegetation free ground); The regional and the local inventory shall have identical or comparable classification systems; The classification system and the method used shall make it possible to scale the results from local to regional level and vice versa; The produced layers shall be presented in digital form and make it possible to model biomass and turnover of organic matter (carbon, nutrients, water); The produced information shall in a first phase be of use for planning and for making nature and environmental considerations. Data sources used in the study include geo-referenced SPOT4 XI data (20 m ground resolution), geo-referenced Landsat TM data (30 m ground resolution), soil type data, topographic map data and colour infrared aerial photographs. The production of vegetation layers has been carried out in two

  8. Climate Change Impacts and Vulnerabilities Assessment on Forest Vegetation Through Time-Series Multisensor Satellite Data

    Science.gov (United States)

    Zoran, Maria; Savastru, Dan; Dida, Adrian

    2016-08-01

    Sustaining forest resources in Romania requires a better understanding of forest ecosystem processes, and how management decisions and climate and anthropogenic change may affect these processes in the future. Spatio- temporal forest vegetation dynamics have been quantified as the total amount of vegetation (mean NDVI) and the seasonal difference (annual NDVI amplitude) by a time series analysis of NDVI LAI satellite images over 2000 - 2015 period for a forest ecosystem placed in the North-Eastern part of Bucharest town, Romania, from MODIS Terra/Aqua, LANDSAT TM/ETM and Sentinel satellite and meteorological data. For investigated test area, considerable NDVI decline was observed for drought events during 2003, 2007 and 2010 years. Under stress conditions, it is evident that environmental factors such as soil type, parent material, and topography are not correlated with NDVI dynamics. EO-based estimates of forest biophysical variables were shown to be similar to predictions derived from forest field inventories.

  9. 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...

  10. Mapping Arctic Tundra Vegetation Communities Using Field Spectroscopy and Multispectral Satellite Data in North Alaska, USA

    Directory of Open Access Journals (Sweden)

    Scott J. Davidson

    2016-11-01

    Full Text Available The Arctic is currently undergoing intense changes in climate; vegetation composition and productivity are expected to respond to such changes. To understand the impacts of climate change on the function of Arctic tundra ecosystems within the global carbon cycle, it is crucial to improve the understanding of vegetation distribution and heterogeneity at multiple scales. Information detailing the fine-scale spatial distribution of tundra communities provided by high resolution vegetation mapping, is needed to understand the relative contributions of and relationships between single vegetation community measurements of greenhouse gas fluxes (e.g., ~1 m chamber flux and those encompassing multiple vegetation communities (e.g., ~300 m eddy covariance measurements. The objectives of this study were: (1 to determine whether dominant Arctic tundra vegetation communities found in different locations are spectrally distinct and distinguishable using field spectroscopy methods; and (2 to test which combination of raw reflectance and vegetation indices retrieved from field and satellite data resulted in accurate vegetation maps and whether these were transferable across locations to develop a systematic method to map dominant vegetation communities within larger eddy covariance tower footprints distributed along a 300 km transect in northern Alaska. We showed vegetation community separability primarily in the 450–510 nm, 630–690 nm and 705–745 nm regions of the spectrum with the field spectroscopy data. This is line with the different traits of these arctic tundra communities, with the drier, often non-vascular plant dominated communities having much higher reflectance in the 450–510 nm and 630–690 nm regions due to the lack of photosynthetic material, whereas the low reflectance values of the vascular plant dominated communities highlight the strong light absorption found here. High classification accuracies of 92% to 96% were achieved using

  11. Vegetation Cover Change in the Upper Kings River Basin of the Sierra Nevada Detected Using Landsat Satellite Image Analysis

    Science.gov (United States)

    Potter, Christopher S.

    2015-01-01

    The Sierra Nevada of California is a region where large wildfires have been suppressed for over a century. A detailed geographic record of recent changes in vegetation cover across the Sierra Nevada remains a gap that can be filled with satellite remote sensing data. Results from Landsat image analysis over the past 25 years in the Upper Kings River basin showed that consistent, significant increases in the normalized difference vegetation index (NDVI) have not extended above 2000 m elevation, where cold temperatures presumably limit the growing season. Moreover, mean increases in NDVI since 1986 at elevations below 2000 m (which cover about half of the total basin area) have not exceeded 9%, even in the most extreme precipitation yearly comparisons. NDVI has decreased significantly at elevations above 2000 m throughout the basin in relatively wet year comparisons since the mid-1980s. These findings conflict with any assumptions that ET fluxes and river flows downstream could have been markedly altered by vegetation change over most of the Upper Kings River basin in recent decades.

  12. Satellite-observed changes in vegetation sensitivities to surface soil moisture and total water storage variations since the 2011 Texas drought

    Science.gov (United States)

    A, Geruo; Velicogna, Isabella; Kimball, John S.; Du, Jinyang; Kim, Youngwook; Colliander, Andreas; Njoku, Eni

    2017-05-01

    We combine soil moisture (SM) data from AMSR-E and AMSR-2, and changes in terrestrial water storage (TWS) from time-variable gravity data from GRACE to delineate and characterize the evolution of drought and its impact on vegetation growth. GRACE-derived TWS provides spatially continuous observations of changes in overall water supply and regional drought extent, persistence and severity, while satellite-derived SM provides enhanced delineation of shallow-depth soil water supply. Together these data provide complementary metrics quantifying available plant water supply. We use these data to investigate the supply changes from water components at different depths in relation to satellite-based enhanced vegetation index (EVI) and gross primary productivity (GPP) from MODIS and solar-induced fluorescence (SIF) from GOME-2, during and following major drought events observed in the state of Texas, USA and its surrounding semiarid area for the past decade. We find that in normal years the spatial pattern of the vegetation-moisture relationship follows the gradient in mean annual precipitation. However since the 2011 hydrological drought, vegetation growth shows enhanced sensitivity to surface SM variations in the grassland area located in central Texas, implying that the grassland, although susceptible to drought, has the capacity for a speedy recovery. Vegetation dependency on TWS weakens in the shrub-dominated west and strengthens in the grassland and forest area spanning from central to eastern Texas, consistent with changes in water supply pattern. We find that in normal years GRACE TWS shows strong coupling and similar characteristic time scale to surface SM, while in drier years GRACE TWS manifests stronger persistence, implying longer recovery time and prolonged water supply constraint on vegetation growth. The synergistic combination of GRACE TWS and surface SM, along with remote-sensing vegetation observations provides new insights into drought impact on

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

    OpenAIRE

    Timothy J. Fullman; Erin L. Bunting

    2014-01-01

    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 as...

  14. An Optical Sensor Network for Vegetation Phenology Monitoring and Satellite Data Calibration

    Directory of Open Access Journals (Sweden)

    Michal Heliasz

    2011-08-01

    Full Text Available We present a network of sites across Fennoscandia for optical sampling of vegetation properties relevant for phenology monitoring and satellite data calibration. The network currently consists of five sites, distributed along an N-S gradient through Sweden and Finland. Two sites are located in coniferous forests, one in a deciduous forest, and two on peatland. The instrumentation consists of dual-beam sensors measuring incoming and reflected red, green, NIR, and PAR fluxes at 10-min intervals, year-round. The sensors are mounted on separate masts or in flux towers in order to capture radiation reflected from within the flux footprint of current eddy covariance measurements. Our computations and model simulations demonstrate the validity of using off-nadir sampling, and we show the results from the first year of measurement. NDVI is computed and compared to that of the MODIS instrument on-board Aqua and Terra satellite platforms. PAR fluxes are partitioned into reflected and absorbed components for the ground and canopy. The measurements demonstrate that the instrumentation provides detailed information about the vegetation phenology and variations in reflectance due to snow cover variations and vegetation development. Valuable information about PAR absorption of ground and canopy is obtained that may be linked to vegetation productivity.

  15. An optical sensor network for vegetation phenology monitoring and satellite data calibration.

    Science.gov (United States)

    Eklundh, Lars; Jin, Hongxiao; Schubert, Per; Guzinski, Radoslaw; Heliasz, Michal

    2011-01-01

    We present a network of sites across Fennoscandia for optical sampling of vegetation properties relevant for phenology monitoring and satellite data calibration. The network currently consists of five sites, distributed along an N-S gradient through Sweden and Finland. Two sites are located in coniferous forests, one in a deciduous forest, and two on peatland. The instrumentation consists of dual-beam sensors measuring incoming and reflected red, green, NIR, and PAR fluxes at 10-min intervals, year-round. The sensors are mounted on separate masts or in flux towers in order to capture radiation reflected from within the flux footprint of current eddy covariance measurements. Our computations and model simulations demonstrate the validity of using off-nadir sampling, and we show the results from the first year of measurement. NDVI is computed and compared to that of the MODIS instrument on-board Aqua and Terra satellite platforms. PAR fluxes are partitioned into reflected and absorbed components for the ground and canopy. The measurements demonstrate that the instrumentation provides detailed information about the vegetation phenology and variations in reflectance due to snow cover variations and vegetation development. Valuable information about PAR absorption of ground and canopy is obtained that may be linked to vegetation productivity.

  16. Nutritional yield: a proposed index for fresh food improvement illustrated with leafy vegetable data.

    Science.gov (United States)

    Bumgarner, Natalie R; Scheerens, Joseph C; Kleinhenz, Matthew D

    2012-09-01

    Consumer interest in food products, including fresh vegetables, with health promoting properties is rising. In fresh vegetables, these properties include vitamins, minerals, dietary fiber, and secondary compounds, which collectively impart a large portion of the dietary, nutritional or health value associated with vegetable intake. Many, including farmers, aim to increase the health-promoting properties of fresh vegetables on the whole but they face at least three obstacles. First, describing crop composition in terms of its nutrition-based impact on human health is complex and there are few, if any, accepted processes and associated metrics for assessing and managing vegetable composition on-farm, at the origin of supply. Second, data suggest that primary and secondary metabolism can be 'in conflict' when establishing the abundance versus composition of a crop. Third, fresh vegetable farmers are rarely compensated for the phytochemical composition of their product. The development and implementation of a fresh vegetable 'nutritional yield' index could be instrumental in overcoming these obstacles. Nutritional yield is a function of crop biomass and tissue levels of health-related metabolites, including bioavailable antioxidant potential. Data from a multi-factor study of leaf lettuce primary and secondary metabolism and the literature suggest that antioxidant yield is sensitive to genetic and environmental production factors, and that changes in crop production and valuation will be required for fresh vegetable production systems to become more focused and purposeful instruments of public health.

  17. 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.

  18. Classification of mangroves vegetation species using texture analysis on Rapideye satellite imagery

    Science.gov (United States)

    Roslani, M. A.; Mustapha, M. A.; Lihan, T.; Juliana, W. A. Wan

    2013-11-01

    Mangroves are unique ecosystem structures that are typically made up of salt tolerant species of vegetation that can be found in tropical and subtropical climate country. Mangrove ecosystem plays important role and also is known as highly productive ecosystem with high diversity of flora and fauna. However, these ecosystems have been declining over time due to the various kinds of direct and indirect pressures. Thus, there is an increasing need to monitor and assess this ecosystem for better conservation and management efforts. The multispectral RapidEye satellite image was used to identify the mangrove vegetation species within the Matang Mangrove Forest Reserve in Perak, Malaysia using texture analysis. Classification was implemented using the maximum likelihood classifier (MLC) method. Total of eleven main mangrove species were found in the satellite image of the study site which includes Rhizophora mucronata, Rhizophora apiculata, Bruguiera parviflora, Bruguiera cylindrica, Bruguiera gymnorrhiza, Avicennia alba, Avicennia officinalis, Sonneratia alba, Sonneratia caseolaris, Sonneratia ovata and Xylocarpus granatum. The classification results showed that the textured image produced high overall classification assessment recorded at 84% and kappa statistic of 0.8016. Meanwhile, the non-textured image produces 80% of overall accuracy and kappa statistic of 0.7061. The classification result indicated the capability of high resolution satellite image to classify the mangrove species and inclusion of texture information in the classification increased the classification accuracy.

  19. Influence of solar zenith angle on the enhanced vegetation index of a Guyanese rainforest

    NARCIS (Netherlands)

    Brede, B.; Suomalainen, J.M.; Bartholomeus, H.M.; Herold, M.

    2015-01-01

    In this study, the effect of solar zenith angle () on enhanced vegetation index (EVI) of a Guyanese tropical rainforest was studied. For this sub-crown resolution, hyperspectral data have been collected with an unmanned aerial vehicle (UAV) at five different solar zenith angles in a 1-day period. Th

  20. Satellite-based forest monitoring: spatial and temporal forecast of growing index and short-wave infrared band.

    Science.gov (United States)

    Bayr, Caroline; Gallaun, Heinz; Kleb, Ulrike; Kornberger, Birgit; Steinegger, Martin; Winter, Martin

    2016-04-18

    For detecting anomalies or interventions in the field of forest monitoring we propose an approach based on the spatial and temporal forecast of satellite time series data. For each pixel of the satellite image three different types of forecasts are provided, namely spatial, temporal and combined spatio-temporal forecast. Spatial forecast means that a clustering algorithm is used to group the time series data based on the features normalised difference vegetation index (NDVI) and the short-wave infrared band (SWIR). For estimation of the typical temporal trajectory of the NDVI and SWIR during the vegetation period of each spatial cluster, we apply several methods of functional data analysis including functional principal component analysis, and a novel form of random regression forests with online learning (streaming) capability. The temporal forecast is carried out by means of functional time series analysis and an autoregressive integrated moving average model. The combination of the temporal forecasts, which is based on the past of the considered pixel, and spatial forecasts, which is based on highly correlated pixels within one cluster and their past, is performed by functional data analysis, and a variant of random regression forests adapted to online learning capabilities. For evaluation of the methods, the approaches are applied to a study area in Germany for monitoring forest damages caused by wind-storm, and to a study area in Spain for monitoring forest fires.

  1. On the terminology of the spectral vegetation index (NIR – SWIR)/(NIR + SWIR)

    Science.gov (United States)

    Ji, Lel; Zhang, Li; Wylie, Bruce K.; Rover, Jennifer R.

    2011-01-01

    The spectral vegetation index (ρNIR – ρSWIR)/(ρNIR + ρSWIR), where ρNIR and ρSWIR are the near-infrared (NIR) and shortwave-infrared (SWIR) reflectances, respectively, has been widely used to indicate vegetation moisture condition. This index has multiple names in the literature, including infrared index (II), normalized difference infrared index (NDII), normalized difference water index (NDWI), normalized difference moisture index (NDMI), land surface water index (LSWI), and normalized burn ratio (NBR), etc. After reviewing each term’s definition, associated sensors, and channel specifications, we found that the index consists of three variants, differing only in the SWIR region (1.2–1.3 µm, 1.55–1.75 µm, or 2.05–2.45 µm). Thus, three terms are sufficient to represent these three SWIR variants; other names are redundant and therefore unnecessary. Considering the spectral representativeness, the term’s popularity, and the “rule of priority” in scientific nomenclature, NDWI, NDII, and NBR, each corresponding to the three SWIR regions, are more preferable terms.

  2. 洞庭湖植被对降水的响应%Analysis of vegetation response to rainfall with satellite images in Dongting Lake

    Institute of Scientific and Technical Information of China (English)

    蒋卫国; 侯鹏; 朱晓华; 曹广真; 刘小曼; 曹入尹

    2011-01-01

    We analyzed the Normalized Difference Vegetation Index (NDVI) from satellite images and precipitation data from meteorological stations from 1998 to 2007 in the Dongting Lake wetland watershed to better understand the eco-hydrological effect of atmospheric precipitation and its relationship with vegetation. First, we analyzed its general spatio-temporal distribution using its mean, standard deviation and linear trend. Then, we used the Empirical Orthogonal Functions (EOF) method to decompose the NDVI and precipitation data into spatial and temporal modes. We selected four leading modes based on North and Scree test rules and analyzed the synchronous seasonal and inter-annual variability between the vegetation index and precipitation, distinguishing time-lagged correlations between EOF modes with the correlative degree analysis method. According to our detailed analyses, the vegetation index and precipitation exhibit a prominent correlation in spatial distribution and seasonal variation. At the 90% confidence level, the time lag is around 110 to 140 days,which matches well with the seasonal variation.

  3. NDVI (Normalized Difference Vegetation Index) signatures of transient ecohydrological systems: The case of post-mining landscapes

    Science.gov (United States)

    Brück, Yasemine; Schulte Overberg, Philipp; Pohle, Ina; Hinz, Christoph

    2017-04-01

    Assessing ecohydrological systems that undergo state transitions due to environmental change is becoming increasingly important. One system that can be used to study severe disturbances are post-mining landscapes as they usually are associated with complete removal of vegetation and afterwards subsequent ecosystem restoration or spontaneous rehabilitation in line with natural succession. Within this context it is of interest, whether and how (fast) the land cover in these areas returns to conditions comparable to those in the undisturbed surrounding or those prior mining. Many aspects of mine site rehabilitation depend on climatic, geomorphic and ecological settings, which determine at which rate vegetation may be re-established. In order to identify general patterns of vegetation establishment, we propose to use NDVI (Normalized Difference Vegetation Index) time series for mine affected land to estimate rate of recovery across climate regions and ecoregions. In this study we analysed the MODIS Terra Satellite 8 day-composite NDVI for areas influenced by surface mining in different climates from 2001 to 2015. The locations have been chosen based on their extent and the data availability of mining and rehabilitation activities. We selected coal extraction as a case study as strip mining generates well-defined chronosequences of disturbance. The selected mining areas are located in equatorial, arid, warm temperate or snow climates with different precipitation and temperature conditions according to the Köppen-Geiger classification. We analysed the NDVI time series regarding significant characteristics of the re-vegetation phase. We applied hierarchical cluster analysis to capture the spatial heterogeneity between different pixels (ca. 250 * 250 m2 each) in and around each open cast mine. We disentangled seasonality, trend and residual components in the NDVI time series by Seasonal and Trend decomposition using LOESS. As expected the time of the removal of vegetation

  4. Toward the Estimation of Surface Soil Moisture Content Using Geostationary Satellite Data over Sparsely Vegetated Area

    Directory of Open Access Journals (Sweden)

    Pei Leng

    2015-04-01

    Full Text Available Based on a novel bare surface soil moisture (SSM retrieval model developed from the synergistic use of the diurnal cycles of land surface temperature (LST and net surface shortwave radiation (NSSR (Leng et al. 2014. “Bare Surface Soil Moisture Retrieval from the Synergistic Use of Optical and Thermal Infrared Data”. International Journal of Remote Sensing 35: 988–1003., this paper mainly investigated the model’s capability to estimate SSM using geostationary satellite observations over vegetated area. Results from the simulated data primarily indicated that the previous bare SSM retrieval model is capable of estimating SSM in the low vegetation cover condition with fractional vegetation cover (FVC ranging from 0 to 0.3. In total, the simulated data from the Common Land Model (CoLM on 151 cloud-free days at three FLUXNET sites that with different climate patterns were used to describe SSM estimates with different underlying surfaces. The results showed a strong correlation between the estimated SSM and the simulated values, with a mean Root Mean Square Error (RMSE of 0.028 m3·m−3 and a coefficient of determination (R2 of 0.869. Moreover, diurnal cycles of LST and NSSR derived from the Meteosat Second Generation (MSG satellite data on 59 cloud-free days were utilized to estimate SSM in the REMEDHUS soil moisture network (Spain. In particular, determination of the model coefficients synchronously using satellite observations and SSM measurements was explored in detail in the cases where meteorological data were not available. A preliminary validation was implemented to verify the MSG pixel average SSM in the REMEDHUS area with the average SSM calculated from the site measurements. The results revealed a significant R2 of 0.595 and an RMSE of 0.021 m3·m−3.

  5. Impacts of Snow Cover on Vegetation Phenology in the Arctic from Satellite Data

    Institute of Scientific and Technical Information of China (English)

    ZENG Heqing; JIA Gensuo

    2013-01-01

    The dynamics of snow cover is considered an essential factor in phenological changes in Arctic tundra and other northern biomes.The Moderate Resolution Imaging Spectroradiometer (MODIS)/Terra satellite data were selected to monitor the spatial and temporal heterogeneity of vegetation phenology and the timing of snow cover in western Arctic Russia (the Yamal Peninsula) during the period 2000-10.The magnitude of changes in vegetation phenology and the timing of snow cover were highly heterogeneous across latitudinal gradients and vegetation types in western Arctic Russia.There were identical latitudinal gradients for "start of season" (SOS) (r2 =0.982,p<0.0001),"end of season" (EOS) (r2 =0.938,p<0.0001),and "last day of snow cover" (LSC) (r2 =0.984,p<0.0001),while slightly weaker relationships between latitudinal gradients and "first day of snow cover" (FSC) were observed (r2 =0.48,p<0.0042).Delayed SOS and FSC,and advanced EOS and LSC were found in the south of the region,while there were completely different shifts in the north.SOS for the various land cover features responded to snow cover differently,while EOS among different vegetation types responded to snowfall almost the same.The timing of snow cover is likely a key driving factor behind the dynamics of vegetation phenology over the Arctic tundra.The present study suggests that snow cover urgently needs more attention to advance understanding of vegetation phenology in the future.

  6. 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).

  7. 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

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

    Science.gov (United States)

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

    2016-09-01

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

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

    DEFF Research Database (Denmark)

    Olsen, Jørgen Lundegaard

    index (NDVI), which combines red and near infrared (NIR) spectral regions. From NDVI data a greening of the Sahel have been identified since the 80s and attributed to increasing trends in annual rainfall for large parts of the region. One part of this thesis analyses time series of parameterized MODIS...... that the varying NPP/NDVI relationships, combined with the large increase in livestock of the Sahel in recent decades, means that the greening of the Sahel cannot uncritically be interpreted as a positive trend in vegetation productivity due to increasing rainfall. It can also represent grazing induced changes...... in species composition which covers neutral or even decreasing trends in biomass production. For monitoring vegetation status on a shorter time scale in the Sahel, the NDVI may not be the most appropriate index. From previous research it has been suggested that the Shortwave infrared (SWIR) spectral region...

  10. Assessment of agricultural drought in Rajasthan (India using remote sensing derived Vegetation Condition Index (VCI and Standardized Precipitation Index (SPI

    Directory of Open Access Journals (Sweden)

    Dipanwita Dutta

    2015-06-01

    Full Text Available Owing to its severe effect on productivity of rain-fed crops and indirect effect on employment as well as per capita income, agricultural drought has become a prime concern worldwide. The occurrence of drought is mainly a climatic phenomenon which cannot be eliminated. However, its effects can be reduced if actual spatio-temporal information related to crop status is available to the decision makers. The present study attempts to assess the efficiency of remote sensing and GIS techniques for monitoring the spatio-temporal extent of agricultural drought. In the present study, NOAA-AVHRR NDVI data were used for monitoring agricultural drought through NDVI based Vegetation Condition Index. VCI was calculated for whole Rajasthan using the long term NDVI images which reveals the occurrence of drought related crop stress during the year 2002. The VCI values of normal (2003 and drought (2002 year were compared with meteorological based Standardized Precipitation Index (SPI, Rainfall Anomaly Index and Yield Anomaly Index and a good agreement was found among them. The correlation coefficient between VCI and yield of major rain-fed crops (r > 0.75 also supports the efficiency of this remote sensing derived index for assessing agricultural drought.

  11. Spatio-temporal features of vegetation restoration and variation after the Wenchuan earthquake with satellite images

    Science.gov (United States)

    Peng, Hou; Qiao, Wang; Yipeng, Yang; Weiguo, Jiang; Bingfeng, Yang; Qiang, Chen; Lihua, Yuan; Fanming, Kong; Xi, Chen; Guanjie, Wang

    2014-01-01

    The Wenchuan earthquake was a deadly earthquake that occurred on May 12, 2008, in Sichuan province of China. With the help of classic statistic methods, including arithmetic mean, standard deviation and linear trend estimation, vegetation restoration was recognized by analyzing spatio-temporal features of normalized difference vegetation index (NDVI) before and after this earthquake. Results indicate: (1) spatial distribution of NDVI mean values remains similar from 1998 to 2011. Higher values are mainly found in north, whereas lower values are mainly distributed over southeast, which is in good correlation with elevation and landform. Vegetation damage is at different levels in different seismic intensity (SI) regions: the higher SI is, the worse vegetation damage is. (2) Over the whole region, standard deviation is bigger after earthquake than before. Both absolute and relative changes in ecosystem stability increase with increasing SI. In different counties, variation of ecosystem stability is more obvious after earthquake, increase of standard deviation is approximately 6.5 times. Relatively, vegetation regionalization is the smallest analysis unit. Consequently, changes resulting from earthquake are unobvious. (3) Linear trend estimation coefficient increases from 0.0079 before the earthquake to 0.0359 after the earthquake in this whole region. This indicates that the plant ecosystem is rapidly restored between 2009 and 2011. The biggest linear trend is for the hill region, indicating good plant restoration and increase after earthquake. Fluctuation of linear trend estimation coefficient in different counties is more obvious after earthquake. Vegetation restoration after earthquake is most obvious in the regions that suffered the greatest SI (SI10 and SI11). In contrast, fluctuation in linear trend estimation coefficient of annual NDVI mean value for different classes of vegetation is more obvious before earthquake.

  12. [Construction of vegetation shadow index (SVI) and application effects in four remote sensing images].

    Science.gov (United States)

    Xu, Zhang-Hua; Liu, Jian; Yu, Kun-Yong; Liu, Tao; Gong, Cong-Hong; Tang, Meng-Ya; Xie, Wan-Jun; Li, Zeng-Lu

    2013-12-01

    Taking the images of Landsat TM, ALOS AVNIR-2, CBERS-02B CCD and HJ-1 CCD as the experimental data, for increasing the differences among shaded area, bright area and water further, the present paper construed a novel vegetation index-Shaded Vegetation Index(SVI), which can not only keep the absolute differences among bright area, shaded area and water area in the near-infrared band, but also can enlarge NDVI, eliminate the possible mixes, and change the histogram "skewed" phenomenon of NDVI, so the vegetation index value is closer to normal distribution, and more in line with the filed condition; this new index was applied to the surface features of large difference of the near-infrared radiation characteristics. Verified by accuracy assessment for the bright area, shaded area and water area recognition effects with SVI, it was showed that the overall classification accuracies of these images were up to 98. 89%, 100%, 97.78% and 97.78% respectively, with the overall Kappa statistics of 0.9833, 1, 0.9667, and 0.966 7, indicating that SVI has excellent detection effects for bright area, shaded area and water area; the statistical comparison of sub-images between SVI and NDVI also illustrated the reliability and effectiveness of SVI, which can be applied in the shadow removal for remote sensing images.

  13. Central Amazon Forest Enhanced Vegetation Index Seasonality Driven by Strongly Seasonal Leaf Flush

    Science.gov (United States)

    Wu, J.; Nelson, B. W.; Lopes, A. P.; Graca, P. M. L. D. A.; Tavares, J. V.; Prohaska, N.; Martins, G.; Saleska, S. R.

    2015-12-01

    We used an RGB camera mounted 50m above an upland forest canopy to quantify leaf phenology during 12 months for 267 upper canopy tree crowns at the Amazon Tall Tower site (59.0005ºW, 2.1433ºS). Daily images under overcast sky were selected and radiometrically intercalibrated to remove any seasonal bias from incoming radiant color balance. Seasonality of crown color was then recovered for each individual crown by plotting its greenness timeline (green chromatic coordinate). We detected rapid large-amplitude positive and negative changes in greenness. Rapid increase was attributed to leaf flush and occurred in 85% of all crowns, with 80% showing a single flush per year. The theory of photoperiod control of equatorial tropical forest leaf phenology predicts two annual peaks of leaf flush, so is not supported. Rapid negative change occurred in 42% of individuals and was caused by massive pre-flush leaf abscission (31% of all trees) or other non-green pre-flushing states (11%). Crown flushing was concentrated in the five driest months (55% of trees) compared to the five wettest months (10%). Enhanced Vegetation Index (EVI) for each of three crown phenostages was obtained from a single high spatial resolution QuickBird satellite image.These phenostages were identified using only the visible bands of QuickBird so they could be related to the same crown stages seen in the RGB tower camera images. Relative frequencies of the three crown level phenostages were monitored with the tower camera, allowing a monthly estimate of landscape-scale EVI. Free of the seasonal effects on orbital sensors from clouds, cloud shadows, aerosols or solar illumination angle and corrected for seasonal change in light quality, the camera- and QuickBird derived EVI served as an independent verification of MODIS EVI seasonality. Camera-based EVI was highly consistent with view- and solar-angle corrected MAIAC-EVI of a 3x3 km footprint centered on the tower (R = 0.95 between the two monthly curves

  14. The comparison analysis of land cover change based on vegetation index and multispectral classification (Case study Leihitu Peninsula Ambon City District

    Directory of Open Access Journals (Sweden)

    W.A. Siahaya

    2015-07-01

    Full Text Available The study utilizes Landsat-7 ETM+ 2001and Landsat TM5 2009 based on Normalized Differences Vegetation Index (NDVI and 457 colour composite at the study area located in Leihitu Peninsula, Ambon City District, Ambon Island, Moluccas Province. The classified satellite data under NDVI and 457 colour composite of 2001 and 2009 of 2001 and 2009 were used to determine land cover change that have occurred in the study areas. This study attempts to use a comparative change detection analysis in land cover that has occurred in the study area with NDVI and 457 colour composite over 9 year period (2001 to 2009. The results of the present study disclose that total area increased their land cover were bare land and impermeable surface, herbaceous and shrubs, low density vegetation, and medium density vegetation, while high density vegetation is decreasing in both NDVI and 457 colour composite analysis. Overall accuracy was estimated to be around 94.3 % for NDVI and for 457 Colour composites was 84.7%. The study area has experienced a change in its land cover between 2001 and 2009 in both NDVI and 457 false colour composite analyses. The whole land cover types have experienced increased in both methods, except high density vegetation. The transformations of spectral vegetation (NDVI product more closely with actual land cover compared with 457 colour composite product.

  15. Dynamic Drought Monitoring in Guangxi Using Revised Temperature Vegetation Dryness Index

    Institute of Scientific and Technical Information of China (English)

    LU Yuan; TAG Heping; WU Hua

    2007-01-01

    Moderate resolution imaging spectroradiometer (MODIS) data are very suitable for vast extent, long term and dynamic drought monitoring for its high temporal resolution, high spectral resolution and moderate spatial resolution. The composite Enhanced Vegetation Index (EVI) and composite land surface temperature (Ts) obtained from MODIS data MOD11A2 and MOD13A2 were used to construct the EVI-rs space. And Temperature Vegetation Dryness Index (TVDI) was calculated to evaluate the agriculture drought in Guangxi province, China in October of 2006. The results showed that the drought area in Guangxi was evidently increasing and continuously deteriorating from the middle of September to the middle of November. The TVDI, coming from the EVI-rs space, could effectively indicate the spatial distribution and temporal evolution of drought, so that it could provide a strong technical support for the forecasting agricultural drought in south China.

  16. Modelling high arctic percent vegetation cover using field digital images and high resolution satellite data

    Science.gov (United States)

    Liu, Nanfeng; Treitz, Paul

    2016-10-01

    In this study, digital images collected at a study site in the Canadian High Arctic were processed and classified to examine the spatial-temporal patterns of percent vegetation cover (PVC). To obtain the PVC of different plant functional groups (i.e., forbs, graminoids/sedges and mosses), field near infrared-green-blue (NGB) digital images were classified using an object-based image analysis (OBIA) approach. The PVC analyses comparing different vegetation types confirmed: (i) the polar semi-desert exhibited the lowest PVC with a large proportion of bare soil/rock cover; (ii) the mesic tundra cover consisted of approximately 60% mosses; and (iii) the wet sedge consisted almost exclusively of graminoids and sedges. As expected, the PVC and green normalized difference vegetation index (GNDVI; (RNIR - RGreen)/(RNIR + RGreen)), derived from field NGB digital images, increased during the summer growing season for each vegetation type: i.e., ∼5% (0.01) for polar semi-desert; ∼10% (0.04) for mesic tundra; and ∼12% (0.03) for wet sedge respectively. PVC derived from field images was found to be strongly correlated with WorldView-2 derived normalized difference spectral indices (NDSI; (Rx - Ry)/(Rx + Ry)), where Rx is the reflectance of the red edge (724.1 nm) or near infrared (832.9 nm and 949.3 nm) bands; Ry is the reflectance of the yellow (607.7 nm) or red (658.8 nm) bands with R2's ranging from 0.74 to 0.81. NDSIs that incorporated the yellow band (607.7 nm) performed slightly better than the NDSIs without, indicating that this band may be more useful for investigating Arctic vegetation that often includes large proportions of senescent vegetation throughout the growing season.

  17. Comparison of the prevalence index and average wetland values for identification of wetland vegetation

    Energy Technology Data Exchange (ETDEWEB)

    Zimmerman, R.E.; Shem, L.M.; Gowdy, M.J. [Argonne National Lab., IL (United States); Van Dyke, G.D. [Trinity Christian Coll., Palos Heights, IL (United States); Hackney, C.T. [North Carolina Univ., Wilmington, NC (United States)

    1992-07-01

    Prevalence index values (FICWD, 1989) and average wetland values for all species present were compared for three wetland gas pipeline rights-of-way (ROWS) and adjacent natural areas. The similarities in results using these two indicator values suggest that an average wetland value may offer a simpler, less time-consuming method of evaluating the vegetation of a study site as an indication of wetness. Both PIVs and AWVs, are presented for the ROWs and the adjacent natural area at each site.

  18. 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 factor in reducing river flows. Climate change, regional groundwater pumping, changes in the intensity of monsoon rain events and lack of overbank flooding are feasible explanations for deterioration of the riparian forest in the northern reach.

  19. The 2005 and 2012 major drought events in Iberia: monitoring vegetation dynamics and crop yields using satellite data.

    Science.gov (United States)

    Gouveia, Célia M.; Trigo, Ricardo M.

    2014-05-01

    The Iberian Peninsula is recurrently affected by drought episodes and therefore by the adverse effects associated that range from severe water shortages to economic losses and related social impacts. During the hydrological years of 2004/2005 and 2011/2012, Iberia was hit by two of the worst drought episodes ever recording in this semi-arid region (Garcia-Herrera at al., 2007; Trigo et al., 2013). These two drought episodes were extreme in both its magnitude and spatial extent. A tendency towards a drier Mediterranean for the period 1970-2010 in comparison with 1901-70 has been identified (Hoerling et al., 2012), reinforcing the need for a continuous monitoring of vegetation stress and reliable estimates of the drought impacts. The strong effect of water scarcity on vegetation dynamics is well documented in Mediterranean and other semi-arid regions. Despite the usual link established between the decrease of vegetation greenness and the lack of precipitation during a considerably long period, the impact on vegetation activity may be amplified by other climatic anomalies, such as high temperature, high wind, and low relative humidity. The recent availability of consistent satellite imagery covering large regions over long periods of time has progressively reinforced the role of remote sensing in environmental studies, in particular in those related to drought episodes (e.g. Gouveia et al., 2009). The aim of the present work is to assess and monitor the cumulative impact over time of drought conditions on vegetation over Iberian Peninsula. For this purpose we have used the regional fields of the Normalized Difference Vegetation Index (NDVI) as obtained from the VEGETATION-SPOT5 instrument, from 1999 to 2013. The entire 15-yr long period was analysed, but particular attention was devoted to the two extreme drought episodes of 2004-2005 and 2011-2012. During the hydrological years of 2004-2005 and 2011-2012 drought episodes negative anomalies of NDVI were observed over

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

    Directory of Open Access Journals (Sweden)

    Alvaro Ivanoff

    2013-08-01

    Full Text Available Satellite observations of surface reflected solar radiation contain information about variability in the absorption of solar radiation by vegetation. Understanding the causes of variability is important for models that use these data to drive land surface fluxes or for benchmarking prognostic vegetation models. Here we evaluated the interannual variability 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. Pearson’s correlation and multiple linear stepwise regression analyses were applied to quantify the NDVI interannual variability driven by climate anomalies, and to evaluate the effects of potential interference (snow, aerosols and clouds on the NDVI signal. 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 systems where in some regions and seasons > 40% of the NDVI variance could be explained by precipitation 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 wet season 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.

  1. 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.

  2. [Retrieval of Copper Pollution Information from Hyperspectral Satellite Data in a Vegetation Cover Mining Area].

    Science.gov (United States)

    Qu, Yong-hua; Jiao, Si-hong; Liu, Su-hong; Zhu, Ye-qing

    2015-11-01

    Heavy metal mining activities have caused the complex influence on the ecological environment of the mining regions. For example, a large amount of acidic waste water containing heavy metal ions have be produced in the process of copper mining which can bring serious pollution to the ecological environment of the region. In the previous research work, bare soil is mainly taken as the research target when monitoring environmental pollution, and thus the effects of land surface vegetation have been ignored. It is well known that vegetation condition is one of the most important indictors to reflect the ecological change in a certain region and there is a significant linkage between the vegetation spectral characteristics and the heavy metal when the vegetation is effected by the heavy metal pollution. It means the vegetation is sensitive to heavy metal pollution by their physiological behaviors in response to the physiological ecology change of their growing environment. The conventional methods, which often rely on large amounts of field survey data and laboratorial chemical analysis, are time consuming and costing a lot of material resources. The spectrum analysis method using remote sensing technology can acquire the information of the heavy mental content in the vegetation without touching it. However, the retrieval of that information from the hyperspectral data is not an easy job due to the difficulty in figuring out the specific band, which is sensitive to the specific heavy metal, from a huge number of hyperspectral bands. Thus the selection of the sensitive band is the key of the spectrum analysis method. This paper proposed a statistical analysis method to find the feature band sensitive to heavy metal ion from the hyperspectral data and to then retrieve the metal content using the field survey data and the hyperspectral images from China Environment Satellite HJ-1. This method selected copper ion content in the leaves as the indicator of copper pollution

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

    Science.gov (United States)

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

    2010-01-01

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

  4. RGB picture vegetation indexes for High-Throughput Phenotyping Platforms (HTPPs)

    Science.gov (United States)

    Kefauver, Shawn C.; El-Haddad, George; Vergara-Diaz, Omar; Araus, José Luis

    2015-10-01

    Extreme and abnormal weather events, as well as the more gradual meteorological changes associated with climate change, often coincide with not only increased abiotic risks (such as increases in temperature and decreases in precipitation), but also increased biotic risks due to environmental conditions that favor the rapid spread of crop pests and diseases. Durum wheat is by extension the most cultivated cereal in the south and east margins of the Mediterranean Basin. It is of strategic importance for Mediterranean agriculture to develop new varieties of durum wheat with greater production potential, better adaptation to increasingly adverse environmental conditions (drought) and better grain quality. Similarly, maize is the top staple crop for low-income populations in Sub-Saharan Africa and is currently suffering from the appearance of new diseases, which, together with increased abiotic stresses from climate change, are challenging the very sustainability of African societies. Current constraints in field phenotyping remain a major bottleneck for future breeding advances, but RGB-based High-Throughput Phenotyping Platforms (HTPPs) have shown promise for rapidly developing both disease-resistant and weather-resilient crops. RGB cameras have proven costeffective in studies assessing the effect of abiotic stresses, but have yet to be fully exploited to phenotype disease resistance. Recent analyses of durum wheat in Spain have shown RGB vegetation indexes to outperform multispectral indexes such as NDVI consistently in disease and yield prediction. Towards HTTP development for breeding maize disease resistance, some of the same RGB picture vegetation indexes outperformed NDVI (Normalized Difference Vegetation Index), with R2 values up to 0.65, compared to 0.56 for NDVI. . Specifically, hue, a*, u*, and Green Area (GA), as produced by FIJI and BreedPix open source software, performed similar to or better than NDVI in predicting yield and disease severity conditions

  5. Vegetation Height Estimation Near Power transmission poles Via satellite Stereo Images using 3D Depth Estimation Algorithms

    Science.gov (United States)

    Qayyum, A.; Malik, A. S.; Saad, M. N. M.; Iqbal, M.; Abdullah, F.; Rahseed, W.; Abdullah, T. A. R. B. T.; Ramli, A. Q.

    2015-04-01

    Monitoring vegetation encroachment under overhead high voltage power line is a challenging problem for electricity distribution companies. Absence of proper monitoring could result in damage to the power lines and consequently cause blackout. This will affect electric power supply to industries, businesses, and daily life. Therefore, to avoid the blackouts, it is mandatory to monitor the vegetation/trees near power transmission lines. Unfortunately, the existing approaches are more time consuming and expensive. In this paper, we have proposed a novel approach to monitor the vegetation/trees near or under the power transmission poles using satellite stereo images, which were acquired using Pleiades satellites. The 3D depth of vegetation has been measured near power transmission lines using stereo algorithms. The area of interest scanned by Pleiades satellite sensors is 100 square kilometer. Our dataset covers power transmission poles in a state called Sabah in East Malaysia, encompassing a total of 52 poles in the area of 100 km. We have compared the results of Pleiades satellite stereo images using dynamic programming and Graph-Cut algorithms, consequently comparing satellites' imaging sensors and Depth-estimation Algorithms. Our results show that Graph-Cut Algorithm performs better than dynamic programming (DP) in terms of accuracy and speed.

  6. Using satellite data on meteorological and vegetation characteristics and soil surface humidity in the Land Surface Model for the vast territory of agricultural destination

    Science.gov (United States)

    Muzylev, Eugene; Startseva, Zoya; Uspensky, Alexander; Vasilenko, Eugene; Volkova, Elena; Kukharsky, Alexander

    2017-04-01

    vegetation cover (taken for vegetation temperature) Ta and efficient radiation temperature Ts.eff, as well as land surface emissivity E, normalized difference vegetation index NDVI, vegetation cover fraction B, and leaf area index LAI. The SEVIRI-based retrievals have included precipitation, LST Tls and Ta, E at daylight and nighttime, LAI (daily), and B. From the MSU-MR data there have been retrieved values of all the same characteristics as from the AVHRR data. The MSU-MR-based daily and monthly sums of precipitation have been calculated using the developed earlier and modified Multi Threshold Method (MTM) intended for the cloud detection and identification of its types around the clock as well as allocation of precipitation zones and determination of instantaneous maximum rainfall intensities for each pixel at that the transition from assessing rainfall intensity to estimating their daily values is a key element of the MTM. Measurement data from 3 IR MSU-MR channels (3.8, 11 i 12 μm) as well as their differences have been used in the MTM as predictors. Controlling the correctness of the MSU-MR-derived rainfall estimates has been carried out when comparing with analogous AVHRR- and SEVIRI-based retrievals and with precipitation amounts measured at the agricultural meteorological station of the study region. Probability of rainfall zones determination from the MSU-MR data, to match against the actual ones, has been 75-85% as well as for the AVHRR and SEVIRI data. The time behaviors of satellite-derived and ground-measured daily and monthly precipitation sums for vegetation season and yeaŗ correspondingly, have been in good agreement with each other although the first ones have been smoother than the latter. Discrepancies have existed for a number of local maxima for which satellite-derived precipitation estimates have been less than ground-measured values. It may be due to the different spatial scales of areal satellite-derived and point ground-based estimates. Some

  7. Estimation of volcanic ash refractive index from satellite infrared sounder data

    Science.gov (United States)

    Ishimoto, H.; Masuda, K.

    2014-12-01

    The properties of volcanic ash clouds (cloud height, optical depth, and effective radius of the particles) are planned to estimate from the data of the next Japanese geostationary meteorological satellite, Himawari 8/9. The volcanic ash algorithms, such as those proposed by NOAA/NESDIS and by EUMETSAT, are based on the infrared absorption properties of the ash particles, and the refractive index of a typical volcanic rock (i.e. andesite) has been used in the forward radiative transfer calculations. Because of a variety of the absorption properties for real volcanic ash particles at infrared wavelengths (9-13 micron), a large retrieval error may occur if the refractive index of the observed ash particles was different from that assumed in the retrieval algorithm. Satellite infrared sounder provides spectral information for the volcanic ash clouds. If we can estimate the refractive index of the ash particles from the infrared sounder data, a dataset of the optical properties for similar rock type of the volcanic ash can be prepared for the ash retrieval algorithms of geostationary/polar-orbiting satellites in advance. Furthermore, the estimated refractive index can be used for a diagnostic and a correction of the ash particle model in the retrieval algorithm within a period of the volcanic activities. In this work, optimal estimation of the volcanic ash parameters was conducted through the radiative transfer calculations for the window channels of the atmospheric infrared sounder (AIRS). The estimated refractive indices are proposed for the volcanic ash particles of some eruption events.

  8. 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

  9. Evaluation of NPP VIIRS Vegetation Index EDR performance using MODIS and AVHRR data records

    Science.gov (United States)

    vargas, M.; Shabanov, N.; Miura, T.

    2012-12-01

    Vegetation Index (VI) is one key parameter to specify the boundary condition in global climate models, weather forecasting models and numerous remote sensing applications for monitoring environmental state and its change. The VI Environmental Data Record (EDR), which includes the Top of Atmosphere Normalized Difference Vegetation Index (TOA NDVI) and the Top of Canopy Enhanced Vegetation Index (TOC EVI), is currently operationally generated from data delivered by the Visible Infrared Imaging radiometer Suite (VIIRS) instrument onboard the National Polar-orbiting Partnership (NPP) platform launched in October 2011. The VI EDR was implemented to provide continuity for 30+ years of historical VI records provided by MODIS and AVHRR sensors. This presentation reports on the results of the analysis performed by the JPSS VI group at NOAA-NESDIS-STAR on two major aspects of performance of the VI EDR in the early phase of the NPP mission: (1) assessment of accuracy of the VIIRS VI EDR product with respect to input data including Surface Reflectances, Cloud and Aerosol masks as function of vegetation (biome) types; (2) temporal and spatial consistency of VIIRS VI EDR with respect to heritage MODIS and AVHRR VI products. This analysis is based on data from VIIRS (daily TOA NDVI and TOC EVI, and daily surface reflectances), Terra MODIS (16 days composites of TOC EVI and TOC NDVI, and daily TOA radiances) and NOAA-18 AVHRR (7-days composites of TOA NDVI). MODIS 8-biome landcover mask was used to quantify variations in VI product performance as function of vegetation type. Best overall agreement is achieved between VIIRS and MODIS data (TOC EVI and TOC NDVI) in terms of minimum systematic discrepancy (minimum bias and STD) and highest correlation of spatial patterns (highest r^2). The agreement is highest for biomes with low vegetation cover, but degrades with increased foliage density. VIIRS cloud mask provides a fair screening of daily data over the globe. While performance of

  10. 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.

  11. A New Temperature-Vegetation Triangle Algorithm with Variable Edges (TAVE for Satellite-Based Actual Evapotranspiration Estimation

    Directory of Open Access Journals (Sweden)

    Hua Zhang

    2016-09-01

    Full Text Available The estimation of spatially-variable actual evapotranspiration (AET is a critical challenge to regional water resources management. We propose a new remote sensing method, the Triangle Algorithm with Variable Edges (TAVE, to generate daily AET estimates based on satellite-derived land surface temperature and the vegetation index NDVI. The TAVE captures heterogeneity in AET across elevation zones and permits variability in determining local values of wet and dry end-member classes (known as edges. Compared to traditional triangle methods, TAVE introduces three unique features: (i the discretization of the domain as overlapping elevation zones; (ii a variable wet edge that is a function of elevation zone; and (iii variable values of a combined-effect parameter (that accounts for aerodynamic and surface resistance, vapor pressure gradient, and soil moisture availability along both wet and dry edges. With these features, TAVE effectively addresses the combined influence of terrain and water stress on semi-arid environment AET estimates. We demonstrate the effectiveness of this method in one of the driest countries in the world—Jordan, and compare it to a traditional triangle method (TA and a global AET product (MOD16 over different land use types. In irrigated agricultural lands, TAVE matched the results of the single crop coefficient model (−3%, in contrast to substantial overestimation by TA (+234% and underestimation by MOD16 (−50%. In forested (non-irrigated, water consuming regions, TA and MOD16 produced AET average deviations 15.5 times and −3.5 times of those based on TAVE. As TAVE has a simple structure and low data requirements, it provides an efficient means to satisfy the increasing need for evapotranspiration estimation in data-scarce semi-arid regions. This study constitutes a much needed step towards the satellite-based quantification of agricultural water consumption in Jordan.

  12. Aerial image mosaics built using images with vegetation index pre-calculated

    Science.gov (United States)

    Rosendo Candido, Leandro; de Castro Jorge, Lúcio André; Luppe, Maximiliam

    2016-10-01

    Precision agriculture (PA) has offered a multitude of benefits to farmers, such as cost reduction, accuracy and speed in decision making. Among the tools that work with PA, the aerial image mosaics have key role in accurate mapping of diseases and pests in crops. A mosaic is the combination of multiple images, creating a new image that covers the property or plots accurately. One of the important analysis for farmers is based on the properties of the reflectance in each range of the electromagnetic spectrum of vegetation. Performing mathematical combinations of the different spectral bands has a better understanding of the spectral response of the vegetation. These combinations are called vegetation index (VI) and are useful for the control of the biomass, water content in leaf, chlorophyll content and others. It is usually calculated VI after the construction of the mosaic, as well the farmer has an accurate analysis of its vegetation. However, building a mosaic of images, it has a high computational cost, taking hours to complete and then apply the VI and to have the first test results. In order to reduce the computational cost of this process, this work aims to present a mosaic of images constructed from images with the VI already pre-calculated providing faster analysis to the farmer, given the fact that applying VI on the image came a this reduction in density image and thus have the gain in computational cost to build the mosaic.

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

    Directory of Open Access Journals (Sweden)

    Timothy J. Fullman

    2014-01-01

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

  14. Monitoring the hydrologic and vegetation dynamics of arid land with satellite remote sensing and mathematic modeling

    Science.gov (United States)

    Zhan, Xiwu; Gao, Wei; Pan, Xiaoling; Ma, Yingjun

    2003-07-01

    Terrestrial ecosystems, in which carbon is retained in live biomass, play an important role in the global carbon cycling. Among these ecological systems, vegetation and soils in deserts and semi deserts control significant proportions in the total carbon stocks on the land surface and the carbon fluxes between the land surface and the atmosphere (IPCC special report: Land Use, Land Use Change and Forestry, June 2000). Therefore, accurate assessment of the carbon stocks and fluxes of the desert and semi desert areas at regional scales is required in global carbon cycle studies. In addition, vegetative ecosystem in semi-arid and arid land is strongly dependent on the water resources. Monitoring the hydrologic processes of the land is thus also required. This work explores the methodology for the sequential continuous estimation of the carbon stocks, CO2 flux, evapotranspiration, and sensible heat fluxes over desert and semidesert area using data from the Jornada desert in New Mexico, USA. A CO2 and energy flux coupled model is used to estimate CO2, water vapor and sensible heat fluxes over the desert area. The model is driven by the observed meteorological data. Its input land surface parameters are derived from satellite images. Simulated energy fluxes are validated for specific sites with eddy covariance observations. Based on the output of spatially distributed CO2 fluxes, carbon accumulations over the desert area during a period of time is calculated and the contribution of the desert ecosystem to the atmospheric carbon pool is discussed.

  15. Spatial Downscaling Research of Satellite Land Surface Temperature Based on Spectral Normalization Index

    Directory of Open Access Journals (Sweden)

    LI Xiaojun

    2017-03-01

    Full Text Available Aiming at the problem that the spatial and temporal resolution of land surface temperature (LST have the contradiction with each other, a new downscaling model was put forward, based on the TsHARP(an algorithm for sharpening thermal imagery downscaling method, this research makes improvements by selecting the better correlation of spectral index(normalized difference vegetation index, NDVI; normalized difference build-up index, NDBI; modified normalized difference water index, MNDWI; enhanced bare soil index, EBSI with LST, i.e., replaces the original NDVI with new spectral index according to the different surface land-cover types, to assess the accuracy of each downscaling method based on qualitative and quantitative analysis with synchronous Landsat 8 TIRS LST data. The results show that both models could effectively enhance the spatial resolution while simultaneously preserving the characteristics and spatial distribution of the original 1 km MODIS LST image, and also eliminate the “mosaic” effect in the original 1 km image, both models were proved to be effective and applicable in our study area; global scale analysis shows that the new model (RMSE:1.635℃ is better than the TsHARP method (RMSE:2.736℃ in terms of the spatial variability and accuracy of the results; the different land-cover types of downscaling statistical analysis shows that the TsHARP method has poor downscaling results in the low vegetation coverage area, especially for the bare land and building-up area(|MBE|>3℃, the new model has obvious advantages in the description of the low vegetation coverage area. Seasonal analysis shows that the downscaling results of two models in summer and autumn are superior to those in spring and winter, the new model downscaling results are better than the TsHARP method in the four seasons, in which the spring and winter downscaling improvement is better than summer and autumn.

  16. A novel spectral index to automatically extract road networks from WorldView-2 satellite imagery

    Directory of Open Access Journals (Sweden)

    Kaveh Shahi

    2015-06-01

    Full Text Available This research develops a spectral index to automatically extract asphalt road networks named road extraction index (REI. This index uses WorldView-2 (WV-2 imagery, which has high spatial resolution and is multispectral. To determine the best bands for WV-2, field spectral data using a field spectroradiometer were collected. These data were then analyzed statistically. The bands were selected through the methodology of stepwise discriminant analysis. The appropriate WV-2 bands were distinguished from one another as per significant wavelengths. The proposed index is based on this classification. By applying REI to WV-2 imagery, we can extract asphalt roads accurately. Results demonstrate that REI is automated, transferable, and efficient in asphalt road extraction from high-resolution satellite imagery.

  17. Development of satellite green vegetation fraction time series for use in mesoscale modeling: application to the European heat wave 2006

    DEFF Research Database (Denmark)

    Nielsen, Joakim Refslund; Dellwik, Ebba; Hahmann, Andrea N.

    2014-01-01

    A method is presented for development of satellite green vegetation fraction (GVF) time series for use in the Weather Research and Forecasting (WRF) model. The GVF data is in the WRF model used to describe the temporal evolution of many land surface parameters, in addition to the evolution...

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

    Science.gov (United States)

    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. PMID:28125607

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

    Science.gov (United States)

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

    2017-01-01

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

  20. Loss of surface horizon of an irrigated soil detected by radiometric images of normalized difference vegetation index.

    Science.gov (United States)

    Fabian Sallesses, Leonardo; Aparicio, Virginia Carolina; Costa, Jose Luis

    2017-04-01

    The use of the soil in the Humid Pampa of Argentina has changed since the mid-1990s from agricultural-livestock production (that included pastures with direct grazing) to a purely agricultural production. Also, in recent years the area under irrigation by central pivot has been increased to 150%. The waters used for irrigation are sodium carbonates. The combination of irrigation and rain increases the sodium absorption ratio of soil (SARs), consequently raising the clay dispersion and reducing infiltration. This implies an increased risk of soil loss. A reduction in the development of white clover crop (Trifolium repens L.) was observed at an irrigation plot during 2015 campaign. The clover was planted in order to reduce the impact of two maize (Zea mays L.) campaigns under irrigation, which had increased soil SAR and deteriorated soil structure. SPOT-5 radiometric normalized difference vegetation index (NDVI) images were used to determine two zones of high and low production. In each zone, four random points were selected for further geo-referenced field sampling. Two geo-referenced measures of effective depth and surface soil sampling were carried out in each point. Texture of soil samples was determined by Pipette Method of Sedimentation Analysis. Data exploratory analysis showed that low production zone had a media effective depth = 80 cm and silty clay loam texture, while high production zone had a media effective depth > 140 cm and silt loam texture. The texture class of the low production zone did not correspond to prior soil studies carried out by the INTA (National Institute of Agricultural Technology), which showed that those soil textures were silt loam at surface and silty clay loam at sub-surface. The loss of the A horizon is proposed as a possible explanation, but further research is required. Besides, the need of a soil cartography actualization, which integrates new satellite imaging technologies and geo-referenced measurements with soil sensors is

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

    Science.gov (United States)

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

    2013-09-01

    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.

  2. Correlation of meteorological parameters and remotely sensed normalized difference vegetation index (NDVI) with cotton leaf curl virus (CLCV) in Multan

    Science.gov (United States)

    Ahmed, A.; Akhtar, A.; Khalid, B.; Shamim, A.

    2013-06-01

    Climate change and weather has a profound effect on the spread of Cotton Leaf Curl Virus (CLCV) which is transmitted by whitefly. Climate change is altering temperature and precipitation patterns, resulting in the shift of some insect/pest from small population to large population thus effecting crops yield. To find out the relationship between the weather conditions, outburst of CLCV and changes in Normalized Difference Vegetation Index (NDVI) values due to the outburst of CLCV, a study was carried out for tehsil Multan. Data was acquired for the months of June, July, August and September for the year 2010. Regression analysis between CLCV and meteorological conditions as well as between CLCV and NDVI was performed. Meteorological parameters included temperature, humidity, precipitation, cloud cover, wind direction, pan evaporation and sunshine hours. NDVI values were calculated from SPOT satellite imagery (1km) using ArcMap10 and WinDisp v5.1. Correlation coefficients obtained in most of the cases were acceptable however the significance F and P-value were higher than their critical value at 95% level of significance. Therefore significant correlation was found only between CLCV and temperature and between CLCV and PAN evaporation during the month of July.

  3. Satellite monitoring of different vegetation types by differential optical absorption spectroscopy (DOAS in the red spectral range

    Directory of Open Access Journals (Sweden)

    T. Wagner

    2007-01-01

    Full Text Available A new method for the satellite remote sensing of different types of vegetation and ocean colour is presented. In contrast to existing algorithms relying on the strong change of the reflectivity in the red and near infrared spectral region, our method analyses weak narrow-band (few nm reflectance structures (i.e. "fingerprint" structures of vegetation in the red spectral range. It is based on differential optical absorption spectroscopy (DOAS, which is usually applied for the analysis of atmospheric trace gas absorptions. Since the spectra of atmospheric absorption and vegetation reflectance are simultaneously included in the analysis, the effects of atmospheric absorptions are automatically corrected (in contrast to other algorithms. The inclusion of the vegetation spectra also significantly improves the results of the trace gas retrieval. The global maps of the results illustrate the seasonal cycles of different vegetation types. In addition to the vegetation distribution on land, they also show patterns of biological activity in the oceans. Our results indicate that improved sets of vegetation spectra might lead to more accurate and more specific identification of vegetation type in the future.

  4. Glycemic index determination of vegetable and fruits in healthy Bangladeshi subjects.

    Science.gov (United States)

    Fatema, K; Sumi, N; Rahman, F; Kobura, K; Ali, L

    2011-12-01

    Fruits and vegetables are an important part of the diet especially for their complex carbohydrates, dietary fibre and micronutrients. The present study investigated the glycemic index (GI) of a vegetable [carrot (Daucas carota)] and fruits [banana (Chapa kola) Musa Sp. and plum (Bau kul) Zizyphus mauritiana] of Bangladeshi origin. Fourteen healthy Bangladeshi subjects, comprising 7 males and, 7 females, with mean age of 26 +/- 3 years, BMI 22 +/- 3 kg/m2, waist-hip ratio of 0.89 +/- 0.01 and 0.84 +/- 0.04 respectively for males and females. Under a cross-over design, they consumed equi-carbohydrate amounts (25 g of total available carbohydrate) of the test foods and two times glucose as reference food (25 g of total carbohydrate), with a run in period of 7 days between the consecutive items. Serum glucose levels were determined at 0, 30, 60, 90, and 120 min. The GIs was calculated. The carrot, banana and plum samples showed significantly lower serum glucose values (incremental area under the curve 30.4 +/- 12.6, 37.3 +/- 19.2 and 41.8 +/- 20.7 respectively) than glucose (132.7 +/- 36.0). The carrot showed a lower GI value than banana and plum respectively (23 +/- 9, 30 +/- 18 and 32 +/- 15). The vegetable and fruit samples tested of Bangladesh origin were shown to have comparatively low GI values.

  5. Drought impact assessment from monitoring the seasonality of vegetation condition using long-term time-series satellite images: a case study of Mt. Kenya region.

    Science.gov (United States)

    Song, Youngkeun; Njoroge, John B; Morimoto, Yukihiro

    2013-05-01

    Drought-induced anomalies in vegetation condition over wide areas can be observed by using time-series satellite remote sensing data. Previous methods to assess the anomalies may include limitations in considering (1) the seasonality in terms of each vegetation-cover type, (2) cumulative damage during the drought event, and (3) the application to various types of land cover. This study proposed an improved methodology to assess drought impact from the annual vegetation responses, and discussed the result in terms of diverse landscape mosaics in the Mt. Kenya region (0.4° N 35.8° E ~ 1.6° S 38.4° E). From the 30-year annual rainfall records at the six meteorological stations in the study area, we identified 2000 as the drought year and 2001, 2004, and 2007 as the normal precipitation years. The time-series profiles of vegetation condition in the drought and normal precipitation years were obtained from the values of Enhanced Vegetation Index (EVI; Huete et al. 2002), which were acquired from Terra MODIS remote sensing dataset (MOD13Q1) taken every 16 days at the scale of 250-m spatial resolution. The drought impact was determined by integrating the annual differences in EVI profiles between drought and normal conditions, per pixel based on nearly same day of year. As a result, we successfully described the distribution of landscape vulnerability to drought, considering the seasonality of each vegetation-cover type at every MODIS pixel. This result will contribute to the large-scale landscape management of Mt. Kenya region. Future study should improve this method by considering land-use change occurred during the long-term monitoring period.

  6. Relationships between evaprorative fraction and remotely sensed vegetation index and microwave brightness temperature for semiarid rangelands

    Science.gov (United States)

    Kustas, W. P.; Schimugge, T. J.; Humes, K. S.; Jackson, T. J.; Parry, R.; Weltz, M. A.; Moran, M. S.

    1993-01-01

    Measurements of the microwave brightness temperature (TB) with the Pushbroom Microwave Radiometer (PBMR) over the Walnut Gulch Experiment Watershed were made on selected days during the MONSOON 90 field campaign. The PBMR is an L-band instrument (21-cm wavelength) that can provide estimates of near-surface soil moisture over a variety of surfaces. Aircraft observations in the visible and near-infrared wavelengths collected on selected days also were used to compute a vegetation index. Continuous micrometeorological measurements and daily soil moisture samples were obtained at eight locations during experimental period. Two sites were instrumented with time domain reflectometry probes to monitor the soil moisture profile. The fraction of available energy used for evapotranspiration was computed by taking the ratio of latent heat flux (LE) to the sum of net radiation (Rn) and soil heat flux (G). This ratio is commonly called the evaporative fraction (EF) and normally varies between 0 and 1 under daytime convective conditions with minimal advection. A wide range of environmental conditions existed during the field campaign, resulting in average EF values for the study area varying from 0.4 to 0.8 and values of TB ranging from 220 to 280 K. Comparison between measured TB and EF for the eight locations showed an inverse relationship. Other days were included in the analysis by estimating TB with the soil moisture data. Because transpiration from the vegetation is more strongly coupled to root zone soil moisture, significant scatter in this relationship existed at high values of TB or dry near-surface soil moisture conditions. The variation in EF under dry near-surface soil moisture conditions was correlated to the amount of vegetation cover estimated with a remotely sensed vegetation index. These findings indicate that information obtained from optical and microwave data can be used for quantifying the energy balance of semiarid areas. The microwave data can indicate

  7. Relationships between Evaporative Fraction and Remotely Sensed Vegetation Index and Microwave Brightness Temperature for Semiarid Rangelands.

    Science.gov (United States)

    Kustas, W. P.; Schmugge, T. J.; Humes, K. S.; Jackson, T. J.; Parry, R.; Weltz, M. A.; Moran, M. S.

    1993-12-01

    Measurements of the microwave brightness temperature (TB) with the Pushbroom Microwave Radiometer (PBMR) over the Walnut Gulch Experimental Watershed were made on selected days during the MONSOON 90 field campaign. The PBMR is an L-band instrument (21-cm wavelength) that can provide estimates of near-surface soil moisture over a variety of surfaces. Aircraft observations in the visible and near-infrared wavelengths collected on selected days also were used to compute a vegetation index. Continuous micrometeorological measurements and daily soil moisture samples were obtained at eight locations during the experimental period. Two sites were instrumented with time domain reflectometry probes to monitor the soil moisture profile. The fraction of available energy used for evapotranspiration was computed by taking the ratio of latent heat flux (LE) to the sum of net radiation (Rn) and soil heat flux (G). This ratio is commonly called the evaporative fraction (EF) and normally varies between 0 and 1 under daytime convective conditions with minimal advection. A wide range of environmental conditions existed during the field campaign, resulting in average EF values for the study area varying from 0.4 to 0.8 and values of TB ranging from 220 to 280 K. Comparison between measured TB and EF for the eight locations showed an inverse relationship with a significant correlation (r2 = 0.69). Other days were included in the analysis by estimating TB with the soil moisture data. Because transpiration from the vegetation is more strongly coupled to root zone soil moisture, significant scatter in this relationship existed at high values of TB or dry near-surface soil moisture conditions. It caused a substantial reduction in the correlation with r2 = 0.40 or only 40% of the variation in EF being explained by TB. The variation in EF under dry near-surface soil moisture conditions was correlated to the amount of vegetation cover estimated with a remotely sensed vegetation index. These

  8. Detection of Terrestrial Ecosystem Disturbances Using Aqua/MODIS Land Surface Temperature and Enhanced Vegetation Index

    Science.gov (United States)

    Mildrexler, D. J.; Zhao, M.; Running, S. W.

    2011-12-01

    Global information on the timing, location and magnitude of large-scale ecosystem disturbance events is needed to reduce significant uncertainty in the global carbon cycle. The MODIS Global Disturbance Index (MGDI) algorithm is designed for systematic, global, disturbance mapping using Aqua/MODIS Land Surface Temperature (LST) and Enhanced Vegetation Index (EVI) data. The MGDI uses annual maximum composite LST data to detect fundamental changes in land-surface energy partitioning, while avoiding the high natural variability associated with tracking LST at daily, weekly, or seasonal time frames. LST and EVI respond to different biophysical processes and coupling these variables together into a ratio results in a dynamic approach that measures both the energy exchange consequence and the vegetation density changes resulting from disturbance. This robust radiometric relationship is revisited for each individual pixel every year resulting in a consistent methodology that can be generalized globally to provide 1-km resolution information about the effects of major disturbance on woody ecosystems and has been validated across North America. We have now applied the full Aqua/MODIS dataset through 2010 to the MGDI algorithm across woody ecosystems globally and continue to validate the MGDI results by comparison with confirmed, historical disturbance events such as wildfire, hurricanes, insect epidemics, ice storms, and droughts.

  9. Mapping paddy biomass with multiple vegetation indexes by using multispectral remotely sensed image

    Science.gov (United States)

    Gu, Xiaohe; Wang, Yancang; Song, Xiaoyu; Xu, Xingang

    2016-10-01

    Monitoring dry biomass of crop timely and accurately by remote sensing is crucial to assess crop growth, manage field water-fertilizer and predict yield. The Huaihe River Basin in China was chose as study area to map the spatial distribution of paddy biomass. The study derived 12 vegetation indexes from HJ-CCD image, which were closely related to crop growth. After screening sensitive vegetation index with in-situ samples by correlation analysis, the study developed the inversion model by single variable and multiple variables. The determination coefficient (R2) and root mean square error (RMSE) was used to evaluate the accuracy of models. Results showed that the accuracies of multivariable models were better than these of single-variable models, of which the average R2 reached 0.647 and the average RMSE was 0.059. It indicated that the multi-variable models were input in more information than those of single-variable models, which improved the accuracies of estimating paddy biomass in to a certain degree. The average overall accuracies of multi-variable models were 92.7%, while that of singe-variable models were 87.8%. The model with multiple linear regressions could be used to map the paddy biomass in the study area by using HJ-CCD image.

  10. Tree Species Richness, Diversity, and Vegetation Index for Federal Capital Territory, Abuja, Nigeria

    Directory of Open Access Journals (Sweden)

    Aladesanmi D Agbelade

    2017-01-01

    Full Text Available This study was conducted to investigate the tree species richness and diversity of urban and periurban areas of the Federal Capital Territory (FCT, Abuja, Nigeria, and produce Normalized Difference Vegetation Index (NDVI for the territory. Data were collected from urban (Abuja city and periurban (Lugbe areas of the FCT using both semistructured questionnaire and inventory of tree species within green areas. In the study location, all trees with diameter at breast height (dbh ≥ 10 cm were identified; their dbh was measured and frequency was taken. The NDVI was calculated in ArcGIS 10.3 environment using standard formula. A cumulative total of twenty-nine (29 families were encountered within the FCT, with 27 occurring in Abuja city (urban centre and 12 in Lugbe (periurban centre of the FCT. The results of Shannon-Wiener diversity index (H′ for the two centres are 3.56 and 2.24 while Shannon’s maximum diversity index (Hmax is 6.54 (Abuja city and 5.36 (Lugbe for the urban (Abuja city and periurban (Lugbe areas of the Federal Capital Territory (FCT. The result of tree species evenness (Shannon’s equitability (EH index in urban and periurban centres was 0.54 and 0.42, respectively. The study provided baseline information on urban and periurban forests in the FCT of Nigeria, which can be used for the development of tree species database of the territory.

  11. Relationship of Remote Sensing Normalized Differential Vegetation Index to Anopheles Density and Malaria Incidence Rate

    Institute of Scientific and Technical Information of China (English)

    2006-01-01

    To study the relationship of remote sensing normalized differential vegetation index (NDVI) to Anopheles density and malaria incidence rate. Methods Data of monthly average climate, environment, Anopheles density and malaria incidence rate, and remote sensing NDVI were collected from 27 townships of 10 counties in southeastern Yunnan Province from 1984 to 1993. The relationship of remote sensing ecological proxy index, NDVI, to Anopheles density and malaria incidence rate was studied by principal component analysis, factor analysis and grey correlation analysis. Results The correlation matrix showed that NDVI highly correlated with Anopheles density in 4 townships of Mengla, Jinghong, and Yuanjiang counties, but in other 23 townships the relationship was not clear. Principal component and factor analyses showed that remote sensing NDVI was the representative index of the first principal component and the first common factor of Anopheles density evaluation. Grey correlation analysis showed that in rainy season NDVI had a high grey correlation with Anopheles density and malaria incidence rate. The grey correlation analysis showed that in rainy season the grey degree of NDVI correlated with Anopheles. Minimus density was 0.730, and 0.713 with Anopheles sinensis density, and 0.800 with malarial incidence rate. Conclusion Remote sensing NDVI can serve as a sensitive evaluation index of Anopheles density and malaria incidence rate.

  12. Trends in normalized difference vegetation index (NDVI) associated with urban development in northern West Siberia

    Science.gov (United States)

    Esau, Igor; Miles, Victoria V.; Davy, Richard; Miles, Martin W.; Kurchatova, Anna

    2016-08-01

    Exploration and exploitation of oil and gas reserves of northern West Siberia has promoted rapid industrialization and urban development in the region. This development leaves significant footprints on the sensitive northern environment, which is already stressed by the global warming. This study reports the region-wide changes in the vegetation cover as well as the corresponding changes in and around 28 selected urbanized areas. The study utilizes the normalized difference vegetation index (NDVI) from high-resolution (250 m) MODIS data acquired for summer months (June through August) over 15 years (2000-2014). The results reveal the increase of NDVI (or "greening") over the northern (tundra and tundra-forest) part of the region. Simultaneously, the southern, forested part shows the widespread decrease of NDVI (or "browning"). These region-wide patterns are, however, highly fragmented. The statistically significant NDVI trends occupy only a small fraction of the region. Urbanization destroys the vegetation cover within the developed areas and at about 5-10 km distance around them. The studied urbanized areas have the NDVI values by 15 to 45 % lower than the corresponding areas at 20-40 km distance. The largest NDVI reduction is typical for the newly developed areas, whereas the older areas show recovery of the vegetation cover. The study reveals a robust indication of the accelerated greening near the older urban areas. Many Siberian cities become greener even against the wider browning trends at their background. Literature discussion suggests that the observed urban greening could be associated not only with special tending of the within-city green areas but also with the urban heat islands and succession of more productive shrub and tree species growing on warmer sandy soils.

  13. Long-term change analysis of satellite-based evapotranspiration over Indian vegetated surface

    Science.gov (United States)

    Gupta, Shweta; Bhattacharya, Bimal K.; Krishna, Akhouri P.

    2016-05-01

    In the present study, trend of satellite based annual evapotranspiration (ET) and natural forcing factors responsible for this were analyzed. Thirty years (1981-2010) of ET data at 0.08° grid resolution, generated over Indian region from opticalthermal observations from NOAA PAL and MODIS AQUA satellites, were used. Long-term data on gridded (0.5° x 0.5°) annual rainfall (RF), annual mean surface soil moisture (SSM) ERS scatterometer at 25 km resolution and annual mean incoming shortwave radiation from MERRA-2D reanalysis were also analyzed. Mann-Kendall tests were performed with time series data for trend analysis. Mean annual ET loss from Indian ago-ecosystem was found to be almost double (1100 Cubic Km) than Indian forest ecosystem (550 Cubic Km). Rainfed vegetation systems such as forest, rainfed cropland, grassland showed declining ET trend @ - 4.8, -0.6 &-0.4 Cubic Kmyr-1, respectively during 30 years. Irrigated cropland initially showed ET decline upto 1995 @ -0.8 cubic Kmyr-1 which could possibly be due to solar dimming followed by increasing ET @ 0.9 cubic Kmyr-1 after 1995. A cross-over point was detected between forest ET decline and ET increase in irrigated cropland during 2008. During 2001-2010, the four agriculturally important Indian states eastern, central, western and southern showed significantly increasing ET trend with S-score of 15-25 and Z-score of 1.09-2.9. Increasing ET in western and southern states was found to be coupled with increase in annual rainfall and SSM. But in eastern and central states no significant trend in rainfall was observed though significant increase in ET was noticed. The study recommended to investigate the influence of anthropogenic factors such as increase in area under irrigation, increased use of water for irrigation through ground water pumping, change in cropping pattern and cultivars on increasing ET.

  14. THE NUMBER OF TIDAL DWARF SATELLITE GALAXIES IN DEPENDENCE OF BULGE INDEX

    Energy Technology Data Exchange (ETDEWEB)

    López-Corredoira, Martín [Instituto de Astrofísica de Canarias, E-38205 La Laguna, Tenerife (Spain); Kroupa, Pavel, E-mail: martinlc@iac.es, E-mail: pavel@astro.uni-bonn.de [Helmholtz-Institut für Strahlen- und Kernphysik, Universität Bonn, Nussallee 14-16, D-53115 Bonn (Germany)

    2016-01-20

    We show that a significant correlation (up to 5σ) emerges between the bulge index, defined to be larger for a larger bulge/disk ratio, in spiral galaxies with similar luminosities in the Galaxy Zoo 2 of the Sloan Digital Sky Survey and the number of tidal-dwarf galaxies in the catalog by Kaviraj et al. In the standard cold or warm dark matter cosmological models, the number of satellite galaxies correlates with the circular velocity of the dark matter host halo. In generalized gravity models without cold or warm dark matter, such a correlation does not exist, because host galaxies cannot capture infalling dwarf galaxies due to the absence of dark-matter-induced dynamical friction. However, in such models, a correlation is expected to exist between the bulge mass and the number of satellite galaxies because bulges and tidal-dwarf satellite galaxies form in encounters between host galaxies. This is not predicted by dark matter models in which bulge mass and the number of satellites are a priori uncorrelated because higher bulge/disk ratios do not imply higher dark/luminous ratios. Hence, our correlation reproduces the prediction of scenarios without dark matter, whereas an explanation is not found readily from the a priori predictions of the standard scenario with dark matter. Further research is needed to explore whether some application of the standard theory may explain this correlation.

  15. The number of tidal dwarf satellite galaxies in dependence of bulge index

    CERN Document Server

    Lopez-Corredoira, Martin

    2015-01-01

    We show that a significant correlation (up to 5sigma) emerges between the bulge index, defined to be larger for larger bulge/disk ratio, in spiral galaxies with similar luminosities in the Galaxy Zoo 2 of SDSS and the number of tidal-dwarf galaxies in the catalogue by Kaviraj et al. (2012). In the standard cold or warm dark-matter cosmological models the number of satellite galaxies correlates with the circular velocity of the dark matter host halo. In generalized-gravity models without cold or warm dark matter such a correlation does not exist, because host galaxies cannot capture in-falling dwarf galaxies due to the absence of dark-matter-induced dynamical friction. However, in such models a correlation is expected to exist between the bulge mass and the number of satellite galaxies, because bulges and tidal-dwarf satellite galaxies form in encounters between host galaxies. This is not predicted by dark matter models in which bulge mass and the number of satellites are a priori uncorrelated because higher b...

  16. Assessing plant senescence reflectance index-retrieved vegetation phenology and its spatiotemporal response to climate change in the Inner Mongolian Grassland

    Science.gov (United States)

    Ren, Shilong; Chen, Xiaoqiu; An, Shuai

    2016-08-01

    Plant phenology is a key link for controlling interactions between climate change and biogeochemical cycles. Satellite-derived normalized difference vegetation index (NDVI) has been extensively used to detect plant phenology at regional scales. Here, we introduced a new vegetation index, plant senescence reflectance index (PSRI), and determined PSRI-derived start (SOS) and end (EOS) dates of the growing season using Moderate Resolution Imaging Spectroradiometer data from 2000 to 2011 in the Inner Mongolian Grassland. Then, we validated the reliability of PSRI-derived SOS and EOS dates using NDVI-derived SOS and EOS dates. Moreover, we conducted temporal and spatial correlation analyses between PSRI-derived SOS/EOS date and climatic factors and revealed spatiotemporal patterns of PSRI-derived SOS and EOS dates across the entire research region at pixel scales. Results show that PSRI has similar performance with NDVI in extracting SOS and EOS dates in the Inner Mongolian Grassland. Precipitation regime is the key climate driver of interannual variation of grassland phenology, while temperature and precipitation regimes are the crucial controlling factors of spatial differentiation of grassland phenology. Thus, PSRI-derived vegetation phenology can effectively reflect land surface vegetation dynamics and its response to climate change. Moreover, a significant linear trend of PSRI-derived SOS and EOS dates was detected only at small portions of pixels, which is consistent with that of greenup and brownoff dates of herbaceous plant species in the Inner Mongolian Grassland. Overall, PSRI is a useful and robust metric in addition to NDVI for monitoring land surface grassland phenology.

  17. Assessing plant senescence reflectance index-retrieved vegetation phenology and its spatiotemporal response to climate change in the Inner Mongolian Grassland

    Science.gov (United States)

    Ren, Shilong; Chen, Xiaoqiu; An, Shuai

    2017-04-01

    Plant phenology is a key link for controlling interactions between climate change and biogeochemical cycles. Satellite-derived normalized difference vegetation index (NDVI) has been extensively used to detect plant phenology at regional scales. Here, we introduced a new vegetation index, plant senescence reflectance index (PSRI), and determined PSRI-derived start (SOS) and end (EOS) dates of the growing season using Moderate Resolution Imaging Spectroradiometer data from 2000 to 2011 in the Inner Mongolian Grassland. Then, we validated the reliability of PSRI-derived SOS and EOS dates using NDVI-derived SOS and EOS dates. Moreover, we conducted temporal and spatial correlation analyses between PSRI-derived SOS/EOS date and climatic factors and revealed spatiotemporal patterns of PSRI-derived SOS and EOS dates across the entire research region at pixel scales. Results show that PSRI has similar performance with NDVI in extracting SOS and EOS dates in the Inner Mongolian Grassland. Precipitation regime is the key climate driver of interannual variation of grassland phenology, while temperature and precipitation regimes are the crucial controlling factors of spatial differentiation of grassland phenology. Thus, PSRI-derived vegetation phenology can effectively reflect land surface vegetation dynamics and its response to climate change. Moreover, a significant linear trend of PSRI-derived SOS and EOS dates was detected only at small portions of pixels, which is consistent with that of greenup and brownoff dates of herbaceous plant species in the Inner Mongolian Grassland. Overall, PSRI is a useful and robust metric in addition to NDVI for monitoring land surface grassland phenology.

  18. Assessing plant senescence reflectance index-retrieved vegetation phenology and its spatiotemporal response to climate change in the Inner Mongolian Grassland.

    Science.gov (United States)

    Ren, Shilong; Chen, Xiaoqiu; An, Shuai

    2017-04-01

    Plant phenology is a key link for controlling interactions between climate change and biogeochemical cycles. Satellite-derived normalized difference vegetation index (NDVI) has been extensively used to detect plant phenology at regional scales. Here, we introduced a new vegetation index, plant senescence reflectance index (PSRI), and determined PSRI-derived start (SOS) and end (EOS) dates of the growing season using Moderate Resolution Imaging Spectroradiometer data from 2000 to 2011 in the Inner Mongolian Grassland. Then, we validated the reliability of PSRI-derived SOS and EOS dates using NDVI-derived SOS and EOS dates. Moreover, we conducted temporal and spatial correlation analyses between PSRI-derived SOS/EOS date and climatic factors and revealed spatiotemporal patterns of PSRI-derived SOS and EOS dates across the entire research region at pixel scales. Results show that PSRI has similar performance with NDVI in extracting SOS and EOS dates in the Inner Mongolian Grassland. Precipitation regime is the key climate driver of interannual variation of grassland phenology, while temperature and precipitation regimes are the crucial controlling factors of spatial differentiation of grassland phenology. Thus, PSRI-derived vegetation phenology can effectively reflect land surface vegetation dynamics and its response to climate change. Moreover, a significant linear trend of PSRI-derived SOS and EOS dates was detected only at small portions of pixels, which is consistent with that of greenup and brownoff dates of herbaceous plant species in the Inner Mongolian Grassland. Overall, PSRI is a useful and robust metric in addition to NDVI for monitoring land surface grassland phenology.

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

    Science.gov (United States)

    Zhang, Xiaoyang; Tan, Bin; Yu, Yunyue

    2014-05-01

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

  20. Interannual Variations and Trends in Global Land Surface Phenology Derived from Enhanced Vegetation Index During 1982-2010

    Science.gov (United States)

    Zhang, Xiaoyang; Tan, Bin; Yu, Yunyue

    2014-01-01

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

  1. Characterizing Spatial-Temporal Variations in Vegetation Phenology over the North-South Transect of Northeast Asia Based upon the MERIS Terrestrial Chlorophyll Index

    Directory of Open Access Journals (Sweden)

    Jiaxin Jin

    2012-01-01

    Full Text Available This study attempted to establish a broad regional phenological pattern for Northeast Asia using time-series data of the satellite measured index of terrestrial chlorophyll content (MERIS Terrestrial Chlorophyll Index from 2003 to 2007. A suite of phenological variables were extracted from 4 integral seasons of time-series Medium Resolution Imaging Spectrometer (MERIS Terrestrial Chlorophyll Index (MTCI of World Wildlife Fund (WWF ecoregions smoothed by an asymmetric Gaussian model. In this study, spatial variation with latitude was observed for the chlorophyll content and phenological variables for natural vegetation across north-south transect of northeast Asia (NSTNEA. The onset of greenness for most ecoregions followed a latitudinal pattern with an earlier onset of greenness at lower latitudes. In general, the length of growing season was higher at lower latitudes. For forests in NSTNEA, the average maximum MTCI value and range of MTCI value at lower latitudes were significantly larger than that at higher latitudes during the study period. In addition, the cumulative CV showed a declining trend with an increase in latitude overall. Our findings suggest that although precipitation plays a promoting role, temperature is still the dominant factor in vegetation phenological period at high latitudes.

  2. 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

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

    Science.gov (United States)

    Li, Zheng; Zhou, Tao; Zhao, Xiang; Huang, Kaicheng; Gao, Shan; Wu, Hao; Luo, Hui

    2015-07-08

    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.

  4. A One-Layer Satellite Surface Energy Balance for Estimating Evapotranspiration Rates and Crop Water Stress Indexes

    Directory of Open Access Journals (Sweden)

    Salvatore Barbagallo

    2009-01-01

    Full Text Available Daily evapotranspiration fluxes over the semi-arid Catania Plain area (Eastern Sicily, Italy were evaluated using remotely sensed data from Landsat Thematic Mapper TM5 images. A one-source parameterization of the surface sensible heat flux exchange using satellite surface temperature has been used. The transfer of sensible and latent heat is described by aerodynamic resistance and surface resistance. Required model inputs are brightness, temperature, fractional vegetation cover or leaf area index, albedo, crop height, roughness lengths, net radiation, air temperature, air humidity and wind speed. The aerodynamic resistance (rah is formulated on the basis of the Monin-Obukhov surface layer similarity theory and the surface resistance (rs is evaluated from the energy balance equation. The instantaneous surface flux values were converted into evaporative fraction (EF over the heterogeneous land surface to derive daily evapotranspiration values. Remote sensing-based assessments of crop water stress (CWSI were also made in order to identify local irrigation requirements. Evapotranspiration data and crop coefficient values obtained from the approach were compared with: (i data from the semi-empirical approach “Kc reflectance-based”, which integrates satellite data in the visible and NIR regions of the electromagnetic spectrum with ground-based measurements and (ii surface energy flux measurements collected from a micrometeorological tower located in the experiment area. The expected variability associated with ET flux measurements suggests that the approach-derived surface fluxes were in acceptable agreement with the observations.

  5. Feasibility to Detect Signs of Potential CO2 Leakage with Multi-Temporal SPOT Satellite Vegetation Imagery in Otway, Victoria

    Science.gov (United States)

    Cholathat, R.; Ge, L.; Li, X.; Hu, Z.

    2012-07-01

    This paper presents image processing results for the OtwayCO2storage site, a demonstration project of CO2 sequestration in south-western Victoria, Australia. These results were derived from SPOT-VGT S10 datasets of 2001 to mid 2011. Over 65,000 tonnes of CO2-rich gas stream was injected into a depleted gas reservoir at a depth of 2050 meters at the site since 2008. Over time, CO2 migration up-dip within the 31 m thick reservoir sandstone capped by the impervious thick seal rock has been recorded. But no top soil contamination has been discovered. This study has analysed the site vegetation growth using NDVI as a measure on a pixel by pixel basis. The multi-year time series result shows that NDVI values at the site regularly vary according to the seasons. Furthermore, precipitation levels were fluctuating in the past 10 years, especially in the years of 2002 and 2006, which correlated with low NDVI measuring results. But there are detected hot spots that cannot be linked with rainfall. Authors have found that some hot spots correspond with site well drilling and pipelines construction periods and locations. While others might be due to image data biased. Therefore, certain low NDVI spikes in the temporal evolution results cannot be attributed to only drought or pasture grazing. These subtle changes detected in the NDVI index prove the ability to use satellite image for providing valuable information to decision makers in relation to CO2 sequestration site environmental safety monitoring for searching CO2 leakage signals.

  6. Long-term energy balance and vegetation water stress monitoring of Mediterranean oak savanna using satellite thermal data

    Science.gov (United States)

    González-Dugo, Maria P.; Chen, Xuelong; Andreu, Ana; Carpintero, Elisabet; Gómez-Giraldez, Pedro; Su, Z.(Bob)

    2017-04-01

    Drought is one of the major hazards faced by natural and cropped vegetation in the Mediterranean Sea Basin. Water scarcity is likely to be worsened under the predicted conditions of climate change, which is expected to make this region both warmer and drier. A Holm oak savanna, known as dehesa in Spain and montado in Portugal, is an agro-silvo-pastoral system occupying more than 3 million hectares the Iberian Peninsula and Greece. It consists of widely-spaced oak trees (mostly Quercus ilex L.), combined with crops, pasture and Mediterranean shrubs. This ecosystem is considered an example of sustainable land use, supporting a large number of species and diversity of habitats and for its importance in rural economy. A similar ecosystem is worldwide distributed in areas with Mediterranean climate (as California or South Africa) and shares structural and functional properties with tropical savannas in Africa, Australia and South America. Remote sensing time series can assist the monitoring of the energy balance components, with special attention to the evapotranspiration and vegetation water stress over these areas. Long-term data analysis may improve our understanding of the functioning of the system, helping to assess drought impacts and leading to reduce the economic and environmental vulnerability of this ecosystem. This work analyzes the evolution the surface energy balance components, mapping the evapotranspiration and moisture stress of holm oak woodlands of Spain and Portugal during the last 15 years (2001-2015). The surface energy balance model (SEBS) has been applied over the Iberian Peninsula on a monthly time scale and 0.05° spatial resolution, using multi-satellite and meteorological forcing data. Modelled energy and water fluxes have been validated using ground measurements of two eddy covariance towers located in oak savanna sites during 3 years, resulting in moderate deviations from observations (10-25 W/m2). The departure of actual ET from the

  7. Evaluating an Enhanced Vegetation Condition Index (VCI Based on VIUPD for Drought Monitoring in the Continental United States

    Directory of Open Access Journals (Sweden)

    Wenzhe Jiao

    2016-03-01

    Full Text Available Drought is a complex hazard, and it has an impact on agricultural, ecological, and socio-economic systems. The vegetation condition index (VCI, which is derived from remote-sensing data, has been widely used for drought monitoring. However, VCI based on the normalized difference vegetation index (NDVI does not perform well in certain circumstances. In this study, we examined the utility of the vegetation index based on the universal pattern decomposition method (VIUPD based VCI for drought monitoring in various climate divisions across the continental United States (CONUS. We compared the VIUPD-derived VCI with the NDVI-derived VCI in various climate divisions and during different sub-periods of the growing season. It was also compared with other remote-sensing-based drought indices, such as the temperature condition index (TCI, precipitation condition index (PCI and the soil moisture condition index (SMCI. The VIUPD-derived VCI had stronger correlations with long-term in situ drought indices, such as the Palmer Drought Severity Index (PDSI and the standardized precipitation index (SPI-3, SPI-6, SPI-9, and SPI-12 than did the NDVI-derived VCI, and other indices, such as TCI, PCI and SMCI. The VIUPD has considerable potential for drought monitoring. As VIUPD can make use of the information from all the observation bands, the VIUPD-derived VCI can be regarded as an enhanced VCI.

  8. Global assessment of Vegetation Index and Phenology Lab (VIP and Global Inventory Modeling and Mapping Studies (GIMMS version 3 products

    Directory of Open Access Journals (Sweden)

    M. Marshall

    2015-06-01

    Full Text Available Earth observation based long-term global vegetation index products are used by scientists from a wide range of disciplines concerned with global change. Inter-comparison studies are commonly performed to keep the user community informed on the consistency and accuracy of such records as they evolve. In this study, we compared two new records: (1 Global Inventory Modeling and Mapping Studies (GIMMS Normalized Difference Vegetation Index Version 3 (NDVI3g and (2 Vegetation Index and Phenology Lab (VIP Version 3 NDVI (NDVI3v and Enhanced Vegetation Index 2 (EVI3v. We evaluated the two records via three experiments that addressed the primary use of such records in global change research: (1 prediction of the Leaf Area Index (LAI used in light-use efficiency modeling, (2 estimation of vegetation climatology in Soil-Vegetation-Atmosphere Transfer models, and (3 trend analysis of the magnitude and phenology of vegetation productivity. Experiment one, unlike previous inter-comparison studies, was performed with a unique Landsat 30 m spatial resolution and in situ LAI database for major crop types on five continents. Overall, the two records showed a high level of agreement both in direction and magnitude on a monthly basis, though VIP values were higher and more variable and showed lower correlations and higher error with in situ LAI. The records were most consistent at northern latitudes during the primary growing season and southern latitudes and the tropics throughout much of the year, while the records were less consistent at northern latitudes during green-up and senescence and in the great deserts of the world throughout much of the year. The two records were also highly consistent in terms of trend direction/magnitude, showing a 30+ year increase (decrease in NDVI over much of the globe (tropical rainforests. The two records were less consistent in terms of timing due to the poor correlation of the records during start and end of growing season.

  9. Characterising Vegetation Structural and Functional Differences Across Australian Ecosystems From a Network of Terrestrial Laser Scanning Survey Sites and Airborne and Satellite Image Archives

    Science.gov (United States)

    Phinn, S. R.; Armston, J.; Scarth, P.; Johansen, K.; Schaefer, M.; Suarez, L.; Soto-Berelov, M.; Muir, J.; Woodgate, W.; Jones, S.; Held, A. A.

    2015-12-01

    Vegetation structural information is critical for environmental monitoring, management and compliance assessment. In this context we refer to vegetation structural properties as vertical, horizontal and volumetric dimensions, including: canopy height; amount and distribution of vegetation by height; foliage projective cover (FPC); leaf area index (LAI); and above ground biomass. Our aim was to determine if there were significant differences between vegetation structural properties across 11 ecosystem types in Australia as measured by terrestrial laser scanner (TLS) structure metrics. The ecosystems sampled included: mesophyll vineforest, wet-dry tropical savannah, mallee woodland, subtropical eucalypt forest, mulga woodland/grassland, wet eucalypt forest, dry eucalypt forest, tall and wet eucalypt forest, and desert grassland/shrublands. Canopy height, plant area-height profiles and LAI were calculated from consistently processed TLS data using Australia's Terrestrial Ecosystem Research Network's (TERN) Supersites by the TERN AusCover remote sensing field teams from 2012-2015. The Supersites were sampled using standardised field protocols within a core set of 1 ha plots as part of a 5 km x 5 km uniform area using a RIEGL-VZ400 waveform recording TLS. Four to seven scans were completed per plot, with one centre point and then at 25 m away from the centre point along transect lines at 0o, 60o and 240o. Individual foliage profiles were sensitive to spatial variation in the distribution of plant materials. Significant differences were visible between each of the vegetation communities assessed when aggregated to plot and ecosystem type scales. Several of the communities exhibited simple profiles with either grass and shrubs (e.g. desert grassland) or grass and trees (e.g. mallee woodland). Others had multiple vegetation forms at different heights, contributing to the profile (e.g. wet eucalypt forest). The TLS data provide significantly more detail about the relative

  10. Vegetation mapping from high-resolution satellite images in the heterogeneous arid environments of Socotra Island (Yemen)

    Science.gov (United States)

    Malatesta, Luca; Attorre, Fabio; Altobelli, Alfredo; Adeeb, Ahmed; De Sanctis, Michele; Taleb, Nadim M.; Scholte, Paul T.; Vitale, Marcello

    2013-01-01

    Socotra Island (Yemen), a global biodiversity hotspot, is characterized by high geomorphological and biological diversity. In this study, we present a high-resolution vegetation map of the island based on combining vegetation analysis and classification with remote sensing. Two different image classification approaches were tested to assess the most accurate one in mapping the vegetation mosaic of Socotra. Spectral signatures of the vegetation classes were obtained through a Gaussian mixture distribution model, and a sequential maximum a posteriori (SMAP) classification was applied to account for the heterogeneity and the complex spatial pattern of the arid vegetation. This approach was compared to the traditional maximum likelihood (ML) classification. Satellite data were represented by a RapidEye image with 5 m pixel resolution and five spectral bands. Classified vegetation relevés were used to obtain the training and evaluation sets for the main plant communities. Postclassification sorting was performed to adjust the classification through various rule-based operations. Twenty-eight classes were mapped, and SMAP, with an accuracy of 87%, proved to be more effective than ML (accuracy: 66%). The resulting map will represent an important instrument for the elaboration of conservation strategies and the sustainable use of natural resources in the island.

  11. Quantifying winter wheat residue biomass with a spectral angle index derived from China Environmental Satellite data

    Science.gov (United States)

    Zhang, Miao; Wu, Bingfang; Meng, Jihua

    2014-10-01

    Quantification of crop residue biomass on cultivated lands is essential for studies of carbon cycling of agroecosystems, soil-atmospheric carbon exchange and Earth systems modeling. Previous studies focus on estimating crop residue cover (CRC) while limited research exists on quantifying crop residue biomass. This study takes advantage of the high temporal resolution of the China Environmental Satellite (HJ-1) data and utilizes the band configuration features of HJ-1B data to establish spectral angle indices to estimate crop residue biomass. Angles formed at the NIRIRS vertex by the three vertices at R, NIRIRS, and SWIR (ANIRIRS) of HJ-1B can effectively indicate winter wheat residue biomass. A coefficient of determination (R2) of 0.811 was obtained between measured winter wheat residue biomass and ANIRIRS derived from simulated HJ-1B reflectance data. The ability of ANIRIRS for quantifying winter wheat residue biomass using HJ-1B satellite data was also validated and evaluated. Results indicate that ANIRIRS performed well in estimating winter wheat residue biomass with different residue treatments; the root mean square error (RMSE) between measured and estimated residue biomass was 0.038 kg/m2. ANIRIRS is a potential method for quantifying winter wheat residue biomass at a large scale due to wide swath width (350 km) and four-day revisit rate of the HJ-1 satellite. While ANIRIRS can adequately estimate winter wheat residue biomass at different residue moisture conditions, the feasibility of ANIRIRS for winter wheat residue biomass estimation at different fractional coverage of green vegetation and different environmental conditions (soil type, soil moisture content, and crop residue type) needs to be further explored.

  12. Analysis of the changes in vegetation of the Sapanca Lake Basin (in Turkey using multitemporal satellite data

    Directory of Open Access Journals (Sweden)

    Cercis İkiel

    2015-04-01

    Full Text Available The Lake Sapanca Basin is located in an area where urbanization and industrialization is rapidly increasing because of its geographical location. The Sapanca Lake Basin was opened to settlement densely after 1980 due to recreational activities for urbanization and industrialization. The aim of this study is to investigate and evaluate the changes in natural vegetation and settlement caused by the effects of human activities in the Sapanca Lake Basin. For this purpose, Landsat 5 TM (1987 and Landsat 8 (2013 satellite images have been used. These images have been analyzed using ERDAS and ArcGIS software’s and this was supported and confirmed by the carried land studies. The results showed that there has been an % 12.8 decrease in the high density green vegetation areas. It is concluded that the natural vegetation of Sapanca Lake Basin damaged rapidly in the period between the years of 1987-2013.

  13. 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.

  14. Modelling spatial and temporal vegetation variability with the Climate Constrained Vegetation Index: evidence of CO2 fertilisation and of water stress in continental interiors

    Directory of Open Access Journals (Sweden)

    S. O. Los

    2015-06-01

    Full Text Available A model was developed to simulate spatial, seasonal and interannual variations in vegetation in response to temperature, precipitation and atmospheric CO2 concentrations; the model addresses shortcomings in current implementations. The model uses the minimum of 12 temperature and precipitation constraint functions to simulate NDVI. Functions vary based on the Köppen–Trewartha climate classification to take adaptations of vegetation to climate into account. The simulated NDVI, referred to as the climate constrained vegetation index (CCVI, captured the spatial variability (0.82 r r = 0.83 and interannual variability (median global r = 0.24 in NDVI. The CCVI simulated the effects of adverse climate on vegetation during the 1984 drought in the Sahel and during dust bowls of the 1930s and 1950s in the Great Plains in North America. A global CO2 fertilisation effect was found in NDVI data, similar in magnitude to that of earlier estimates (8 % for the 20th century. This effect increased linearly with simple ratio, a transformation of the NDVI. Three CCVI scenarios, based on climate simulations using the representative concentration pathway RCP4.5, showed a greater sensitivity of vegetation towards precipitation in Northern Hemisphere mid latitudes than is currently implemented in climate models. This higher sensitivity is of importance to assess the impact of climate variability on vegetation, in particular on agricultural productivity.

  15. Evaluating the difference between the normalized difference vegetation index and net primary productivity as the indicators of vegetation vigor assessment at landscape scale.

    Science.gov (United States)

    Xu, Chi; Li, Yutong; Hu, Jian; Yang, Xuejiao; Sheng, Sheng; Liu, Maosong

    2012-03-01

    Both the net primary productivity (NPP) and the normalized difference vegetation index (NDVI) are commonly used as indicators to characterize vegetation vigor, and NDVI has been used as a surrogate estimator of NPP in some cases. To evaluate the reliability of such surrogation, here we examined the quantitative difference between NPP and NDVI in their outcomes of vegetation vigor assessment at a landscape scale. Using Landsat ETM+ data and a process model, the Boreal Ecosystem Productivity Simulator, NPP distribution was mapped at a resolution of 90 m, and total NDVI during the growing season was calculated in Heihe River Basin, Northwest China in 2002. The results from a comparison between the NPP and NDVI classification maps show that there existed a substantial difference in terms of both area and spatial distribution between the assessment outcomes of these two indicators, despite that they are strongly correlated. The degree of difference can be influenced by assessment schemes, as well as the type of vegetation and ecozone. Overall, NDVI is not a good surrogate of NPP as the indicators of vegetation vigor assessment in the study area. Nonetheless, NDVI could serve as a fairish surrogate indicator under the condition that the target region has low vegetation cover and the assessment has relatively coarse classification schemes (i.e., the class number is small). It is suggested that the use of NPP and NDVI should be carefully selected in landscape assessment. Their differences need to be further evaluated across geographic areas and biomes.

  16. Improving the representation of fire disturbance in dynamic vegetation models by assimilating satellite data

    Science.gov (United States)

    Kantzas, E. P.; Quegan, S.; Lomas, M.

    2015-03-01

    Fire provides an impulsive and stochastic pathway for carbon from the terrestrial biosphere to enter the atmosphere. Despite fire emissions being of similar magnitude to Net Ecosystem Exchange in many biomes, even the most complex Dynamic Vegetation Models (DVMs) embedded in General Circulation Models contain poor representations of fire behaviour and dynamics such as propagation and distribution of fire sizes. A model-independent methodology is developed which addresses this issue. Its focus is on the Arctic where fire is linked to permafrost dynamics and on occasion can release great amounts of carbon from carbon-rich organic soils. Connected Component Labeling is used to identify individual fire events across Canada and Russia from daily, low-resolution burned area satellite products, and the results are validated against historical data. This allows the creation of a fire database holding information on area burned and temporal evolution of fires in space and time. A method of assimilating the statistical distribution of fire area into a DVM whilst maintaining its Fire Return Interval is then described. The algorithm imposes a regional scale spatially dependent fire regime on a sub-scale spatially independent model (point model); the fire regime is described by large scale statistical distributions of fire intensity and spatial extent, and the temporal dynamics (fire return intervals) are determined locally. This permits DVMs to estimate many aspects of post-fire dynamics that cannot occur under their current representations of fire, as is illustrated by considering the evolution of land cover, biomass and Net Ecosystem Exchange after a fire.

  17. From Satellite Imagery to Peatland Vegetation Diversity: How Reliable Are Habitat Maps?

    Directory of Open Access Journals (Sweden)

    Monique F. Poulin

    2002-12-01

    Full Text Available Although satellite imagery is becoming a basic component of the work of ecologists and conservationists, its potential and reliability are still relatively unknown for a large number of ecosystems. Using Landsat 7/ETM+ (Enhanced Thematic Mapper Plus data, we tested the accuracy of two types of supervised classifications for mapping 13 peatland habitats in southern Quebec, Canada. Before classifying peatland habitats, we applied a mask procedure that revealed 629 peatlands covering a total of 18,103 ha; 26% of them were larger than 20 ha. We applied both a simple maximum likelihood (ML function and a weighted maximum likelihood (WML function that took into account the proportion of each habitat class within each peatland when classifying the habitats on the image. By validating 626 Global Positioning System locations within 92 peatlands, we showed that both classification procedures provided an accurate representation of the 13 peatland habitat classes. For all habitat classes except lawn with pools, the predominant classified habitat within 45 m of the center of the validation location was of the same type as the one observed in the field. There were differences in the performance of the two classification procedures: ML was a better tool for mapping rare habitats, whereas WML favored the most common habitats. Based on ordinations, peatland habitat classes were as effective as environmental variables such as humidity indicators and water chemistry components at explaining the distribution of plant species and performed 1.6 times better when it came to accounting for vegetation structure patterns. Peatland habitats with pools had the most distinct plant assemblages, and the habitats dominated by herbs were moderately distinct from those characterized by ericaceous shrubs. Habitats dominated by herbs were the most variable in terms of plant species assemblages. Because peatlands are economically valuable wetlands, the maps resulting from the new

  18. Improving the representation of fire disturbance in dynamic vegetation models by assimilating satellite data

    Directory of Open Access Journals (Sweden)

    E. P. Kantzas

    2015-03-01

    Full Text Available Fire provides an impulsive and stochastic pathway for carbon from the terrestrial biosphere to enter the atmosphere. Despite fire emissions being of similar magnitude to Net Ecosystem Exchange in many biomes, even the most complex Dynamic Vegetation Models (DVMs embedded in General Circulation Models contain poor representations of fire behaviour and dynamics such as propagation and distribution of fire sizes. A model-independent methodology is developed which addresses this issue. Its focus is on the Arctic where fire is linked to permafrost dynamics and on occasion can release great amounts of carbon from carbon-rich organic soils. Connected Component Labeling is used to identify individual fire events across Canada and Russia from daily, low-resolution burned area satellite products, and the results are validated against historical data. This allows the creation of a fire database holding information on area burned and temporal evolution of fires in space and time. A method of assimilating the statistical distribution of fire area into a DVM whilst maintaining its Fire Return Interval is then described. The algorithm imposes a regional scale spatially dependent fire regime on a sub-scale spatially independent model (point model; the fire regime is described by large scale statistical distributions of fire intensity and spatial extent, and the temporal dynamics (fire return intervals are determined locally. This permits DVMs to estimate many aspects of post-fire dynamics that cannot occur under their current representations of fire, as is illustrated by considering the evolution of land cover, biomass and Net Ecosystem Exchange after a fire.

  19. Temperature Vegetation Dryness Index Estimation of Soil Moisture under Different Tree Species

    Directory of Open Access Journals (Sweden)

    Shulin Chen

    2015-08-01

    Full Text Available The Laoshan forest is the largest forest in Nanjing, and it plays an important role in water resource management in Nanjing. The objectives of this study are to determine if the temperature vegetation dryness index (TVDI is suitable to estimate the soil moisture and if soil moisture is significantly affected by tree species in the Laoshan forest. This paper calculated the spatial distribution of TVDI using LANDSAT-5 TM data. Sixty-two observation points of in situ soil moisture measurements were selected to validate the effectiveness of the TVDI as an index for assessing soil moisture in the Laoshan forest. With the aid of the three different temporal patterns, which are 10 January 2011, 18 May 2011 and 23 September 2011, this paper used the TVDI to investigate the differences of soil moisture under four kinds of mono-species forests and two kinds of mixed forests. The results showed that there is a strong and significant negative correlation between the TVDI and the in situ measured soil moisture (R2 = 0.15–0.8, SE = 0.015–0.041 cm3/cm3. This means that the TVDI can reflect the soil moisture status under different tree species in the Laoshan forest. The soil moisture under these six types of land cover from low to high is listed in the following order: Eucommia ulmoides, Quercus acutissima, broadleaf mixed forest, Cunninghamia lanceolata, coniferous and broadleaf mixed forest and Pinus massoniana.

  20. Interannual Variability of the Normalized Difference Vegetation Index on the Tibetan Plateau and Its Relationship with Climate Change

    Institute of Scientific and Technical Information of China (English)

    ZHOU Dingwen; FAN Guangzhou; HUANG Ronghui; FANG Zhifang; LIU Yaqin; LI Hongquan

    2007-01-01

    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.

  1. 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

    change. The present study explores the benefits of combining vegetation index and physically based approaches for the spatial and temporal mapping of green leaf area index (LAI), total chlorophyll content (TCab), and total vegetation water content (VWC). A numerical optimization method was employed...... and computationally efficient VI approach makes the combined retrieval scheme for LAI, TCab, and VWC suitable for large-scale mapping operations. In order to facilitate application of the canopy reflectance model to heterogeneous forested areas, a simple correction scheme was elaborated, which was found to improve...... constituents without utilizing calibration measurements. Preliminary LAI validation results for the Island of Zealand, Denmark (57°N, 12°E) provided confidence in the approach with root mean square (RMS) deviations between estimates and in-situ measurements of 0.62, 0.46, and 0.63 for barley, wheat...

  2. Prognostic land surface albedo from a dynamic global vegetation model clumped canopy radiative transfer scheme and satellite-derived geographic forest heights

    Science.gov (United States)

    Kiang, N. Y.; Yang, W.; Ni-Meister, W.; Aleinov, I. D.; Jonas, J.

    2014-12-01

    Vegetation cover was introduced into general circulations models (GCMs) in the 1980's to account for the effect of land surface albedo and water vapor conductance on the Earth's climate. Schemes assigning canopy albedoes by broad biome type have been superceded in 1990's by canopy radiative transfer schemes for homogeneous canopies obeying Beer's Law extinction as a function of leaf area index (LAI). Leaf albedo and often canopy height are prescribed by plant functional type (PFT). It is recognized that this approach does not effectively describe geographic variation in the radiative transfer of vegetated cover, particularly for mixed and sparse canopies. GCM-coupled dynamic global vegetation models (DGVMs) have retained these simple canopy representations, with little further evaluation of their albedos. With the emergence lidar-derived canopy vertical structure data, DGVM modelers are now revisiting albedo simulation. We present preliminary prognostic global land surface albedo produced by the Ent Terrestrial Biosphere Model (TBM), a DGVM coupled to the NASA Goddard Institute for Space Studies (GISS) GCM. The Ent TBM is a next generation DGVM designed to incorporate variation in canopy heights, and mixed and sparse canopies. For such dynamically varying canopy structure, it uses the Analytical Clumped Two-Stream (ACTS) canopy radiative transfer model, which is derived from gap probability theory for canopies of tree cohorts with ellipsoidal crowns, and accounts for soil, snow, and bare stems. We have developed a first-order global vegetation structure data set (GVSD), which gives a year of satellite-derived geographic variation in canopy height, maximum canopy leaf area, and seasonal LAI. Combined with Ent allometric relations, this data set provides population density and foliage clumping within crowns. We compare the Ent prognostic albedoes to those of the previous GISS GCM scheme, and to satellite estimates. The impact of albedo differences on surface

  3. 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

  4. Application of Satellite Solar-Induced Chlorophyll Fluorescence to Understanding Large-Scale Variations in Vegetation Phenology and Function Over Northern High Latitude Forests

    Science.gov (United States)

    Jeong, Su-Jong; Schimel, David; Frankenberg, Christian; Drewry, Darren T.; Fisher, Joshua B.; Verma, Manish; Berry, Joseph A.; Lee, Jung-Eun; Joiner, Joanna

    2016-01-01

    This study evaluates the large-scale seasonal phenology and physiology of vegetation over northern high latitude forests (40 deg - 55 deg N) during spring and fall by using remote sensing of solar-induced chlorophyll fluorescence (SIF), normalized difference vegetation index (NDVI) and observation-based estimate of gross primary productivity (GPP) from 2009 to 2011. Based on GPP phenology estimation in GPP, the growing season determined by SIF time-series is shorter in length than the growing season length determined solely using NDVI. This is mainly due to the extended period of high NDVI values, as compared to SIF, by about 46 days (+/-11 days), indicating a large-scale seasonal decoupling of physiological activity and changes in greenness in the fall. In addition to phenological timing, mean seasonal NDVI and SIF have different responses to temperature changes throughout the growing season. We observed that both NDVI and SIF linearly increased with temperature increases throughout the spring. However, in the fall, although NDVI linearly responded to temperature increases, SIF and GPP did not linearly increase with temperature increases, implying a seasonal hysteresis of SIF and GPP in response to temperature changes across boreal ecosystems throughout their growing season. Seasonal hysteresis of vegetation at large-scales is consistent with the known phenomena that light limits boreal forest ecosystem productivity in the fall. Our results suggest that continuing measurements from satellite remote sensing of both SIF and NDVI can help to understand the differences between, and information carried by, seasonal variations vegetation structure and greenness and physiology at large-scales across the critical boreal regions.

  5. 遥感数字影像中提取植被指数并行算法的研究与实现%Research and Implementation of Parallel Algorithm for Extracting Vegetation Index in Remote Sensing Digital Image

    Institute of Scientific and Technical Information of China (English)

    于延; 王建华; 段喜萍

    2013-01-01

    In remote sensing processing, extracting vegetation index could be used to evaluate the coverage of vegetation or growth vitality quantitatively.Because of the increase of the projects for satellite observation and the increase of space time resolution induced by electronic technology, the materials of satellite remote sensing are growing exponentially.Traditional serial extracting vegetation index algorithms could not deal with huge amount of image materials efficiently.In this paper, we propose a parallel extracting vegetation index algorithm based on CUDA, this parallel algorithm could compute vegetation index efficiently and fast.The experimental results show that the algorithm proposed by this paper has a good speed-up comparing to the traditional algorithms, and has a low error.%在遥感影像处理中,植被指数的提取可以用来定性和定量评价植被覆盖及生长活力.由于现有的卫星观测项目的增多以及电子技术的进步引起的数据时空分辨率增加,获取的卫星遥感资料成指数级地增加.传统已有的串行的植被指数提取算法已经不能有效地处理大量的影像资料.本文提出了基于CUDA的并行植被指数提取算法.该并行算法可以快速、高效地计算植被指数.实验结果表明,本文提出的算法与传统的算法在时间上取得了很好的加速比,并且有很低的误差.

  6. The Seasonal Cycle of Satellite Chlorophyll Fluorescence Observations and its Relationship to Vegetation Phenology and Ecosystem Atmosphere Carbon Exchange

    Science.gov (United States)

    Joiner, J.; Yoshida, Y.; Vasilkov, A. P.; Schaefer, K.; Jung, M.; Guanter, L.; Zhang, Y; Garrity, S.; Middleton, E. M.; Huemmrich, K. F.; Gu, L.; Marchesini, L. Belelli

    2014-01-01

    Mapping of terrestrial chlorophyll uorescence from space has shown potentialfor providing global measurements related to gross primary productivity(GPP). In particular, space-based fluorescence may provide information onthe length of the carbon uptake period that can be of use for global carboncycle modeling. Here, we examine the seasonal cycle of photosynthesis asestimated from satellite fluorescence retrievals at wavelengths surroundingthe 740nm emission feature. These retrievals are from the Global OzoneMonitoring Experiment 2 (GOME-2) flying on the MetOp A satellite. Wecompare the fluorescence seasonal cycle with that of GPP as estimated froma diverse set of North American tower gas exchange measurements. Because the GOME-2 has a large ground footprint (40 x 80km2) as compared with that of the flux towers and requires averaging to reduce random errors, we additionally compare with seasonal cycles of upscaled GPP in the satellite averaging area surrounding the tower locations estimated from the Max Planck Institute for Biogeochemistry (MPI-BGC) machine learning algorithm. We also examine the seasonality of absorbed photosynthetically-active radiation(APAR) derived with reflectances from the MODerate-resolution Imaging Spectroradiometer (MODIS). Finally, we examine seasonal cycles of GPP as produced from an ensemble of vegetation models. Several of the data-driven models rely on satellite reflectance-based vegetation parameters to derive estimates of APAR that are used to compute GPP. For forested sites(particularly deciduous broadleaf and mixed forests), the GOME-2 fluorescence captures the spring onset and autumn shutoff of photosynthesis as delineated by the tower-based GPP estimates. In contrast, the reflectance-based indicators and many of the models tend to overestimate the length of the photosynthetically-active period for these and other biomes as has been noted previously in the literature. Satellite fluorescence measurements therefore show potential for

  7. [A novel vegetation index (MPRI) of corn canopy by vehicle-borne dynamic prediction].

    Science.gov (United States)

    Li, Shu-qiang; Li, Min-zan; Sun, Hong

    2014-06-01

    Ground-based remote sensing system is a significant way to understand the growth of corn and provide accurate and scientific data for precision agriculture. The vehicle-borne system is one of the most important tools for corn canopy monitoring. However, the vehicle-borne growth monitoring system cannot maintain steady operations due to the row spacing of corn. The reflectance of corn canopy, which was used to construct the model for the chlorophyll content, was disturbed by the reflectance of soil background. The background interference with the reflectance could not be removed effectively, which would result in a deviation in the growth monitoring. In order to overcome this problem, a novel vegetation index named MPRI was developed in the present paper. The tests were carried out by the vehicle-borne system on the cornfield. The sensors which configured the vehicle-borne system had 4 bands, being respectively 550, 650, 766 and 850 nm. It would obtain the spectral data while the vehicle moved along the row direction. The sampling rate was about 1 point per second. The GPS receiver obtained the location information at the same rate. MPRI was made up by the reflectance ratio of 660 and 550 nm. It was very effective to analyze the information about the reflectance of the canopy. The results of experiments showed that the MPRI of soil was the positive value and the MPRI of canopy was the negative value. So it is easier to distinguish the spectral information about soil and corn canopy by MPRI. The results indicated that: it had satisfactory forecasting accuracy for the chlorophyll content by using the MPRI on the moving monitoring. The R2 of the prediction model was about 0.72. The R2 Of the model of NDVI, which was used to represent the chlorophyll content, was only 0.24. It indicates that MPRI had good measurement results for the dynamic measurement process. It provided the novel measurement way to get the canopy reflectance spectra and the better vegetation index to

  8. Testing Shelter Index and a Simple Wind Speed Parameter to Characterize Vegetation Control of Sand Transport Threshold and Flux

    Science.gov (United States)

    Gillies, John; Nield, Joanna; Nickling, William; Furtak-Cole, Eden

    2013-04-01

    Wind erosion and dust emissions occur in the Chihuahuan Desert surrounding Las Cruces NM from a range of surfaces with different types and amounts of vegetation. Understanding how vegetation modulates these processes remains a research challenge. One important aspect of research is to develop a relationship between a descriptor of the surface roughness that can be used to provide an indication of how susceptible the sediment transport system is to activation by wind. Here we present results from a study that examines the relationship between an index of shelter (distance from a point to the nearest upwind vegetation/vegetation height), as originally proposed by Okin (2008), and particle threshold expressed as a ratio of wind measured at 0.45 times the plant height divided by the wind speed at 17 m, and saltation flux (g cm-2 s-1). Saltation flux was measured using sediment traps positioned 15 cm above the surface and nearby optical gate sensors (Wenglor® model YH03PCT8)measuring saltation activity also placed at a height of 15 cm. The results are used to evaluate shelter index as a parameter to characterize the local winds as influenced by the vegetation and sediment transport conditions (threshold and transport). Wind speed, wind direction, saltation activity and point saltation flux were measured at 35 locations in defined test areas (~13,000 m2) in three vegetation communities: mature mesquite covered nebkha dunes, incipient nebkha dunes dominated by low mesquite plants, and a mature creosote bush area. 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 approximately 10 degree wind direction bin using digital elevation models for each site acquired using terrestrial laser scanning.

  9. Physical Explanation on Designing Three Axes as Different Resolution Indexes from GRACE Satellite-Borne Accelerometer

    Institute of Scientific and Technical Information of China (English)

    ZHENG Wei; XU Hou-Ze; ZHONG Min; YUN Mei-Juan

    2008-01-01

    @@ The GRACE Earth's gravitational field complete up to degree and order 120 is recovered based on the same and different three-axis resolution indexes from satellite-borne accelerometer using the improved energy conservation principle. The results show that designing XA1(2) as low-sensitivity axis (3 × 10-9 m/s2) of accelerometer and designing YA1(2) and ZA1(2) as high-sensitivity axes (3 × 10-10m/s2) are reasonable. The physical reason why the resolution of XA1(2) is one order of magnitude lower than YA1(2) and ZA1(2) is that non-conservative forces acting on GRACE satellites axe mainly decomposed into YA1(2) and ZA1(2) in the orbital plane.Since X A1(2) is not orthogonal accurately to orbital plane during the development of accelerometer, the measurement of X A1(2) can not be thrown off entirely, but be reduced properly.

  10. Effects of Normalized Difference Vegetation Index and Related Wavebands' Characteristics on Detecting Spatial Heterogeneity Using Variogram-based Analysis

    Institute of Scientific and Technical Information of China (English)

    WEN Zhaofei; ZHANG Ce; ZHANG Shuqing; DING Changhong; LIU Chunyue; PAN Xin; LI Huapeng; SUN Yan

    2012-01-01

    Spatial heterogeneity is widely used in diverse applications,such as recognizing ecological process,guiding ecological restoration,managing land use,etc.Many researches have focused on the inherent scale multiplicity of spatial heterogeneity by using various environmental variables.How these variables affect their corresponding spatial heterogeneities,however,have received little attention.In this paper,we examined the effects of characteristics of normalized difference vegetation index (NDVI) and its related bands variable images,namely red and near infrared (NIR),on their corresponding spatial heterogeneity detection based on variogram models.In a coastal wetland region,two groups of study sites with distinct fractal vegetation cover were tested and analyzed.The results show that:1) in high fractal vegetation cover (H-FVC) area,NDVI and NIR variables display a similar ability in detecting the spatial heterogeneity caused by vegetation growing status structure; 2) in low fractal vegetation cover (L-FVC) area,the NIR and red variables outperform NDVI in the survey of soil spatial heterogeneity; and 3) generally,NIR variable is ubiquitously applicable for vegetation spatial heterogeneity investigation in different fractal vegetation covers.Moreover,as variable selection for remote sensing applications should fully take the characteristics of variables and the study object into account,the proposed variogram analysis method can make the variable selection objectively and scientifically,especially in studies related to spatial heterogeneity using remotely sensed data.

  11. Modeling water and heat balance components of large territory for vegetation season using information from polar-orbital and geostationary meteorological satellites

    Science.gov (United States)

    Muzylev, Eugene; Startseva, Zoya; Uspensky, Alexander; Volkova, Elena; Kukharsky, Alexander; Uspensky, Sergey

    2015-04-01

    To date, physical-mathematical modeling processes of land surface-atmosphere interaction is considered to be the most appropriate tool for obtaining reliable estimates of water and heat balance components of large territories. The model of these processes (Land Surface Model, LSM) developed for vegetation period is destined for simulating soil water content W, evapotranspiration Ev, vertical latent LE and heat fluxes from land surface as well as vertically distributed soil temperature and moisture, soil surface Tg and foliage Tf temperatures, and land surface skin temperature (LST) Ts. The model is suitable for utilizing remote sensing data on land surface and meteorological conditions. In the study these data have been obtained from measurements by scanning radiometers AVHRR/NOAA, MODIS/EOS Terra and Aqua, SEVIRI/geostationary satellites Meteosat-9, -10 (MSG-2, -3). The heterogeneity of the land surface and meteorological conditions has been taken into account in the model by using soil and vegetation characteristics as parameters and meteorological characteristics as input variables. Values of these characteristics have been determined from ground observations and remote sensing information. So, AVHRR data have been used to build the estimates of effective land surface temperature (LST) Ts.eff and emissivity E, vegetation-air temperature (temperature at the vegetation level) Ta, normalized vegetation index NDVI, vegetation cover fraction B, the leaf area index LAI, and precipitation. From MODIS data the values of LST Tls, Å, NDVI, LAI have been derived. From SEVIRI data there have been retrieved Tls, E, Ta, NDVI, LAI and precipitation. All named retrievals covered the vast territory of the part of the agricultural Central Black Earth Region located in the steppe-forest zone of European Russia. This territory with coordinates 49°30'-54°N, 31°-43°E and a total area of 227,300 km2 has been chosen for investigation. It has been carried out for years 2009

  12. Estimating Sugarcane Yield Potential Using an In-Season Determination of Normalized Difference Vegetative Index

    Directory of Open Access Journals (Sweden)

    Howard Viator

    2012-06-01

    Full Text Available Estimating crop yield using remote sensing techniques has proven to be successful. However, sugarcane possesses unique characteristics; such as, a multi-year cropping cycle and plant height-limiting for midseason fertilizer application timing. Our study objective was to determine if sugarcane yield potential could be estimated using an in-season estimation of normalized difference vegetative index (NDVI. Sensor readings were taken using the GreenSeeker® handheld sensor from 2008 to 2011 in St. Gabriel and Jeanerette, LA, USA. In-season estimates of yield (INSEY values were calculated by dividing NDVI by thermal variables. Optimum timing for estimating sugarcane yield was between 601–750 GDD. In-season estimated yield values improved the yield potential (YP model compared to using NDVI. Generally, INSEY value showed a positive exponential relationship with yield (r2 values 0.48 and 0.42 for cane tonnage and sugar yield, respectively. When models were separated based on canopy structure there was an increase the strength of the relationship for the erectophile varieties (r2 0.53 and 0.47 for cane tonnage and sugar yield, respectively; however, the model for planophile varieties weakened slightly. Results of this study indicate using an INSEY value for predicting sugarcane yield shows potential of being a valuable management tool for sugarcane producers in Louisiana.

  13. Estimating sugarcane yield potential using an in-season determination of normalized difference vegetative index.

    Science.gov (United States)

    Lofton, Josh; Tubana, Brenda S; Kanke, Yumiko; Teboh, Jasper; Viator, Howard; Dalen, Marilyn

    2012-01-01

    Estimating crop yield using remote sensing techniques has proven to be successful. However, sugarcane possesses unique characteristics; such as, a multi-year cropping cycle and plant height-limiting for midseason fertilizer application timing. Our study objective was to determine if sugarcane yield potential could be estimated using an in-season estimation of normalized difference vegetative index (NDVI). Sensor readings were taken using the GreenSeeker® handheld sensor from 2008 to 2011 in St. Gabriel and Jeanerette, LA, USA. In-season estimates of yield (INSEY) values were calculated by dividing NDVI by thermal variables. Optimum timing for estimating sugarcane yield was between 601-750 GDD. In-season estimated yield values improved the yield potential (YP) model compared to using NDVI. Generally, INSEY value showed a positive exponential relationship with yield (r(2) values 0.48 and 0.42 for cane tonnage and sugar yield, respectively). When models were separated based on canopy structure there was an increase the strength of the relationship for the erectophile varieties (r(2) 0.53 and 0.47 for cane tonnage and sugar yield, respectively); however, the model for planophile varieties weakened slightly. Results of this study indicate using an INSEY value for predicting sugarcane yield shows potential of being a valuable management tool for sugarcane producers in Louisiana.

  14. 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.

  15. [Kriging analysis of vegetation index depression in peak cluster karst area].

    Science.gov (United States)

    Yang, Qi-Yong; Jiang, Zhong-Cheng; Ma, Zu-Lu; Cao, Jian-Hua; Luo, Wei-Qun; Li, Wen-Jun; Duan, Xiao-Fang

    2012-04-01

    In order to master the spatial variability of the normal different vegetation index (NDVI) of the peak cluster karst area, taking into account the problem of the mountain shadow "missing" information of remote sensing images existing in the karst area, NDVI of the non-shaded area were extracted in Guohua Ecological Experimental Area, in Pingguo County, Guangxi applying image processing software, ENVI. The spatial variability of NDVI was analyzed applying geostatistical method, and the NDVI of the mountain shadow areas was predicted and validated. The results indicated that the NDVI of the study area showed strong spatial variability and spatial autocorrelation resulting from the impact of intrinsic factors, and the range was 300 m. The spatial distribution maps of the NDVI interpolated by Kriging interpolation method showed that the mean of NDVI was 0.196, apparently strip and block. The higher NDVI values distributed in the area where the slope was greater than 25 degrees of the peak cluster area, while the lower values distributed in the area such as foot of the peak cluster and depression, where slope was less than 25 degrees. Kriging method validation results show that interpolation has a very high prediction accuracy and could predict the NDVI of the shadow area, which provides a new idea and method for monitoring and evaluation of the karst rocky desertification.

  16. Assessment of Iranian Agroclimatological Zone Classification by Using TVDI (Temperature Vegetation Dryness Index)

    Science.gov (United States)

    Asadi, Ebrahim; Lopez-Baeza, Ernesto; Coll Pajaron, M. Amparo; Kouzehgaran, Saeedeh; Haghighat, Masoud

    2016-07-01

    Agricultural zoning is an important tool for authorities to plan and decide about development of the agricultural sector, environmental sustainability issues and plan and provide irrigation and rural infrastructures. Previous different methods have suggested the definition of agroclimatological zones in big areas in Iran, but most of them are not easy to be validated or there are not clear criteria to evaluate whether the zones are correctly defined or not. The current {it Iranian Meteorological Organisation} classification is composed of six significant agroclimatological zones defined using the fundamental climate elements of temperature and precipitation obtained from 30 years data from 180 synoptic stations interpolated using regression kriging methods. Elevation was derived from SRTM (Shuttle Radar Topography Mission) digital elevation model of 90 m resolution. In this paper we assess the homogeneity of each of these conventionally defined agroclimatological zones using {bf TVDI (Temperature Vegetation Dryness Index)} values obtained from MODIS land surface temperature and NDVI operational products of the last three years between 2013 and 2015.

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

    Science.gov (United States)

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

    2017-03-01

    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 < 0.001) from 1982 to 2013. As for the spatial distribution, NDVI revealed an increasing trend from the northwest to the southeast, with about 61.79% of the LP exhibiting a significant increasing trend (P < 0.05). Some temperature extreme indices, including TMAXmean, TMINmean, TN90p, TNx, TX90p, and TXx, increased significantly at rates of 0.77 mm/10a, 0.52 °C/10a, 0.62 °C/10a, 0.80 °C/10a, 5.16 days/10a, and 0.65 °C/10a, respectively. On the other hand, other extreme temperature indices including TX10p and TN10p decreased significantly at rates of -2.77 days/10a and 4.57 days/10a (P < 0.01), respectively. Correlation analysis showed that only TMINmean had a significant relationship with NDVI at the yearly time scale (P < 0.05). At the monthly time scale, vegetation coverage and different vegetation types responded significantly positively to precipitation and temperature extremes (TMAXmean, TMINmean, TNx, TNn, TXn, and TXx) (P < 0.01). All of the precipitation extremes and temperature extremes exhibited significant positive relationships with NDVI during the spring and autumn (P < 0.01). However, the relationship between NDVI and RX1day, TMAXmean, TXn, and TXx was insignificant in summer. Vegetation exhibited a significant negative relationship with precipitation extremes in winter (P < 0.05). In terms of human activity, our results indicate a strong correlation between the cumulative afforestation area and NDVI in Yan

  18. [Assessment of chlorophyll content using a new vegetation index based on multi-angular hyperspectral image data].

    Science.gov (United States)

    Liao, Qin-hong; Zhang, Dong-yan; Wang, Ji-hua; Yang, Gui-jun; Yang, Hao; Coburn, Craig; Wong, Zhijie; Wang, Da-cheng

    2014-06-01

    The fast estimation of chlorophyll content is significant for understanding the crops growth, monitoring the disease and insect, and assessing the yield of crops. This study gets the hyperspectral imagery data by using a self-developed multi-angular acquisition system during the different maize growth period, the reflectance of maize canopy was extracted accurately from the hyperspectral images under different view angles in the principal plane. The hot-dark-spot index (HDS) of red waveband was calculated through the analysis of simulated values by ACRM model and measured values, then this index was used to modify the vegetation index (TCARI), thus a new vegetation index (HD-TCARI) based on the multi-angular observation was proposed. Finally, the multi-angular hyperspectral imagery data was used to validate the vegetation indexes. The result showed that HD-TCARI could effectively reduce the LAI effects on the assessment of chlorophyll content. When the chlorophyll content was greater than 30 μg x cm(-2), the correlation (R2) between HD-TCARI and LAI was only 26.88%-28.72%. In addition, the HD-TCARI could resist the saturation of vegetation index during the assessment of high chlorophyll content. When the LAI varled from 1 to 6, the linear relation between HD-TCARI and chlorophyll content could be improved by 9% compared with TCARI. The ground validation of HD-TCARI by multi-angular hyperspectral image showed that the linear relation between HD-TCARI and chlorophyll content (R2 = 66.74%) was better than the TCARI (R2 = 39.92%), which indicated that HD-TCARI has good potentials for estimating the chlorophyll content.

  19. Monitoring Vegetation Phenological Cycles in Two Different Semi-Arid Environmental Settings Using a Ground-Based NDVI System: A Potential Approach to Improve Satellite Data Interpretation

    Directory of Open Access Journals (Sweden)

    Malika Baghzouz

    2010-04-01

    Full Text Available In semi-arid environmental settings with sparse canopy covers, obtaining remotely sensed information on soil and vegetative growth characteristics at finer spatial and temporal scales than most satellite platforms is crucial for validating and interpreting satellite data sets. In this study, we used a ground-based NDVI system to provide continuous time series analysis of individual shrub species and soil surface characteristics in two different semi-arid environmental settings located in the Great Basin (NV, USA. The NDVI system was a dual channel SKR-1800 radiometer that simultaneously measured incident solar radiation and upward reflectance in two broadband red and near-infrared channels comparable to Landsat-5 TM band 3 and band 4, respectively. The two study sites identified as Spring Valley 1 site (SV1 and Snake Valley 1 site (SNK1 were chosen for having different species composition, soil texture and percent canopy cover. NDVI time-series of greasewood (Sarcobatus vermiculatus from the SV1 site allowed for clear distinction between the main phenological stages of the entire growing season during the period from January to November, 2007. NDVI time series values were significantly different between sagebrush (Artemisia tridentata and rabbitbrush (Chrysothamnus viscidiflorus at SV1 as well as between the two bare soil types at the two sites. Greasewood NDVI from the SNK1 site produced significant correlations with chlorophyll index (r = 0.97, leaf area index (r = 0.98 and leaf xylem water potential (r = 0.93. Whereas greasewood NDVI from the SV1 site produced lower correlations (r = 0.89, r = 0.73, or non significant correlations (r = 0.32 with the same parameters, respectively. Total percent cover was estimated at 17.5% for SV1 and at 63% for SNK1. Results from this study indicated the potential capabilities of using this ground-based NDVI system to extract spatial and temporal details of soil and vegetation optical properties not possible

  20. Scale effects of leaf area index inversion based on environmental and disaster monitoring satellite data

    Institute of Scientific and Technical Information of China (English)

    2010-01-01

    The spatial distribution of sub-pixel components has an impact on retrieval accuracy,and should be accounted for when inverting a three-dimensional adiative transfer model to retrieve leaf area index(LAI).To investigate this effect,we constructed three realistic scenarios with the same LAI values and other properties,except that the simulated plants had different distributions.We implemented the radiosity method to subsequently produce synthetic bidirectional reflectance factor(BRF) datasets based upon these simulated scenes.The inversion was conducted using these data,which showed that spatial distribution affects retrieval accuracy.The inversion was also conducted for LAI based on charge-coupled device(CCD) data from the Environment and Disaster Monitor Satellite(HJ-1),which depicted both forest and drought-resistant crop land cover.This showed that heterogeneity in coarse-resolution remote sensing data is the main error source in LAI inversion.The spatial distribution of global fractal dimension index,which can be used to describe the area of sub-pixel components and their spatial distribution modes,shows good consistency with the coarse resolution LAI inversion error.

  1. Mapping plastic greenhouse with medium spatial resolution satellite data: Development of a new spectral index

    Science.gov (United States)

    Yang, Dedi; Chen, Jin; Zhou, Yuan; Chen, Xiang; Chen, Xuehong; Cao, Xin

    2017-06-01

    Plastic greenhouses (PGs) are an important agriculture development technique to protect and control the growing environment for food crops. The extensive use of PGs can change the agriculture landscape and affects the local environment. Accurately mapping and estimating the coverage of PGs is a necessity to the strategic planning of modern agriculture. Unfortunately, PG mapping over large areas is methodologically challenging, as the medium spatial resolution satellite imagery (such as Landsat data) used for analysis lacks spatial details and spectral variations. To fill the gap, the paper proposes a new plastic greenhouse index (PGI) based on the spectral, sensitivity, and separability analysis of PGs using medium spatial resolution images. In the context of the Landsat Enhanced Thematic Mapper Plus (ETM+) imagery, the paper examines the effectiveness and capability of the proposed PGI. The results indicate that PGs in Landsat ETM+ image can be successfully detected by the PGI if the PG fraction is greater than 12% in a mixed pixel. A kappa coefficient of 0.83 and overall accuracy of 91.2% were achieved when applying the proposed PGI in the case of Weifang District, Shandong, China. These results show that the proposed index can be applied to identifying transparent PGs in atmospheric corrected Landsat image and has the potential for the digital mapping of plastic greenhouse coverage over a large area.

  2. 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.

  3. Remote sensing of temperate coniferous forest lead area index - The influence of canopy closure, understory vegetation and background reflectance

    Science.gov (United States)

    Spanner, Michael A.; Pierce, Lars L.; Running, Steven W.; Peterson, David L.

    1990-01-01

    Consideration is given to the effects of canopy closure, understory vegetation, and background reflectance on the relationship between Landsat TM data and the leaf area index (LAI) of temperate coniferous forests in the western U.S. A methodology for correcting TM data for atmospheric conditions and sun-surface-sensor geometry is discussed. Strong inverse curvilinear relationships were found between coniferous forest LAI and TM bands 3 and 5. It is suggested that these inverse relationships are due to increased reflectance of understory vegetation and background in open stands of lower LAI and decreased reflectance of the overstory in closed canopy stands with higher LAI.

  4. Remote sensing of temperate coniferous forest lead area index - The influence of canopy closure, understory vegetation and background reflectance

    Science.gov (United States)

    Spanner, Michael A.; Pierce, Lars L.; Running, Steven W.; Peterson, David L.

    1990-01-01

    Consideration is given to the effects of canopy closure, understory vegetation, and background reflectance on the relationship between Landsat TM data and the leaf area index (LAI) of temperate coniferous forests in the western U.S. A methodology for correcting TM data for atmospheric conditions and sun-surface-sensor geometry is discussed. Strong inverse curvilinear relationships were found between coniferous forest LAI and TM bands 3 and 5. It is suggested that these inverse relationships are due to increased reflectance of understory vegetation and background in open stands of lower LAI and decreased reflectance of the overstory in closed canopy stands with higher LAI.

  5. How well do we characterize the biophysical effects of vegetation cover change? Benchmarking land surface models against satellite observations.

    Science.gov (United States)

    Duveiller, Gregory; Forzieri, Giovanni; Robertson, Eddy; Georgievski, Goran; Li, Wei; Lawrence, Peter; Ciais, Philippe; Pongratz, Julia; Sitch, Stephen; Wiltshire, Andy; Arneth, Almut; Cescatti, Alessandro

    2017-04-01

    Changes in vegetation cover can affect the climate by altering the carbon, water and energy cycles. The main tools to characterize such land-climate interactions for both the past and future are land surface models (LSMs) that can be embedded in larger Earth System models (ESMs). While such models have long been used to characterize the biogeochemical effects of vegetation cover change, their capacity to model biophysical effects accurately across the globe remains unclear due to the complexity of the phenomena. The result of competing biophysical processes on the surface energy balance varies spatially and seasonally, and can lead to warming or cooling depending on the specific vegetation change and on the background climate (e.g. presence of snow or soil moisture). Here we present a global scale benchmarking exercise of four of the most commonly used LSMs (JULES, ORCHIDEE, JSBACH and CLM) against a dedicated dataset of satellite observations. To facilitate the understanding of the causes that lead to discrepancies between simulated and observed data, we focus on pure transitions amongst major plant functional types (PFTs): from different tree types (evergreen broadleaf trees, deciduous broadleaf trees and needleleaf trees) to either grasslands or crops. From the modelling perspective, this entails generating a separate simulation for each PFT in which all 1° by 1° grid cells are uniformly covered with that PFT, and then analysing the differences amongst them in terms of resulting biophysical variables (e.g net radiation, latent and sensible heat). From the satellite perspective, the effect of pure transitions is obtained by unmixing the signal of different 0.05° spatial resolution MODIS products (albedo, latent heat, upwelling longwave radiation) over a local moving window using PFT maps derived from the ESA Climate Change Initiative land cover map. After aggregating to a common spatial support, the observation and model-driven datasets are confronted and

  6. Vegetation Phenology and Intensity as a Function of Climate and River Flows for an Ephemeral Desert River, 2000 to 2010, Using MODIS Satellite Data

    Science.gov (United States)

    Nguyen, U.; Nagler, P. L.; Glenn, E. P.; Van Riper, C., III

    2011-12-01

    The San Pedro river, located along Sonoran and Chihuahuan desert, is one of the most biologically diverse ecosystems in the Rocky mountains of the Southwestern United States. Vegetation dynamics related to seasonal changes may affect the life and migration of many wildlife species. Furthermore, vegetation density is related to surface flows in the river and depth to groundwater, which vary year to year. The MODIS Vegetation Index products (EVI and NDVI) were used to monitor vegetation dynamics during 10 years (2000-2010) to examine the impact of climatic conditions (such as temperature from LST, precipitation from PRISM and rive flows from gaga data) on the onset of greenness, senescence, and maximum vegetation density. The phenology profiles from time series data and relationships between vegetation index and temperature not only show seasonal changes but also respond to moisture stress on vegetation in the riparian areas of the San Pedro River.

  7. Casa Grande Ruins National Monument Vegetation Mapping Project - Quickbird Satellite Imagery

    Data.gov (United States)

    National Park Service, Department of the Interior — This imagery was acquired on December 3, 2007 by DigitalGlobe, Inc.'s Quickbird satellite. Its 4 multispectral bands (blue, green, red, near infrared), together with...

  8. Steady state estimation of soil organic carbon using satellite-derived canopy leaf area index

    Science.gov (United States)

    Fang, Yilin; Liu, Chongxuan; Huang, Maoyi; Li, Hongyi; Leung, L. Ruby

    2014-12-01

    Estimation of soil organic carbon (SOC) stock using models typically requires long term spin-up of the carbon-nitrogen (CN) models, which has become a bottleneck for global modeling. We report a new numerical approach to estimate global SOC stock that can alleviate long spin-up. The approach uses satellite-based canopy leaf area index (LAI) and takes advantage of a reaction-based biogeochemical module—Next Generation BioGeoChemical Module (NGBGC) that was recently developed and incorporated in version 4 of the Community Land Model (CLM4). Although NGBGC uses the same CN mechanisms as in CLM4CN, it can be easily configured to run prognostic or steady state simulations. The new approach was applied at point and global scales and compared with SOC derived from spin-up by running NGBGC in the prognostic mode, and SOC from the Harmonized World Soil Database (HWSD). The steady state solution is comparable to the spin-up value when the satellite LAI is close to that from the spin-up solution, and largely captured the global variability of the HWSD SOC across the different dominant plant functional types (PFTs). The correlation between the simulated and HWSD SOC was, however, weak at both point and global scales, suggesting the needs for improving the biogeochemical processes described in CLM4 and updating HWSD. Besides SOC, the steady state solution also includes all other state variables simulated by a spin-up run, which makes the tested approach a promising tool to efficiently estimate global SOC distribution and evaluate and compare multiple aspects simulated by different CN mechanisms in the model.

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

    Directory of Open Access Journals (Sweden)

    Miao Tian

    2016-08-01

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

  10. A Satellite-Derived Upper-Tropospheric Water Vapor Transport Index for Climate Studies

    Science.gov (United States)

    Jedlovec, Gray J.; Lerner, Jeffrey A.; Atkinson, Robert J.

    1998-01-01

    A new approach is presented to quantify upper-level moisture transport from geostationary satellite data. Daily time sequences of Geostationary Operational Environmental Satellite GOES-7 water vapor imagery were used to produce estimates of winds and water vapor mixing ratio in the cloud-free region of the upper troposphere sensed by the 6.7- microns water vapor channel. The winds and mixing ratio values were gridded and then combined to produce a parameter called the water vapor transport index (WVTI), which represents the magnitude of the two-dimensional transport of water vapor in the upper troposphere. Daily grids of WVTI, meridional moisture transport, mixing ratio, pressure, and other associated parameters were averaged to produce monthly fields for June, July, and August (JJA) of 1987 and 1988 over the Americas and surrounding oceanic regions, The WVTI was used to compare upper-tropospheric moisture transport between the summers of 1987 and 1988, contrasting the latter part of the 1986/87 El Nino event and the La Nina period of 1988. A similar product derived from the National Centers for Environmental Prediction (NCEP)-National Center for Atmospheric Research (NCAR) 40-Year Reanalysis Project was used to help to validate the index. Although the goal of this research was to describe the formulation and utility of the WVTI, considerable insight was obtained into the interannual variability of upper-level water vapor transport. Both datasets showed large upper-level water vapor transport associated with synoptic features over the Americas and with outflow from tropical convective systems. Minimal transport occurred over tropical and subtropical high pressure regions where winds were light. Index values from NCEP-NCAR were 2-3 times larger than that determined from GOES. This difference resulted from large zonal wind differences and an apparent overestimate of upper-tropospheric moisture in the reanalysis model. A comparison of the satellite-derived monthly

  11. Radiometric quality and performance of TIMESAT for smoothing moderate resolution imaging spectroradiometer enhanced vegetation index time series from western Bahia State, Brazil

    Science.gov (United States)

    Borges, Elane F.; Sano, Edson E.; Medrado, Euzébio

    2014-01-01

    The launch of the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor aboard the Terra and Aqua platforms in 1999 and 2002, respectively, with temporal resolutions of 1 to 2 days opened the possibility of using a longtime series of satellite images to map land use and land cover classes from different regions of the Earth, to study vegetation phenology, and to monitor regional and global climate change, among other applications. The main objectives of this study were twofold: to analyze the radiometric quality of the time series of enhanced vegetation index (EVI) products derived from the Terra MODIS sensor in western Bahia State, Brazil, and to identify the most appropriate filter to smooth MODIS EVI time series of the study area among those available in the public domain, the TIMESAT algorithm. The 2000 to 2011 time period was considered (a total of 276 scenes). The radiometric quality was analyzed based on the pixel reliability data set available in the MOD13Q1 product. The performances of the three smoothing filters available within TIMESAT (double logistic, Savitzky-Golay, and asymmetric Gaussian) were analyzed using the Graybill's F test and Willmott statistics. Five percent of the MODIS pixels from the study area were cloud-affected, almost all of which were from the rainy season. The double logistic filter presented the best performance.

  12. Gravimetric Vegetation Water Content Estimation for Corn Using L-Band Bi-Angular, Dual-Polarized Brightness Temperatures and Leaf Area Index

    Directory of Open Access Journals (Sweden)

    Qi Wang

    2015-08-01

    Full Text Available In this study, an algorithm to retrieve the gravimetric vegetation water content (GVWC, % of corn was developed. First, the method for obtaining the optical depth from L-band (1.4 GHz bi-angular, dual-polarized brightness temperatures (TB for short vegetation was investigated. Then, the quantitative relationship between the corn optical depth, corn GVWC and corn leaf area index (LAI was constructed. Finally, using the Polarimetric L-band Microwave Radiometer (PLMR airborne data in the 2012 Heihe Watershed Allied Telemetry Experimental Research (HiWATER project, the Global Land Surface Satellite (GLASS LAI product, the height and areal density of the corn stalks, the corn GVWC was estimated (corn GLASS-GVWC. Both the in situ measured corn GVWC and the corn GVWC retrieved based on the in situ measured corn LAI (corn LAINET-GVWC were used to validate the accuracy of the corn GLASS-GVWC. The results show that the GVWC retrieval method proposed in this study is feasible for monitoring the corn GVWC. However, the accuracy of the retrieval results is highly sensitive to the accuracy of the LAI input parameters.

  13. Vegetation

    DEFF Research Database (Denmark)

    Epstein, H.E.; Walker, D.A.; Bhatt, U.S.

    2012-01-01

    increased 20-26%. • Increasing shrub growth and range extension throughout the Low Arctic are related to winter and early growing season temperature increases. Growth of other tundra plant types, including graminoids and forbs, is increasing, while growth of mosses and lichens is decreasing. • Increases...... in vegetation (including shrub tundra expansion) and thunderstorm activity, each a result of Arctic warming, have created conditions that favor a more active Arctic fire regime....

  14. Forested floristic quality index: An assessment tool for forested wetland habitats using the quality and quantity of woody vegetation at Coastwide Reference Monitoring System (CRMS) vegetation monitoring stations

    Science.gov (United States)

    Wood, William B.; Shaffer, Gary P.; Visser, Jenneke M.; Krauss, Ken W.; Piazza, Sarai C.; Sharp, Leigh Anne; Cretini, Kari F.

    2017-02-08

    The U.S. Geological Survey, in cooperation with the Coastal Protection and Restoration Authority of Louisiana and the Coastal Wetlands Planning, Protection and Restoration Act, developed the Forested Floristic Quality Index (FFQI) for the Coastwide Reference Monitoring System (CRMS). The FFQI will help evaluate forested wetland sites on a continuum from severely degraded to healthy and will assist in defining areas where forested wetland restoration can be successful by projecting the trajectories of change. At each CRMS forested wetland site there are stations for quantifying the overstory, understory, and herbaceous vegetation layers. Rapidly responding overstory canopy cover and herbaceous layer composition are measured annually, while gradually changing overstory basal area and species composition are collected on a 3-year cycle.A CRMS analytical team has tailored these data into an index much like the Floristic Quality Index (FQI) currently used for herbaceous marsh and for the herbaceous layer of the swamp vegetation. The core of the FFQI uses basal area by species to assess the quality and quantity of the overstory at each of three stations within each CRMS forested wetland site. Trees that are considered by experts to be higher quality swamp species like Taxodium distichum (bald cypress) and Nyssa aquatica (water tupelo) are scored higher than tree species like Triadica sebifera (Chinese tallow) and Salix nigra (black willow) that are indicators of recent disturbance. This base FFQI is further enhanced by the percent canopy cover in the overstory and the presence of indicator species at the forest floor. This systemic approach attempts to differentiate between locations with similar basal areas that are on different ecosystem trajectories. Because of these varying states of habitat degradation, paired use of the FQI and the FFQI is useful to interpret the vegetative data in transitional locations. There is often an inverse relation between the health of the

  15. Fruit and Vegetable Intake and Body Mass Index in a Large Sample of Middle-Aged Australian Men and Women

    Directory of Open Access Journals (Sweden)

    Karen Charlton

    2014-06-01

    Full Text Available Dietary guidelines around the world recommend increased intakes of fruits and non-starchy vegetables for the prevention of chronic diseases and possibly obesity. This study aimed to describe the association between body mass index (BMI and habitual fruit and vegetable consumption in a large sample of 246,995 Australian adults aged 45 + year who had been recruited for the “45 and Up” cohort study. Fruit and vegetable intake was assessed using validated short questions, while weight and height were self-reported. Multinomial logistic regression was used, by sex, to assess the association between fruit and vegetable intake and BMI. Compared to the referent normal weight category (BMI 18.5 to 24.9, the odds ratio (OR of being in the highest vegetable intake quartile was 1.09 (95% confidence interval (CI 1.04–1.14 for overweight women (BMI 25.0–29.9 and 1.18 (95% CI 1.12–1.24 for obese women. The association was in the opposite direction for fruit for overweight (OR 0.85; 95% CI 0.80–0.90 and obese women (OR 0.75; 95% CI 0.69–0.80. Obese and overweight women had higher odds of being in the highest intake quartile for combined fruit and vegetable intake, and were more likely to meet the “2 and 5” target or to have five or more serves of fruit and vegetables per day. In contrast, overweight men were less likely to be in high intake quartiles and less likely to meet recommended target of 5 per day, but there was no consistent relationship between obesity and fruit and vegetable intake. Underweight women and underweight men were less likely to be in the highest intake quartiles or to meet the recommended targets. These data suggest that improving adherence to dietary targets for fruit and vegetables may be a dietary strategy to overcome overweight among men, but that overweight and obese women are already adhering to these targets. The association between fruit and vegetable intake and underweight in adults suggests that improving fruit

  16. Fruit and vegetable intake and body mass index in a large sample of middle-aged Australian men and women.

    Science.gov (United States)

    Charlton, Karen; Kowal, Paul; Soriano, Melinda M; Williams, Sharon; Banks, Emily; Vo, Kha; Byles, Julie

    2014-06-17

    Dietary guidelines around the world recommend increased intakes of fruits and non-starchy vegetables for the prevention of chronic diseases and possibly obesity. This study aimed to describe the association between body mass index (BMI) and habitual fruit and vegetable consumption in a large sample of 246,995 Australian adults aged 45 + year who had been recruited for the "45 and Up" cohort study. Fruit and vegetable intake was assessed using validated short questions, while weight and height were self-reported. Multinomial logistic regression was used, by sex, to assess the association between fruit and vegetable intake and BMI. Compared to the referent normal weight category (BMI 18.5 to 24.9), the odds ratio (OR) of being in the highest vegetable intake quartile was 1.09 (95% confidence interval (CI) 1.04-1.14) for overweight women (BMI 25.0-29.9) and 1.18 (95% CI 1.12-1.24) for obese women. The association was in the opposite direction for fruit for overweight (OR 0.85; 95% CI 0.80-0.90) and obese women (OR 0.75; 95% CI 0.69-0.80). Obese and overweight women had higher odds of being in the highest intake quartile for combined fruit and vegetable intake, and were more likely to meet the "2 and 5" target or to have five or more serves of fruit and vegetables per day. In contrast, overweight men were less likely to be in high intake quartiles and less likely to meet recommended target of 5 per day, but there was no consistent relationship between obesity and fruit and vegetable intake. Underweight women and underweight men were less likely to be in the highest intake quartiles or to meet the recommended targets. These data suggest that improving adherence to dietary targets for fruit and vegetables may be a dietary strategy to overcome overweight among men, but that overweight and obese women are already adhering to these targets. The association between fruit and vegetable intake and underweight in adults suggests that improving fruit and vegetables intakes are

  17. Impact of consumption of vegetable, fruit, grain, and high glycemic index foods on aggressive prostate cancer risk.

    Science.gov (United States)

    Hardin, Jill; Cheng, Iona; Witte, John S

    2011-01-01

    Prostate cancer is a common but complex disease, and distinguishing modifiable risk factors such as diet for more aggressive disease is extremely important. Previous work has detected intriguing associations between vegetable, fruit, and grains and more aggressive prostate cancer, although these remain somewhat unclear. Here we further investigate such potential relationships with a case-control study of 982 men (470 more aggressive prostate cancer cases and 512 control subjects). Comparing the highest to lowest quartiles of intake, we found that increasing intakes of leafy vegetables were inversely associated with risk of aggressive prostate cancer [adjusted odds ratio (OR) = 0.66, 95% CI: 0.46, 0.96; P trend = 0.02], as was higher consumption of high carotenoid vegetables (OR = 0.71, 95% CI: 0.48, 1.04; P trend = 0.04). Conversely, increased consumption of high glycemic index foods were positively associated with risk of aggressive disease (OR = 1.64, 95% CI: 1.05, 2.57; P trend = 0.02). These results were driven by a number of specific foods within the food groups. Our findings support the hypothesis that diets high in vegetables and low in high glycemic index foods decrease risk of aggressive prostate cancer.

  18. Evaluation of TRMM satellite-based precipitation indexes for flood forecasting over Riyadh City, Saudi Arabia

    Science.gov (United States)

    Tekeli, Ahmet Emre; Fouli, Hesham

    2016-10-01

    Floods are among the most common disasters harming humanity. In particular, flash floods cause hazards to life, property and any type of structures. Arid and semi-arid regions are equally prone to flash floods like regions with abundant rainfall. Despite rareness of intensive and frequent rainfall events over Kingdom of Saudi Arabia (KSA); an arid/semi-arid region, occasional flash floods occur and result in large amounts of damaging surface runoff. The flooding of 16 November, 2013 in Riyadh; the capital city of KSA, resulted in killing some people and led to much property damage. The Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) Real Time (RT) data (3B42RT) are used herein for flash flood forecasting. 3B42RT detected high-intensity rainfall events matching with the distribution of observed floods over KSA. A flood early warning system based on exceedance of threshold limits on 3B42RT data is proposed for Riyadh. Three different indexes: Constant Threshold (CT), Cumulative Distribution Functions (CDF) and Riyadh Flood Precipitation Index (RFPI) are developed using 14-year 3B42RT data from 2000 to 2013. RFPI and CDF with 90% captured the three major flooding events that occurred in February 2005, May 2010 and November 2013 in Riyadh. CT with 3 mm/h intensity indicated the 2013 flooding, but missed those of 2005 and 2010. The methodology implemented herein is a first-step simple and accurate way for flash flood forecasting over Riyadh. The simplicity of the methodology enables its applicability for the TRMM follow-on missions like Global Precipitation Measurement (GPM) mission.

  19. Comparison of sampling strategies for object-based classification of urban vegetation from Very High Resolution satellite images

    Science.gov (United States)

    Rougier, Simon; Puissant, Anne; Stumpf, André; Lachiche, Nicolas

    2016-09-01

    Vegetation monitoring is becoming a major issue in the urban environment due to the services they procure and necessitates an accurate and up to date mapping. Very High Resolution satellite images enable a detailed mapping of the urban tree and herbaceous vegetation. Several supervised classifications with statistical learning techniques have provided good results for the detection of urban vegetation but necessitate a large amount of training data. In this context, this study proposes to investigate the performances of different sampling strategies in order to reduce the number of examples needed. Two windows based active learning algorithms from state-of-art are compared to a classical stratified random sampling and a third combining active learning and stratified strategies is proposed. The efficiency of these strategies is evaluated on two medium size French cities, Strasbourg and Rennes, associated to different datasets. Results demonstrate that classical stratified random sampling can in some cases be just as effective as active learning methods and that it should be used more frequently to evaluate new active learning methods. Moreover, the active learning strategies proposed in this work enables to reduce the computational runtime by selecting multiple windows at each iteration without increasing the number of windows needed.

  20. Monitoring of the Spatial Distribution and Temporal Dynamics of the Green Vegetation Fraction of Croplands in Southwest Germany Using High-Resolution RapidEye Satellite Images

    Science.gov (United States)

    Imukova, Kristina; Ingwersen, Joachim; Streck, Thilo

    2014-05-01

    The green vegetation fraction (GVF) is a key input variable to the evapotranspiration scheme applied in the widely used NOAH land surface model (LSM). In standard applications of the NOAH LSM, the GVF is taken from a global map with a 15 km×15 km resolution. The central objective of the present study was (a) to derive gridded GVF data in a high spatial and temporal resolution from RapidEye images for a region in Southwest Germany, and (b) to improve the representation of the GVF dynamics of croplands in the NOAH LSM for a better simulation of water and energy exchange between land surface and atmosphere. For the region under study we obtained monthly RapidEye satellite images with a resolution 5 m×5 m by the German Aerospace Center (DLR). The images hold five spectral bands: blue, green, red, red-edge and near infrared (NIR). The GVF dynamics were determined based on the Normalized Difference Vegetation Index (NDVI) calculated from the red and near-infrared bands of the satellite images. The satellite GVF data were calibrated and validated against ground truth measurements. Digital colour photographs above the canopy were taken with a boom-mounted digital camera at fifteen permanently marked plots (1 m×1 m). Crops under study were winter wheat, winter rape and silage maize. The GVF was computed based on the red and the green band of the photographs according to Rundquist's method (2002). Based on the obtained calibration scheme GVF maps were derived in a monthly resolution for the region. Our results confirm a linear relationship between GVF and NDVI and demonstrate that it is possible to determine the GVF of croplands from RapidEye images based on a simple two end-member mixing model. Our data highlight the high variability of the GVF in time and space. At the field scale, the GVF was normally distributed with a coefficient of variation of about 32%. Variability was mainly caused by soil heterogeneities and management differences. At the regional scale the GVF

  1. NOAA Climate Data Record Normalized Difference Vegetation Index: 1981-2013

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — National Oceanic and Atmospheric Administration (NOAA) Climate Data Records (CDR) provide historical climate information using data from weather satellites. This...

  2. NOAA Climate Data Record Normalized Difference Vegetation Index: 1981-2013

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — National Oceanic and Atmospheric Administration (NOAA) Climate Data Records (CDR) provide historical climate information using data from weather satellites. This...

  3. DEVELOPMENT OF AN INDEX OF ALIEN SPECIES INVASIVENESS: AN AID TO ASSESSING RIPARIAN VEGETATION CONDITION

    Science.gov (United States)

    Many riparian areas are invaded by alien plant species that negatively affect native species composition, community dynamics and ecosystem properties. We sampled vegetation along reaches of 31 low order streams in eastern Oregon, and characterized species assemblages at patch an...

  4. Assessment of acreage and vegetation change in Florida`s Big Bend tidal wetlands using satellite imagery

    Energy Technology Data Exchange (ETDEWEB)

    Raabe, E.A.; Stumpf, R.P. [Geological Survey, St. Petersburg, FL (United States)

    1997-06-01

    Fluctuations in sea level and impending development on the west coast of Florida have aroused concern for the relatively pristine tidal marshes of the Big Bend. Landsat Thematic Mapper (TM) images for 1986 and 1995 are processed and evaluated for signs of change. The images cover 250 km of Florida`s Big Bend Gulf Coast, encompassing 160,000 acres of tidal marshes. Change is detected using the normalized difference vegetation index (NDVI) and land cover classification. The imagery shows negligible net loss or gain in the marsh over the 9-year period. However, regional changes in biomass are apparent and are due to natural disturbances such as low winter temperatures, fire, storm surge, and the conversion of forest to marsh. Within the marsh, the most prominent changes in NDVI and in land cover result from the recovery of mangroves from freezes, a decline of transitional upland vegetation, and susceptibility of the marsh edge and interior to variations in tidal flooding.

  5. Discrimination of Vegetation Height Categories With Passive Satellite Sensor Imagery Using Texture Analysis

    NARCIS (Netherlands)

    Petrou, Z.; Manakos, I.; Stathaki, T.; Mücher, C.A.; Adamo, M.

    2015-01-01

    Vegetation height is a crucial factor in environmental studies, landscape analysis, and mapping applications. Its estimation may prove cost and resource demanding, e.g., employing light detection and ranging (LiDAR) data. This study presents a cost-effective framework for height estimation, built ar

  6. Benchmarking LSM root-zone soil mositure predictions using satellite-based vegetation indices

    Science.gov (United States)

    The application of modern land surface models (LSMs) to agricultural drought monitoring is based on the premise that anomalies in LSM root-zone soil moisture estimates can accurately anticipate the subsequent impact of drought on vegetation productivity and health. In addition, the water and energy ...

  7. West-east contrast of phenology and climate in northern Asia revealed using a remotely sensed vegetation index.

    Science.gov (United States)

    Suzuki, Rikie; Nomaki, Tomoyuki; Yasunari, Tetsuzo

    2003-05-01

    The phenology of the vegetation covering north Asia (mainly Siberia) and its spatial characterstics were investigated using remotely sensed normalized difference vegetation index (NDVI) data. The analysis used the weekly averaged NDVI over 5 years (1987-1991) using the second-generation weekly global vegetation index dataset (0.144 degrees x 0.144 degrees spatial resolution). In the seasonal NDVI cycle, three phenological events were defined for each pixel: green-up week (NDVI exceeds 0.2), maximum week, and senescence week (NDVI drops below 0.2). Generally there was a west-early/east-late gradient in the three events in north Asia. In the zonal transect between 45 degrees and 50 degrees N, the timing of green-up, maximum, and senescence near 60 degrees E (Kazakh) was about 3.4, 8.7, and 13.4 weeks earlier than near 110 degrees E (Mongolia) respectively. It has been suggested that vegetation near Kazakh only flourishes during a short period when water from snow melt is available from late spring to early summer. In Mongolia, abundant water is available for the vegetation, even in midsummer, because of precipitation. In the 50-60 degrees N zonal transect, the green-up and maximum near 40 degrees E were about 3.8 and 3.9 weeks earlier than near 115 degrees E, respectively. As for the week of senescence, there was no clear west-east trend. This west-to-east phenological gradient was related to the weekly cumulative temperature (over 0 degrees C). Weeks in which the cumalative temperature exceeded 40 degrees C and 140 degrees C had a similar west-east distribution to green-up and maximum NDVI.

  8. Mapping Aquatic Vegetation in a Tropical Wetland Using High Spatial Resolution Multispectral Satellite Imagery

    Directory of Open Access Journals (Sweden)

    Timothy G. Whiteside

    2015-09-01

    Full Text Available Vegetation plays a key role in the environmental function of wetlands. The Ramsar-listed wetlands of the Magela Creek floodplain in Northern Australia are identified as being at risk from weeds, fire and climate change. In addition, the floodplain is a downstream receiving environment for the Ranger Uranium Mine. Accurate methods for mapping wetland vegetation are required to provide contemporary baselines of annual vegetation dynamics on the floodplain to assist with analysing any potential change during and after minesite rehabilitation. The aim of this study was to develop and test the applicability of geographic object-based image analysis including decision tree classification to classify WorldView-2 imagery and LiDAR-derived ancillary data to map the aquatic vegetation communities of the Magela Creek floodplain. Results of the decision tree classification were compared against a Random Forests classification. The resulting maps showed the 12 major vegetation communities that exist on the Magela Creek floodplain and their distribution for May 2010. The decision tree classification method provided an overall accuracy of 78% which was significantly higher than the overall accuracy of the Random Forests classification (67%. Most of the error in both classifications was associated with confusion between spectrally similar classes dominated by grasses, such as Hymenachne and Pseudoraphis. In addition, the extent of the sedge Eleocharis was under-estimated in both cases. This suggests the method could be useful for mapping wetlands where statistical-based supervised classifications have achieved less than satisfactory results. Based upon the results, the decision tree method will form part of an ongoing operational monitoring program.

  9. Backscattering and vegetation water content response of paddy crop at C-band using RISAT-1 satellite data

    Science.gov (United States)

    Kumar, Pradeep; Prasad, Rajendra; Choudhary, Arti; Gupta, Dileep Kumar; Narayan Mishra, Varun; Srivastava, Prashant K.

    2016-04-01

    The study about the temporal behaviour of vegetation water content (VWC) is essential for monitoring the growth of a crop to improve agricultural production. In agriculture, VWC could possibly provide information that can be used to infer water stress for irrigation decisions, vegetation health conditions, aid in yield estimation and assessment of drought conditions (Penuelas et al., 1993). The VWC is an important parameter for soil moisture retrieval in microwave remote sensing (Srivastava et al., 2014). In the present study, the backscattering and VWC response of paddy crop has been investigated using medium resolution (MRS) radar imaging satellite-1 (RISAT-1) synthetic aperture radar (SAR) data in Varanasi, India. The VWC of paddy crop was measured at its five different growth stages started from 15 July 2013 to 23 October 2013 from the transplanting to maturity stage during Kharif season. The whole life of paddy crop was divided into three different major growth stages like vegetative stage, reproductive stage and ripening stage. During vegetative stage, the backscattering coefficients were found increasing behaviour until the leaves became large and dense due to major contribution of stems and the interaction between the stems and water underneath the paddy crop. During reproductive stage, the backscattering coefficients were found to increase slowly due to random scattering by vertical leaves. The increase in the size of leaves cause to cover most of the spaces between plants resulted to quench the contributions from the stems and the water underneath. At the maturity stage, the backscattering showed its decreasing behaviour. The VWC of paddy crop was found increasing up to vegetative to reproductive stages (28 September 2013) and then started decreasing during the ripening (maturity) stage. Similar behaviour was obtained between backscattering coefficients and VWC that showed an increasing trend from vegetative to reproductive stage and then lowering down at

  10. Satellite detection of Northern Hemisphere Non-Frozen season changes and associated impacts to vegetation growing seasons

    Science.gov (United States)

    Kim, Y.; Kimball, J. S.; Zhang, K.; McDonald, K. C.

    2011-12-01

    The landscape freeze-thaw (FT) signal from satellite microwave remote sensing is closely linked to vegetation phenology, productivity and land-atmosphere trace gas exchange where seasonal frozen temperatures are a major constraint to plant growth. We applied a temporal change classification of 37 GHz, vertically polarized brightness temperature (Tb) measurements from the Scanning Multichannel Microwave Radiometer (SMMR) and Special Sensor Microwave Imager (SSM/I) to classify daily FT status over global land areas where seasonal frozen temperatures influence ecosystem processes. A temporally consistent, long-term (>30 year) FT record was created ensuring cross-sensor consistency through pixel-wise adjustment of the SMMR Tb record based on empirical analyses of overlapping SMMR and SSM/I measurements. The resulting FT record showed mean annual spatial classification accuracies of 91 (+/-8.6) and 84 (+/-9.3) percent for PM and AM overpass retrievals relative to air temperature measurements from global weather stations. The FT results were also compared against other measures of biosphere activity including satellite derived vegetation greenness (NDVI) and terrestrial net primary productivity (NPP), tower CO2 flux measurements and seasonal patterns of atmospheric CO2 concentrations from northern (>50°N) monitoring sites. A strong (P45°N) latitudes and upper elevations. The FT record also shows a positive (0.199 days yr-1) trend in the number of transitional (AM frozen and PM non-frozen) frost days, resulting in reduced photosynthetic activity inferred from tower and NDVI measurements. The relative benefits of earlier and longer non-frozen seasons for vegetation growth and productivity under global warming may be declining due to opposing increases in disturbance, drought and frost damage related impacts. Portions of this work were conducted at the Jet Propulsion Laboratory, California Institute of Technology under contract to the National Aeronautics and Space

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

    Science.gov (United States)

    Georgopoulou, Danai; Koutsias, Nikos

    2015-04-01

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

  12. 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

    2016-10-01

    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.

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

    Science.gov (United States)

    Beck, Pieter S. A.; Goetz, Scott J.

    2011-12-01

    In the first paragraph of the section '2. Data sets and methods', the Normalized Difference Vegetation Index (NDVI) data set used was incorrectly referred to as GIMMS-NDVI version 3G with a 0.084° spatial resolution. This should be corrected to GIMMS-NDVI version G with a 0.07° spatial resolution. Accordingly, the acknowledgement should state 'We would like to thank ... Jim Tucker and Jorge Pinzon for providing the GIMMS version G data', instead of 'We would like to thank ... Jorge Pinzon for providing the GIMMS 3G data'.

  14. 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

    2017-08-29

    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

  15. Assimilation of leaf area index and surface soil moisture satellite observations into the SIM hydrological model over France

    Science.gov (United States)

    Fairbairn, David; Calvet, Jean-Christophe; Mahfouf, Jean-Francois; Barbu, Alina

    2016-04-01

    Hydrological models have a variety of uses, including flood and drought prediction and water management. The SAFRAN-ISBA-MODCOU (SIM) hydrological model consists of three stages: An atmospheric analysis (SAFRAN) over France, which forces a land surface model (ISBA-A-gs), which then provides drainage and runoff inputs to a hydrological model (MODCOU). The river discharge from MODCOU is validated using observed river discharge over France. Data assimilation (DA) combines a short model forecast from the past with observations to improve the estimate of the model state. The ISBA-A-gs representation of soil moisture and its influence by vegetation can be improved by assimilating surface soil moisture (SSM) and leaf area index (LAI) observations respectively. The Advanced Scatterometer (ASCAT) on board the MetOP satellite measures a low-frequency microwave signal, which is used to retrieve daily SSM over France. The SPOT-VGT sensor observes LAI over France at a temporal frequency of about 10 days. The Simplified Extended Kalman (SEKF) filter combines the model and observed variables by weighting them according to their respective accuracies. Although the SEKF makes incorrect linear assumptions, past experiments have shown that it improves on the model estimates of SSM and LAI. However, due to nonlinearities in the land surface model, improvements in SSM and LAI do not imply improved soil moisture fluxes (drainage, runoff and evapotranspiration). This study indirectly examines the impact of the SEKF on the soil moisture fluxes using the MODCOU hydrological model. The ISBA-A-gs model appears to underestimate the LAI for grasslands in winter and spring, which results in an underestimation (overestimation) of evapotranspiration (drainage and runoff). The excess water flowing into the rivers and aquifers contributes to an overestimation of the MODCOU discharge. Assimilating LAI observations slightly increases the LAI analysis in winter and spring and therefore reduces the

  16. The application of very high resolution satellite image in urban vegetation cover investigation: a case study of Xiamen City

    Institute of Scientific and Technical Information of China (English)

    CHENGChengqi; LiBin; MATing

    2003-01-01

    With the technological improvements of satellite sensors, we will acquire more information about the earth so that we have reached a new application epoch of observation on earth environmental change and cartography. But with the enhancement of spatial resolution, some questions have arisen in the application of using traditional image processing and classification methods. Aiming for such questions, we studied the application of IKONOS very high resolution image (1 m) in Xiamen City on Urban Vegetation Cover Investigation and discussed the difference between the very high resolution image and traditional low spatial resolution image at classification,information abstraction etc. It is an advantageous test for the large-scale application of very high resolution data in the future.

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

    Science.gov (United States)

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

    2014-06-01

    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.

  18. Monitoring Corals and Submerged Aquatic Vegetation in Western Pacific Using Satellite Remote Sensing Integrated with Field Data

    Science.gov (United States)

    Roelfsema, C. M.; Phinn, S. R.; Lyons, M. B.; Kovacs, E.; Saunders, M. I.; Leon, J. X.

    2013-12-01

    Corals and Submerged Aquatic Vegetation (SAV) are typically found in highly dynamic environments where the magnitude and types of physical and biological processes controlling their distribution, diversity and function changes dramatically. Recent advances in the types of satellite image data and the length of their archives that are available globally, coupled with new techniques for extracting environmental information from these data sets has enabled significant advances to be made in our ability to map and monitor coral and SAV environments. Object Based Image Analysis techniques are one of the most significant advances in information extraction techniques for processing images to deliver environmental information at multiple spatial scales. This poster demonstrates OBIA applied to high spatial resolution satellite image data to map and monitor coral and SAV communities across a variety of environments in the Western Pacific that vary in their extent, biological composition, forcing physical factors and location. High spatial resolution satellite imagery (Quickbird, Ikonos and Worldview2) were acquired coincident with field surveys on each reef to collect georeferenced benthic photo transects, over various areas in the Western Pacific. Base line maps were created, from Roviana Lagoon Solomon island (600 km2), Bikini Atoll Marshall Island (800 Km2), Lizard Island, Australia (30 km2) and time series maps for geomorphic and benthic communities were collected for Heron Reef, Australia (24 km2) and Eastern Banks area of Moreton Bay, Australia (200 km2). The satellite image data were corrected for radiometric and atmospheric distortions to at-surface reflectance. Georeferenced benthic photos were acquired by divers or Autonomous Underwater Vehicles, analysed for benthic cover composition, and used for calibration and validation purposes. Hierarchical mapping from: reef/non-reef (1000's - 10000's m); reef type (100's - 1000's m); 'geomorphic zone' (10's - 100's m); to

  19. Constraints from atmospheric CO2 and satellite-based vegetation activity observations on current land carbon cycle trends

    Directory of Open Access Journals (Sweden)

    S. Zaehle

    2012-11-01

    Full Text Available Terrestrial ecosystem models used for Earth system modelling show a significant divergence in future patterns of ecosystem processes, in particular carbon exchanges, despite a seemingly common behaviour for the contemporary period. An in-depth evaluation of these models is hence of high importance to achieve a better understanding of the reasons for this disagreement. Here, we develop an extension for existing benchmarking systems by making use of the complementary information contained in the observational records of atmospheric CO2 and remotely-sensed vegetation activity to provide a firm set of diagnostics of ecosystem responses to climate variability in the last 30 yr at different temporal and spatial scales. The selection of observational characteristics (traits specifically considers the robustness of information given the uncertainties in both data and evaluation analysis. In addition, we provide a baseline benchmark, a minimum test that the model under consideration has to pass, to provide a more objective, quantitative evaluation framework. The benchmarking strategy can be used for any land surface model, either driven by observed meteorology or coupled to a climate model. We apply this framework to evaluate the offline version of the MPI-Earth system model's land surface scheme JSBACH. We demonstrate that the complementary use of atmospheric CO2 and satellite based vegetation activity data allows to pinpoint specific model failures that would not be possible by the sole use of atmospheric CO2 observations.

  20. A normalized difference vegetation index (NDVI) time-series of idle agriculture lands: A preliminary study

    NARCIS (Netherlands)

    Vaiphasa, C.; Piamduaytham, S.; Vaiphasa, T.; Skidmore, A.K.

    2011-01-01

    In this paper, the NDVI time-series collected from the study area between year 2003 and 2005 of all land cover types are plotted and compared. The study area is the agricultural zones in Banphai District, Khonkean, Thailand. The LANDSAT satellite images of different dates were first transformed into

  1. Evaluating Biosphere Model Estimates of the Start of the Vegetation Active Season in Boreal Forests by Satellite Observations

    Directory of Open Access Journals (Sweden)

    Kristin Böttcher

    2016-07-01

    Full Text Available The objective of this study was to assess the performance of the simulated start of the photosynthetically active season by a large-scale biosphere model in boreal forests in Finland with remote sensing observations. The start of season for two forest types, evergreen needle- and deciduous broad-leaf, was obtained for the period 2003–2011 from regional JSBACH (Jena Scheme for Biosphere–Atmosphere Hamburg runs, driven with climate variables from a regional climate model. The satellite-derived start of season was determined from daily Moderate Resolution Imaging Spectrometer (MODIS time series of Fractional Snow Cover and the Normalized Difference Water Index by applying methods that were targeted to the two forest types. The accuracy of the satellite-derived start of season in deciduous forest was assessed with bud break observations of birch and a root mean square error of seven days was obtained. The evaluation of JSBACH modelled start of season dates with satellite observations revealed high spatial correspondence. The bias was less than five days for both forest types but showed regional differences that need further consideration. The agreement with satellite observations was slightly better for the evergreen than for the deciduous forest. Nonetheless, comparison with gross primary production (GPP determined from CO2 flux measurements at two eddy covariance sites in evergreen forest revealed that the JSBACH-simulated GPP was higher in early spring and led to too-early simulated start of season dates. Photosynthetic activity recovers differently in evergreen and deciduous forests. While for the deciduous forest calibration of phenology alone could improve the performance of JSBACH, for the evergreen forest, changes such as seasonality of temperature response, would need to be introduced to the photosynthetic capacity to improve the temporal development of gross primary production.

  2. The new Caribbean Nitrogen Index to assess nitrogen dynamics in vegetable production systems in southwestern Puerto Rico

    Directory of Open Access Journals (Sweden)

    Miguel Oliveras-Berrocales

    2017-03-01

    Full Text Available Nutrient loss from agricultural fields is one of the main factors influencing surface- and ground-water quality. Typical fertilizer nitrogen (N consumption rates in vegetable production systems and horticultural crops in Puerto Rico fluctuate between 112 and 253 kg N/ha. The nitrogen use efficiency of vegetable crops is low, increasing the potential for nitrogen losses and high residual soil nitrate content. Quantification of residual soil N and N losses to the environment can be a difficult task. Simulation models such as the USDA-ARS N Index can be used to identify the relative magnitude of varying N-loss pathways and to identify best management practices. Field studies were conducted to quantify residual soil N and crop N removal, and to validate the Nitrogen Index in onion, tropical pumpkin and tomato production systems in the Lajas Valley in southwestern Puerto Rico. Relationships between observed and simulated values were determined to examine the capability of the model for evaluating N losses. There was good correlation between observed and predicted values for residual soil N (r =0.88 and crop N removal (r =0.99 (p<0.05. In the production systems evaluated, the N volatilization losses ranged from 1 to 4 kg N/ha, the denitrification losses ranged from 18 to 46 kg N/ha, the leaching losses ranged from 155 to 779 kg N/ha, and the residual soil nitrate ranged from 64 to 401 kg N/ha. The N use efficiency ranged from 15% to 39%. The results obtained showed that the Nitrogen Index tool can be a useful tool for evaluating N transformations in vegetable production systems of Puerto Rico's semi-arid zone.

  3. Estimating evapotranspiration using remote sensing: A hybrid approach between MODIS derived enhanced vegetation index, Bowen ratio system, and ground based micro-meteorological data

    Science.gov (United States)

    Chatterjee, Sumantra

    We investigated water loss by evapotranspiration (ET) from the Palo Verde Irrigation District (PVID) and the Cibola National Wildlife Refuge (CNWR) in southern California bordering the Colorado River collaborating with the United States Bureau of Reclamation (U.S.B.R.). We developed an empirical model to estimate ET for the entire PVID using satellite derived MODIS enhanced vegetation index (EVI), and ground based measurements of solar radiation and vapor pressure. We compared our predictions with U.S.B.R. estimates through statistical cross validation and showed they agree with an error less than 8%. We tested the same model for an alfalfa field inside PVID to check its applicability at a smaller spatial scale. We showed that the same model developed for PVID is the best model for estimating ET for the alfalfa field. We collected data from three Bowen ratio energy balance (BREB) towers installed in the invasive saltcedar (Tamarix spp) dominated riparian zone in the CNWR and a fourth tower in the alfalfa field in PVID. The riparian sites were selected according to different densities of vegetation. We collected data from these sites at various intervals during the period between June 2006 to November 2008. We reduced the errors associated with the Bowen ratio data using statistical procedures taking into account occasional instrument failures and problems inherent in the BREB method. Our results were consistent with vegetation density and estimates from MODIS EVI images. To estimate ET for larger patches of mixed vegetation we modified the crop coefficient equation and represented it in terms of EVI. Using this approach, we scaled the alfalfa field data to the entire PVID and compared the results with U.S.B.R. (2001-2007) estimates. We predicted ET well within the acceptable range established in the literature. We empirically developed ET models for the riparian tower sites to provide accurate point scale ET estimation and scaled for the entire riparian region in

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

    DEFF Research Database (Denmark)

    Olsen, Jørgen Lundegaard

    on short timescales, which are challenging from polar orbiting instruments. Geostationary NDVI and the NIR and SWIR based Shortwave Infrared Water Stress Index (SIWSI) indices are compared with extensive field data from the Dahra site, supplemented by data from the Agoufou and Demokeya sites. The indices...

  5. Vegetation index-based crop coefficients to estimate evapotranspiration by remote sensing in agricultural and natural ecosystems

    Science.gov (United States)

    Glenn, E.P.; Neale, C. M. U.; Hunsaker, D.J.; Nagler, P.L.

    2011-01-01

    Crop coefficients were developed to determine crop water needs based on the evapotranspiration (ET) of a reference crop under a given set of meteorological conditions. Starting in the 1980s, crop coefficients developed through lysimeter studies or set by expert opinion began to be supplemented by remotely sensed vegetation indices (VI) that measured the actual status of the crop on a field-by-field basis. VIs measure the density of green foliage based on the reflectance of visible and near infrared (NIR) light from the canopy, and are highly correlated with plant physiological processes that depend on light absorption by a canopy such as ET and photosynthesis. Reflectance-based crop coefficients have now been developed for numerous individual crops, including corn, wheat, alfalfa, cotton, potato, sugar beet, vegetables, grapes and orchard crops. Other research has shown that VIs can be used to predict ET over fields of mixed crops, allowing them to be used to monitor ET over entire irrigation districts. VI-based crop coefficients can help reduce agricultural water use by matching irrigation rates to the actual water needs of a crop as it grows instead of to a modeled crop growing under optimal conditions. Recently, the concept has been applied to natural ecosystems at the local, regional and continental scales of measurement, using time-series satellite data from the MODIS sensors on the Terra satellite. VIs or other visible-NIR band algorithms are combined with meteorological data to predict ET in numerous biome types, from deserts, to arctic tundra, to tropical rainforests. These methods often closely match ET measured on the ground at the global FluxNet array of eddy covariance moisture and carbon flux towers. The primary advantage of VI methods for estimating ET is that transpiration is closely related to radiation absorbed by the plant canopy, which is closely related to VIs. The primary disadvantage is that they cannot capture stress effects or soil

  6. Evaluating Landsat 8 Satellite Sensor Data for Improved Vegetation Mapping Accuracy of the New Hampshire Coastal Watershed Area

    Science.gov (United States)

    Ledoux, Lindsay

    Remote sensing is a technology that has been used for many years to generate land cover maps. These maps provide insight as to the landscape, and features that are on the ground. One way in which this is useful is through the visualization of forest cover types. The forests of New England have been notoriously difficult to map, due to their high complexity and fine-scale heterogeneity. In order to be able to better map these features, the newest satellite imagery available may be the best technology to use. Landsat 8 is the newest satellite created by a team of scientists and engineers from the United States Geological Survey and the National Aeronautics and Space Administration, and was launched in February of 2013. The Landsat 8 satellite sensor is considered an improvement over previous Landsat sensors, as it has three additional bands: (1) a coastal/ aerosol band, band 1, that senses light in deep blue, (2) a cirrus band, band 9, that provides detection of wispy clouds that may interfere with analysis, and (3) a Quality Assessment band whose bits contain information regarding conditions that may affect the quality and applicability of certain image pixels. In addition to these added bands, the data generated by Landsat 8 are delivered at an increased radiometric resolution compared with previous Landsat sensors, increasing the dynamic range of the data the sensor can retrieve. In order to investigate the satellite sensor data, a novel approach to classifying Landsat 8 imagery was used. Object-Based Image Analysis was employed, along with the random forest machine learning classifier, to segment and classify the land cover of the Coastal Watershed of southeastern New Hampshire. In order to account strictly for band improvements, supervised classification using the maximum likelihood classifier was completed, on imagery created: (1) using all of the original bands provided by Landsat 8, and (2) an image created using Landsat 8 bands that were only available on

  7. Ten Years of Vegetation Change in Northern California Marshlands Detected using Landsat Satellite Image Analysis

    Science.gov (United States)

    Potter, Christopher

    2013-01-01

    The Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS) methodology was applied to detected changes in perennial vegetation cover at marshland sites in Northern California reported to have undergone restoration between 1999 and 2009. Results showed extensive contiguous areas of restored marshland plant cover at 10 of the 14 sites selected. Gains in either woody shrub cover and/or from recovery of herbaceous cover that remains productive and evergreen on a year-round basis could be mapped out from the image results. However, LEDAPS may not be highly sensitive changes in wetlands that have been restored mainly with seasonal herbaceous cover (e.g., vernal pools), due to the ephemeral nature of the plant greenness signal. Based on this evaluation, the LEDAPS methodology would be capable of fulfilling a pressing need for consistent, continual, low-cost monitoring of changes in marshland ecosystems of the Pacific Flyway.

  8. Crop Species Recognition and Discrimination Paddy-Rice from Reaped-Fields by the Radar Vegetation Index (rvi) of ALOS-2/PALSAR2

    Science.gov (United States)

    Yamada, Y.

    2016-06-01

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

  9. Seasonal relationship between normalized difference vegetation index and abundance of the Phlebotomus kala-azar vector in an endemic focus in Bihar, India

    Directory of Open Access Journals (Sweden)

    Gouri S. Bhunia

    2012-11-01

    Full Text Available Remote sensing was applied for the collection of spatio-temporal data to increase our understanding of the potential distribution of the kala-azar vector Phlebotomus argentipes in endemic areas of the Vaishali district of Bihar, India. We produced monthly distribution maps of the normalized difference vegetation index (NDVI based on data from the thematic mapper (TM sensor onboard the Landsat-5 satellite. Minimum, maximum and mean NDVI values were computed for each month and compared with the concurrent incidence of kala-azar and the vector density. Maximum and mean NDVI values (R2 = 0.55 and R2 = 0.60, respectively, as well as the season likelihood ratio (X2 = 17.51; P <0.001, were found to be strongly associated with kala-azar, while the correlation with between minimum NDVI values and kala-azar was weak (R2 = 0.25. Additionally, a strong association was found between the mean and maximum NDVI values with seasonal vector abundance (R2 = 0.60 and R2 = 0.55, respectively but there was only a marginal association between minimum NDVI value and the spatial distribution of kala-azar vis-à-vis P. argentipes density.

  10. Assessment of climate impact on vegetation dynamics by using remote sensing

    NARCIS (Netherlands)

    Roerink, G.J.; Menenti, M.; Soepboer, W.; Su, Z.

    2003-01-01

    Climate variability has a large impact on the vegetation dynamics. To quantify this impact a study is carried out with Normalized Difference Vegetation Index (NDVI) satellite images and meteorological data over part of Sahelian Africa and Europe over several years. The vegetation dynamics are quanti

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

    Directory of Open Access Journals (Sweden)

    Thomas P. Higginbottom

    2014-10-01

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

  12. A combined deficit index for regional agricultural drought assessment over semi-arid tract of India using geostationary meteorological satellite data

    Science.gov (United States)

    Vyas, Swapnil S.; Bhattacharya, Bimal K.; Nigam, Rahul; Guhathakurta, Pulak; Ghosh, Kripan; Chattopadhyay, N.; Gairola, R. M.

    2015-07-01

    The untimely onset and uneven distribution of south-west monsoon rainfall lead to agricultural drought causing reduction in food-grain production with high vulnerability over semi-arid tract (SAT) of India. A combined deficit index (CDI) has been developed from tri-monthly sum of deficit in antecedent rainfall and deficit in monthly vegetation vigor with a lag period of one month between the two. The formulation of CDI used a core biophysical (e.g., NDVI) and a hydro-meteorological (e.g., rainfall) variables derived using observation from Indian geostationary satellites. The CDI was tested and evaluated in two drought years (2009 and 2012) within a span of five years (2009-2013) over SAT. The index was found to have good correlation (0.49-0.68) with standardized precipitation index (SPI) computed from rain-gauge measurements but showed lower correlation with anomaly in monthly land surface temperature (LST). Significant correlations were found between CDI and reduction in agricultural carbon productivity (0.67-0.83), evapotranspiration (0.64-0.73), agricultural grain yield (0.70-0.85). Inconsistent correlation between CDI and ET reduction was noticed in 2012 in contrast to consistent correlation between CDI and reduction in carbon productivity both in 2009 and 2012. The comparison of CDI-based drought-affected area with those from existing operational approach showed 75% overlapping regions though class-to-class matching was only 40-45%. The results demonstrated that CDI is a potential indicator for assessment of late-season regional agricultural drought based on lag-response between water supply and crop vigor.

  13. Large Differences in Terrestrial Vegetation Production Derived from Satellite-Based Light Use Efficiency Models

    Directory of Open Access Journals (Sweden)

    Wenwen Cai

    2014-09-01

    Full Text Available Terrestrial gross primary production (GPP is the largest global CO2 flux and determines other ecosystem carbon cycle variables. Light use efficiency (LUE models may have the most potential to adequately address the spatial and temporal dynamics of GPP, but recent studies have shown large model differences in GPP simulations. In this study, we investigated the GPP differences in the spatial and temporal patterns derived from seven widely used LUE models at the global scale. The result shows that the global annual GPP estimates over the period 2000–2010 varied from 95.10 to 139.71 Pg C∙yr−1 among models. The spatial and temporal variation of global GPP differs substantially between models, due to different model structures and dominant environmental drivers. In almost all models, water availability dominates the interannual variability of GPP over large vegetated areas. Solar radiation and air temperature are not the primary controlling factors for interannual variability of global GPP estimates for most models. The disagreement among the current LUE models highlights the need for further model improvement to quantify the global carbon cycle.

  14. Spectra and vegetation index variations in moss soil crust in different seasons, and in wet and dry conditions

    Science.gov (United States)

    Fang, Shibo; Yu, Weiguo; Qi, Yue

    2015-06-01

    Similar to vascular plants, non-vascular plant mosses have different periods of seasonal growth. There has been little research on the spectral variations of moss soil crust (MSC) over different growth periods. Few studies have paid attention to the difference in spectral characteristics between wet MSC that is photosynthesizing and dry MSC in suspended metabolism. The dissimilarity of MSC spectra in wet and dry conditions during different seasons needs further investigation. In this study, the spectral reflectance of wet MSC, dry MSC and the dominant vascular plant (Artemisia) were characterized in situ during the summer (July) and autumn (September). The variations in the normalized difference vegetation index (NDVI), biological soil crust index (BSCI) and CI (crust index) in different seasons and under different soil moisture conditions were also analyzed. It was found that (1) the spectral characteristics of both wet and dry MSCs varied seasonally; (2) the spectral features of wet MSC appear similar to those of the vascular plant, Artemisia, whether in summer or autumn; (3) both in summer and in autumn, much higher NDVI values were acquired for wet than for dry MSC (0.6 ∼ 0.7 vs. 0.3 ∼ 0.4 units), which may lead to misinterpretation of vegetation dynamics in the presence of MSC and with the variations in rainfall occurring in arid and semi-arid zones; and (4) the BSCI and CI values of wet MSC were close to that of Artemisia in both summer and autumn, indicating that BSCI and CI could barely differentiate between the wet MSC and Artemisia.

  15. Estimation of Anticipated Performance Index and Air Pollution Tolerance Index and of vegetation around the marble industrial areas of Potwar region: bioindicators of plant pollution response.

    Science.gov (United States)

    Noor, Mehwish Jamil; Sultana, Shazia; Fatima, Sonia; Ahmad, Mushtaq; Zafar, Muhammad; Sarfraz, Maliha; Balkhyour, Masour A; Safi, Sher Zaman; Ashraf, Muhammad Aqeel

    2015-06-01

    Mitigating industrial air pollution is a big challenge, in such scenario screening of plants as a bio monitor is extremely significant. It requires proper selection and screening of sensitive and tolerant plant species which are bio indicator and sink for air pollution. The present study was designed to evaluate the Air Pollution Tolerance Index (APTI) and Anticipated Performance Index (API) of the common flora. Fifteen common plant species from among trees, herb and shrubs i.e. Chenopodium album (Chenopodiaceae), Parthenium hysterophorus (Asteraceae), Amaranthus viridis (Amaranthaceae), Lantana camara (Verbenaceaea), Ziziphus nummulari (Rhamnaceae), Silibum merianum (Asteraceae), Cannabis sativa (Cannabinaceae), Calatropis procera (Asclepediaceae), Ricinus communis (Euphorbiaceae), Melia azadirachta (Meliaceae), Psidium guajava (Myrtaceae), Eucalyptus globules (Myrtaceae), Broussonetia papyrifera (Moraceae), Withania somnifera (Solanaceae) and Sapium sabiferum (Euphorbiaceae) were selected growing frequently in vicinity of Marble industries in Potwar region. APTI and API of selected plant species were analyzed by determining important biochemical parameter i.e. total chlorophyll, ascorbic acid, relative water content and pH etc. Furthermore the selected vegetation was studied for physiological, economic, morphological and biological characteristics. The soil of studied sites was analyzed. It was found that most the selected plant species are sensitive to air pollution. However B. papyrifera, E. globulus and R. communis shows the highest API and therefore recommended for plantation in marble dust pollution stress area.

  16. Satellites Based Annual Carbon Dynamics of Africa Tropical Vegetation During the 2003-2014 Period

    Science.gov (United States)

    Baccini, A.

    2015-12-01

    Tracking terrestrial carbon fluxes and predicting how tropical forests will respond to continuous global change requires accurate estimates of annual changes in the density and distribution of carbon stocks at local to global scales. Existing evidence for tropical forests as a carbon sink is based on a limited number of repeated field measurements (Phillips et al. 1998,Lewis et al. 2009, Brienen et al. 2015), while spatially explicit estimates over large areas are limited to emissions derived from deforestation without being able to account for degradation and gain (Harris et al. 2012, Hansen et al. 2013). Here we use 12 years (2003-2014) of satellite data to quantify wall-to-wall annual net changes in aboveground carbon density, showing that Africa tropical forests are a net carbon source on the order of 72.1 ± 32.9 Tg C yr-1. This net release of carbon consists of losses of 205.0 ± 24.7 Tg C yr1 and gains of -132.9 ± 19.3 Tg C yr1. The net gains result from forest growth; net losses result from both reductions in forest area due to deforestation and in biomass density within forests due to degradation; this last accounting overall for 68.9 % of the losses. We anticipate several advantages over the traditional estimates. It measures carbon lost from forest degradation as well as from deforestation. It measures the gains of carbon in forest growth. Data are available to determine annual changes with associated uncertainty. The approach focuses directly on changes in carbon. While global emissions from fossil fuel stabilized in 2014 for the first time in the past 40 years, results from this study indicate that the annual rate of emissions from tropical forests has tended upward over the latest years of the 2003-2014 period.

  17. Assessing the Impacts of the 2009/2010 Drought on Vegetation Indices, Normalized Difference Water Index, and Land Surface Temperature in Southwestern China

    Directory of Open Access Journals (Sweden)

    Xiaoqiang Zhang

    2017-01-01

    Full Text Available Droughts are projected to increase in severity and frequency on both regional and global scales. Despite the increasing occurrence and intensity of the 2009/2010 drought in southwestern China, the impacts of drought on vegetation in this region remain unclear. We examined the impacts of the 2009/2010 drought in southwestern China on vegetation by calculating the standardized anomalies of Normalized Difference Vegetation Index (NDVI, Enhanced Vegetation Index (EVI, Normalized Difference Water Index (NDWI, and Land Surface Temperature (LST. The standardized anomalies of NDVI, EVI, and NDWI exhibited positively skewed frequency distributions, while the standardized anomalies of LST exhibited a negatively skewed frequency distribution. These results implied that the NDVI, EVI, and NDWI declined, while LST increased in the 2009/2010 drought-stricken vegetated areas during the drought period. The responses of vegetation to the 2009/2010 drought differed substantially among biomes. Savannas, croplands, and mixed forests were more vulnerable to the 2009/2010 drought than deciduous forest and grasslands, while evergreen forest was resistant to the 2009/2010 drought in southwestern China. We concluded that the 2009/2010 drought had negative impacts on vegetation in southwestern China. The resulting assessment on the impacts of drought assists in evaluating and mitigating its adverse effects in southwestern China.

  18. 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

    Directory of Open Access Journals (Sweden)

    Arne Torbjørn Høstmark

    2011-01-01

    Full Text Available 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.

  19. 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.

  20. 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

  1. Quality of Life Assessment Based on Spatial and Temporal Analysis of the Vegetation Area Derived from Satellite Images

    Directory of Open Access Journals (Sweden)

    MARIA IOANA VLAD

    2011-01-01

    Full Text Available The quality of life in urban areas is a function of many parameters among which, one highly important is the number and quality of green areas for people and wildlife to thrive. The quality of life is also a political concept often used to describe citizen satisfaction within different residential locations. Only in the last decades green areas have suffered a progressive decrease in quality, pointing out the ecological urban risk with a negative impact on the standard of living and population health status. This paper presents the evolution of green areas in the cities of South-Eastern Romania within the last 20 years and sets forth the current state of quality of life from the perspective of vegetation reference. By using state-of-the-art processing tools applied on high-resolution satellite images, we have derived knowledge about the spatial and temporal expansion of urbanized regions. Our semi-automatic technologies for analysis of remote sensing data such as Landsat 7 ETM+, correlated with statistical information inferred from urban charts, demonstrate a negative trend in the distribution of green areas within the analyzed cities, with long-term implications on multiple areas in our lives.

  2. Mapping species of submerged aquatic vegetation with multi-seasonal satellite images and considering life history information

    Science.gov (United States)

    Luo, Juhua; Duan, Hongtao; Ma, Ronghua; Jin, Xiuliang; Li, Fei; Hu, Weiping; Shi, Kun; Huang, Wenjiang

    2017-05-01

    Spatial information of the dominant species of submerged aquatic vegetation (SAV) is essential for restoration projects in eutrophic lakes, especially eutrophic Taihu Lake, China. Mapping the distribution of SAV species is very challenging and difficult using only multispectral satellite remote sensing. In this study, we proposed an approach to map the distribution of seven dominant species of SAV in Taihu Lake. Our approach involved information on the life histories of the seven SAV species and eight distribution maps of SAV from February to October. The life history information of the dominant SAV species was summarized from the literature and field surveys. Eight distribution maps of the SAV were extracted from eight 30 m HJ-CCD images from February to October in 2013 based on the classification tree models, and the overall classification accuracies for the SAV were greater than 80%. Finally, the spatial distribution of the SAV species in Taihu in 2013 was mapped using multilayer erasing approach. Based on validation, the overall classification accuracy for the seven species was 68.4%, and kappa was 0.6306, which suggests that larger differences in life histories between species can produce higher identification accuracies. The classification results show that Potamogeton malaianus was the most widely distributed species in Taihu Lake, followed by Myriophyllum spicatum, Potamogeton maackianus, Potamogeton crispus, Elodea nuttallii, Ceratophyllum demersum and Vallisneria spiralis. The information is useful for planning shallow-water habitat restoration projects.

  3. 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.

  4. Monitoring and Characterizing Seasonal Drought, Water Supply Pattern and Their Impact on Vegetation Growth Using Satellite Soil Moisture Data, GRACE Water Storage and In-situ Observations.

    Science.gov (United States)

    A, G.; Velicogna, I.; Kimball, J. S.; Kim, Y.; Colliander, A.; Njoku, E. G.

    2015-12-01

    We combine soil moisture (SM) data from AMSR-E, AMSR-2 and SMAP, terrestrial water storage (TWS) changes from GRACE, in-situ groundwater measurements and atmospheric moisture data to delineate and characterize the evolution of drought and its impact on vegetation growth. GRACE TWS provides spatially continuous observations of total terrestrial water storage changes and regional drought extent, persistence and severity, while satellite derived soil moisture estimates provide enhanced delineation of plant-available soil moisture. Together these data provide complementary metrics quantifying available plant water supply. We use these data to investigate the supply changes from water components at different depth in relation to satellite based vegetation metrics, including vegetation greenness (NDVI) measures from MODIS and related higher order productivity (GPP) before, during and following the major drought events observed in the continental US for the past 14 years. We observe consistent trends and significant correlations between monthly time series of TWS, SM, NDVI and GPP. We study how changes in atmosphere moisture stress and coupling of water storage components at different depth impact on the spatial and temporal correlation between TWS, SM and vegetation metrics. In Texas, we find that surface SM and GRACE TWS agree with each other in general, and both capture the underlying water supply constraints to vegetation growth. Triggered by a transit increase in precipitation following the 2011 hydrological drought, vegetation productivity in Texas shows more sensitivity to surface SM than TWS. In the Great Plains, the correspondence between TWS and vegetation productivity is modulated by temperature-induced atmosphere moisture stress and by the coupling between surface soil moisture and groundwater through irrigation.

  5. Assessment of Land Use-Cover Changes and Successional Stages of Vegetation in the Natural Protected Area Altas Cumbres, Northeastern Mexico, Using Landsat Satellite Imagery

    Directory of Open Access Journals (Sweden)

    Uriel Jeshua Sánchez-Reyes

    2017-07-01

    Full Text Available Loss of vegetation cover is a major factor that endangers biodiversity. Therefore, the use of geographic information systems and the analysis of satellite images are important for monitoring these changes in Natural Protected Areas (NPAs. In northeastern Mexico, the Natural Protected Area Altas Cumbres (NPAAC represents a relevant floristic and faunistic patch on which the impact of loss of vegetation cover has not been assessed. This work aimed to analyze changes of land use and coverage (LULCC over the last 42 years on the interior and around the exterior of the area, and also to propose the time of succession for the most important types of vegetation. For the analysis, LANDSAT satellite images from 1973, 1986, 2000, 2005 and 2015 were used, they were classified in seven categories through a segmentation and maximum likelihood analysis. A cross-tabulation analysis was performed to determine the succession gradient. Towards the interior of the area, a significant reduction of tropical vegetation and, to a lesser extent, temperate forests was found, as well as an increase in scrub cover from 1973 to 2015. In addition, urban and vegetation-free areas, as well as modified vegetation, increased to the exterior. Towards the interior of the NPA, the processes of perturbation and recovery were mostly not linear, while in the exterior adjacent area, the presence of secondary vegetation with distinct definite time of succession was evident. The analysis carried out is the first contribution that evaluates LULCC in this important NPA of northeastern Mexico. Results suggest the need to evaluate the effects of these modifications on species.

  6. Characterizing Seasonal Drought, Water Supply Pattern and Their Impact on Vegetation Growth Using Satellite Soil Moisture Data, GRACE Water Storage and Precipitation Observations

    Science.gov (United States)

    A, G.; Velicogna, I.; Kimball, J. S.; Du, J.; Kim, Y.; Njoku, E. G.; Colliander, A.

    2016-12-01

    We combine soil moisture (SM) data from AMSR-E, AMSR-2 and SMAP, terrestrial water storage (TWS) changes from GRACE and precipitation measurements from GPCP to delineate and characterize drought and water supply pattern and its impact on vegetation growth. GRACE TWS provides spatially continuous observations of total terrestrial water storage changes and regional drought extent, persistence and severity, while satellite derived soil moisture estimates provide enhanced delineation of plant-available soil moisture. Together these data provide complementary metrics quantifying available plant water supply and have important implications for water resource management. We use these data to investigate the supply changes from different water components in relation to satellite based vegetation productivity metrics from MODIS, before, during and following the major drought events observed in the continental US during the past 13 years. We observe consistent trends and significant correlations between monthly time series of TWS, SM, and vegetation productivity. In Texas and surrounding semi-arid areas, we find that the spatial pattern of the vegetation-moisture relation follows the gradient in mean annual precipitation. In Texas, GRACE TWS and surface SM show strong coupling and similar characteristic time scale in relatively normal years, while during the 2011 onward hydrological drought, GRACE TWS manifests a longer time scale than that of surface SM, implying stronger drought persistence in deeper water storage. In the Missouri watershed, we find a spatially varying vegetation-moisture relationship where in the drier northwestern portion of the basin, the inter-annual variability in summer vegetation productivity is closely associated with changes in carry-on GRACE TWS from spring, whereas in the moist southeastern portion of the basin, summer precipitation is the dominant controlling factor on vegetation growth.

  7. A Satellite-Based Multi-Pollutant Index of Global Air Quality

    Science.gov (United States)

    Cooper, Mathew J.; Martin, Randall V.; vanDonkelaar, Aaron; Lamsal, Lok; Brauer, Michael; Brook, Jeffrey R.

    2012-01-01

    Air pollution is a major health hazard that is responsible formillions of annual excess deaths worldwide. Simpleindicators are useful for comparative studies and to asses strends over time. The development of global indicators hasbeen impeded by the lack of ground-based observations in vast regions of the world. Recognition is growing of the need for amultipollutant approach to air quality to better represent human exposure. Here we introduce the prospect of amultipollutant air quality indicator based on observations from satellite remote sensing.

  8. Accuracy of the Temperature-Vegetation Dryness Index using MODIS under water-limited vs. energy-limited evapotranspiration conditions

    DEFF Research Database (Denmark)

    Garcia, Monica; Fernández, N.; Villagarcía, L.

    2014-01-01

    water is the main control in dryland ecosystems, these can also undergo periods of energy and temperature limitation. In this paper we aimed to: (i) evaluate the TVDI (Temperature-Vegetation Dryness Index) to estimate water deficits (e.g. ratio between actual and potential evapotranspiration), and heat......Water deficit indices based on the spatial relationship between surface temperature (Ts) and NDVI, known as triangle approaches, are widely used for drought monitoring. However, their application has been recently questioned when the main factor limiting evapotranspiration is energy. Even though...... surface fluxes using MODIS data; and (ii) provide insights about the factors most affecting the accuracy of results. Factors considered included the type of climatic control on evapotranspiration, λE, (i.e. water-limited vs. energy-limited), the quality of Tair estimates, the heterogeneity of land cover...

  9. Land Surface Temperature Retrieval in Wetlands Using Normalized Difference Vegetation Index-Emissivity Estimation and ASTER Emissivity Product

    Science.gov (United States)

    Muro, Javier; Heinmann, Sascha; Strauch, Adrian; Menz, Gunter

    2016-08-01

    Land Surface Temperature (LST) has the potential to act as a continuous indicator of the ecological status of wetlands. Accurate emissivity values are required in order to calculate precise LST. We test two emissivity retrieval methods and their influence on LST calculated from a Landsat 7 image of a highly dynamic wetland in Southern Spain. LST calculated using NDVI (Normalized Difference Vegetation Index) threshold estimations and the ASTER emissivity product are compared. The results show differences of around 0-1 K for most land covers, and up to 3 K for areas of bare soil when Landsat and ASTER images have the same acquisition date. Tests using Landsat and ASTER images from different seasons do not show greater differences between both LSTs. This has important implications for automated LST retrieval methods, such as the one planed by the USGS using Landsat and ASTER emissivity products.

  10. Investigation of the recent recolonisation of Beech on Mont Ventoux using historical records, vegetation analyses from satellite image and landscape genetics

    OpenAIRE

    Prouillet-Leplat, Hélène

    2009-01-01

    In this study, we investigated the genetic structure and the recolonisation process of the European beech (Fagus sylvatica) over the north face of the Mont Ventoux Mountain, using of combination of historical record investigation, vegetation mapping from satellite image and unsupervised classification process, and a landscape genetic approach. Mont Ventoux has undergone large deforestation phases until the XIXth century due to over-grazing and over-logging for woof supply. Historical records ...

  11. An intercomparison of Satellite Burned Area Maps derived from MODIS, MERIS, SPOT-VEGETATION, and ATSR images. An application to the August 2006 Galicia (Spain forest fires

    Directory of Open Access Journals (Sweden)

    M. Huesca

    2013-07-01

    : Earth Observation System; ESA: European Space Agency; GBA2000: Global Burnt Area 2000; GLOBCARBON-BAE: GLOBCARBON Burnt Area Estimate Product; L3JRC: Terrestrial Ecosystem Monitoring Global Burnt Area Product; MCD45A1: MODIS Burned Area Product; MERIS: MEdium Resolution Imaging Spectrometer; MOD09GA: Terra MODIS Surface Reflectance Daily L2G Global 500 m; MOD09GQ: Terra MODIS Surface Reflectance Daily L2G Global 250 m; MODIS: MODerate resolution Imaging Spectrometer; NBR: Normalized Burn Ratio; NDVI: Normalized Difference Vegetation Index; NIR: near-infrared; SPOT: Satellite Pour l’Observation de la Terre; SWIR: short-wave infrared; UTM: Universal Transverse Mercator.

  12. Predicting bird phenology from space: satellite-derived vegetation green-up signal uncovers spatial variation in phenological synchrony between birds and their environment.

    Science.gov (United States)

    Cole, Ella F; Long, Peter R; Zelazowski, Przemyslaw; Szulkin, Marta; Sheldon, Ben C

    2015-11-01

    Population-level studies of how tit species (Parus spp.) track the changing phenology of their caterpillar food source have provided a model system allowing inference into how populations can adjust to changing climates, but are often limited because they implicitly assume all individuals experience similar environments. Ecologists are increasingly using satellite-derived data to quantify aspects of animals' environments, but so far studies examining phenology have generally done so at large spatial scales. Considering the scale at which individuals experience their environment is likely to be key if we are to understand the ecological and evolutionary processes acting on reproductive phenology within populations. Here, we use time series of satellite images, with a resolution of 240 m, to quantify spatial variation in vegetation green-up for a 385-ha mixed-deciduous woodland. Using data spanning 13 years, we demonstrate that annual population-level measures of the timing of peak abundance of winter moth larvae (Operophtera brumata) and the timing of egg laying in great tits (Parus major) and blue tits (Cyanistes caeruleus) is related to satellite-derived spring vegetation phenology. We go on to show that timing of local vegetation green-up significantly explained individual differences in tit reproductive phenology within the population, and that the degree of synchrony between bird and vegetation phenology showed marked spatial variation across the woodland. Areas of high oak tree (Quercus robur) and hazel (Corylus avellana) density showed the strongest match between remote-sensed vegetation phenology and reproductive phenology in both species. Marked within-population variation in the extent to which phenology of different trophic levels match suggests that more attention should be given to small-scale processes when exploring the causes and consequences of phenological matching. We discuss how use of remotely sensed data to study within-population variation

  13. Mapping rice cropping systems using Landsat-derived Renormalized Index of Normalized Difference Vegetation Index (RNDVI) in the Poyang Lake Region, China

    Science.gov (United States)

    Li, Peng; Jiang, Luguang; Feng, Zhiming; Sheldon, Sage; Xiao, Xiangming

    2016-06-01

    Mapping rice cropping systems with optical imagery in multiple cropping regions is challenging due to cloud contamination and data availability; development of a phenology-based algorithm with a reduced data demand is essential. In this study, the Landsat-derived Renormalized Index of Normalized Difference Vegetation Index (RNDVI) was proposed based on two temporal windows in which the NDVI values of single and early (or late) rice display inverse changes, and then applied to discriminate rice cropping systems. The Poyang Lake Region (PLR), characterized by a typical cropping system of single cropping rice (SCR, or single rice) and double cropping rice (DCR, including early rice and late rice), was selected as a testing area. The results showed that NDVI data derived from Landsat time-series at eight to sixteen days captures the temporal development of paddy rice. There are two key phenological stages during the overlapping growth period in which the NDVI values of SCR and DCR change inversely, namely the ripening phase of early rice and the growing phase of single rice as well as the ripening stage of single rice and the growing stage of late rice. NDVI derived from scenes in two temporal windows, specifically early August and early October, was used to construct the RNDVI for discriminating rice cropping systems in the polder area of the PLR, China. Comparison with ground truth data indicates high classification accuracy. The RNDVI approach highlights the inverse variations of NDVI values due to the difference of rice growth between two temporal windows. This makes the discrimination of rice cropping systems straightforward as it only needs to distinguish whether the candidate rice type is in the period of growth (RNDVI0).

  14. Trends in the normalized difference vegetation index (NDVI) associated with urban development in arctic and subarctic Western Siberia

    Science.gov (United States)

    Outten, S.; Miles, V.; Ezau, I.

    2015-12-01

    Changes in normalized difference vegetation index (NDVI) in the high Arctic have been reliably documented, with widespread "greening" (increase in NDVI), specifically along the northern rim of Eurasia and Alaska. Whereas in West Siberia south of 65N, widespread "browning" (decrease in NDVI) has been noted, although the causes remain largely unclear. In this study we report results of statistical analysis of the spatial and temporal changes in NDVI around 28 major urban areas in the arctic and subarctic Western Siberia. Exploration and exploitation of oil and gas reserves has led to rapid industrialization and urban development in the region. This development has significant impact on the environment and particularly in the vegetation cover in and around the urbanized areas. The analysis is based on 15 years (2000-2014) of high-resolution (250 m) Moderate Resolution Imaging Spectroradiometer (MODIS) data acquired for summer months (June through August) over the entire arctic and subarctic Western Siberian region. The analysis shows that the NDVI background trends are generally in agreement with the trends reported in previous coarse-resolution NDVI studies. Our study reveals greening over the arctic (tundra and tundra-forest) part of the region. Simultaneously, the southern (boreal taiga forest) part is browning, with the more densely vegetation areas or areas with highest NDVI, particularly along Ob River showing strong negative trend. The unexpected and interesting finding of the study is statistically robust indication of the accelerated increase of NDVI ("greening") in the older urban areas. Many Siberian cities become greener even against the decrease in the NDVI background. Moreover, interannual variations of urban NDVI are not coherent with the NDVI background variability. We also find that in tundra zones, NDVI values are higher in a 5-10 km buffer zone around the city edge than in rural areas (40 km distance from the city edge), and in taiga in a 5-10 km

  15. 基于冠层反射和植被指数的华东地区叶面指数反演%Leaf area index retrieval based on canopy reflectance and vegetation index in eastern China

    Institute of Scientific and Technical Information of China (English)

    蒋建军; 陈锁忠; 曹顺仙

    2005-01-01

    The aim of this paper is to investigate the feasibility of using Landsat TM data to retrieve leaf area index (LAI). To get a LAI retrieval model based ground reflectance and vegetation index, detailed field data were collected in the study area of eastern China, dominated by bamboo, tea plant and greengage. Plant canopy reflectance of Landsat TM wavelength bands has been inversed using software of 6S. LAI is an important ecological parameter. In this paper, atmospheric corrected Landsat TM imagery was utilized to calculate different vegetation indices (VI), such as simple ratio vegetation index (SR), shortwave infrared modified simple ratio (MSR), and normalized difference vegetation index (NDVI). Data of 53 samples of LAI were measured by LAI-2000 (LI-COR) in the study area. LAI was modeled based on different reflectances of bands and different vegetation indices from Landsat TM and LAI samples data. There are certainly correlations between LAI and the reflectance of TM3, TM4, TM5 and TM7. The best model through analyzing the results is LAI = 1.2097*MSR +0.4741 using the method of regression analysis. The result shows that the correlation coefficient R2 is 0.5157, and average accuracy is 85.75%. However, whether the model of this paper is suitable for application in subtropics needs to be verified in the future.

  16. Monitoring Crop Yield in USA Using a Satellite-Based Climate-Variability Impact Index

    Science.gov (United States)

    Zhang, Ping; Anderson, Bruce; Tan, Bin; Barlow, Mathew; Myneni, Ranga

    2011-01-01

    A quantitative index is applied to monitor crop growth and predict agricultural yield in continental USA. The Climate-Variability Impact Index (CVII), defined as the monthly contribution to overall anomalies in growth during a given year, is derived from 1-km MODIS Leaf Area Index. The growing-season integrated CVII can provide an estimate of the fractional change in overall growth during a given year. In turn these estimates can provide fine-scale and aggregated information on yield for various crops. Trained from historical records of crop production, a statistical model is used to produce crop yield during the growing season based upon the strong positive relationship between crop yield and the CVII. By examining the model prediction as a function of time, it is possible to determine when the in-season predictive capability plateaus and which months provide the greatest predictive capacity.

  17. Empirical Relationship Between Leaf Biomass of Red Pine Forests and Enhanced Vegetation Index in South Korea Using LANDSAT-5 TM

    Science.gov (United States)

    Gusso, A.; Lee, J.; Son, Y.; Son, Y. M.

    2016-06-01

    Research on forest carbon (C) dynamics has been undertaken due to the importance of forest ecosystems in national C inventories. Currently, the C sequestration of South Korean forests surpasses that of other countries. In South Korea, Pinus densiflora (red pine) is the most abundant tree species. Thus, understanding the growth rate and biomass evolution of red pine forest in South Korea is important for estimating the forest C dynamics. In this paper, we derived empirical relationship between foliage biomass and the no blue band enhanced vegetation index (EVI-2) profile using both field work and multi-temporal Landsat-5 TM remote sensing data to estimate the productivity of forest biomass in South Korea. Our analysis combined a set of 84 Landsat-5 TM images from 28 different dates between 1986 and 2008 to study red pine forest development over time. Field data were collected from 30 plots (0.04 ha) that were irregularly distributed over South Korea. Individual trees were harvested by destructive sampling, and the age of trees were determined by the number of tree rings. The results are realistic (R2&thinsp=&thinsp0.81, p < 0.01) and suggest that the EVI-2 index is able to adequately represent the development profile of foliage biomass in red pine forest growth.

  18. EMPIRICAL RELATIONSHIP BETWEEN LEAF BIOMASS OF RED PINE FORESTS AND ENHANCED VEGETATION INDEX IN SOUTH KOREA USING LANDSAT-5 TM

    Directory of Open Access Journals (Sweden)

    A. Gusso

    2016-06-01

    Full Text Available Research on forest carbon (C dynamics has been undertaken due to the importance of forest ecosystems in national C inventories. Currently, the C sequestration of South Korean forests surpasses that of other countries. In South Korea, Pinus densiflora (red pine is the most abundant tree species. Thus, understanding the growth rate and biomass evolution of red pine forest in South Korea is important for estimating the forest C dynamics. In this paper, we derived empirical relationship between foliage biomass and the no blue band enhanced vegetation index (EVI-2 profile using both field work and multi-temporal Landsat-5 TM remote sensing data to estimate the productivity of forest biomass in South Korea. Our analysis combined a set of 84 Landsat-5 TM images from 28 different dates between 1986 and 2008 to study red pine forest development over time. Field data were collected from 30 plots (0.04 ha that were irregularly distributed over South Korea. Individual trees were harvested by destructive sampling, and the age of trees were determined by the number of tree rings. The results are realistic (R2&thinsp=&thinsp0.81, p < 0.01 and suggest that the EVI-2 index is able to adequately represent the development profile of foliage biomass in red pine forest growth.

  19. Present and future water resources in India: Insights from satellite remote sensing and a dynamic global vegetation model

    Indian Academy of Sciences (India)

    S J Murray

    2013-02-01

    India is a country of particular interest with regard to its future water resources, as it is expected to undergo continued rapid population growth while also being especially sensitive to climate change. The Land-surface Processes and eXchanges Dynamic Global Vegetation Model (LPX-DGVM) is used here to simulate present and future runoff in India using ClimGen pattern-scaled scenarios of 1°, 2° and 4°C temperature increase (scaled to 2050) forced by six general circulation models (GCMs). As is the case with many DGVMs, groundwater storage is not simulated by LPX, so in order to form a more comprehensive understanding of water resources, Gravity Recovery and Climate Experiment (GRACE) satellite estimates for north-west India are incorporated into this study and compared to LPX runoff simulations. Runoff is simulated to have increased slightly (1.5 mm/year) in this region during 2002–2006, while groundwater extractions appear to have been made at rates of 40 ± 10 mm/year. North-west India is simulated to experience considerable increases in runoff by 2070–2099, with a mean change of 189 mm/year for 2°C climate change (although the range of model results, 247 mm/year, demonstrates high uncertainty among GCMs). Precipitation is shown to have an important bearing on runoff generation, while the degree of warming is shown to affect the magnitude of future runoff. This may subsequently influence the longevity of the local groundwater resource. However, at recent rates of depletion and in view of expected population growth, the long-term sustainability of groundwater reserves in north-west India is in doubt.

  20. Land-use regression with long-term satellite-based greenness index and culture-specific sources to model PM2.5 spatial-temporal variability.

    Science.gov (United States)

    Wu, Chih-Da; Chen, Yu-Cheng; Pan, Wen-Chi; Zeng, Yu-Ting; Chen, Mu-Jean; Guo, Yue Leon; Lung, Shih-Chun Candice

    2017-05-01

    This study utilized a long-term satellite-based vegetation index, and considered culture-specific emission sources (temples and Chinese restaurants) with Land-use Regression (LUR) modelling to estimate the spatial-temporal variability of PM2.5 using data from Taipei metropolis, which exhibits typical Asian city characteristics. Annual average PM2.5 concentrations from 2006 to 2012 of 17 air quality monitoring stations established by Environmental Protection Administration of Taiwan were used for model development. PM2.5 measurements from 2013 were used for external data verification. Monthly Normalized Difference Vegetation Index (NDVI) images coupled with buffer analysis were used to assess the spatial-temporal variations of greenness surrounding the monitoring sites. The distribution of temples and Chinese restaurants were included to represent the emission contributions from incense and joss money burning, and gas cooking, respectively. Spearman correlation coefficient and stepwise regression were used for LUR model development, and 10-fold cross-validation and external data verification were applied to verify the model reliability. The results showed a strongly negative correlation (r: -0.71 to -0.77) between NDVI and PM2.5 while temples (r: 0.52 to 0.66) and Chinese restaurants (r: 0.31 to 0.44) were positively correlated to PM2.5 concentrations. With the adjusted model R(2) of 0.89, a cross-validated adj-R(2) of 0.90, and external validated R(2) of 0.83, the high explanatory power of the resultant model was confirmed. Moreover, the averaged NDVI within a 1750 m circular buffer (p < 0.01), the number of Chinese restaurants within a 1750 m buffer (p < 0.01), and the number of temples within a 750 m buffer (p = 0.06) were selected as important predictors during the stepwise selection procedures. According to the partial R(2), NDVI explained 66% of PM2.5 variation and was the dominant variable in the developed model. We suggest future studies consider

  1. [The arctic sea ice refractive index retrieval based on satellite AMSR-E observations].

    Science.gov (United States)

    Chen, Han-Yue; Bi, Hai-Bo; Niu, Zheng

    2012-11-01

    The refractive index of sea ice in the polar region is an important geophysical parameter. It is needed as a vital input for some numerical climate models and is helpful to classifying sea ice types. In the present study, according to Hong Approximation (HA), we retrieved the arctic sea ice refractive index at 6.9, 10.7, 23, 37, and 89 GHz in different arctic climatological conditions. The refractive indices of wintertime first year (FY) sea ice and summertime ice were derived with average values of 1.78 - 1.75 and 1.724 - 1.70 at different frequencies respectively, which are consistent with previous studies. However, for multiyear (MY) ice, the results indicated relatively large bias between modeled results since 10.7 GHz. At a higher frequency, there is larger MY ice refractive index difference. This bias is mainly attributed to the volume scattering effect on MY microwave radiation due to emergence of massive small empty cavities after the brine water in MY ice is discharged into sea. In addition, the retrieved sea ice refractive indices can be utilized to classify ice types (for example, the winter derivation at 89 GHz), to identify coastal polynyas (winter retrieval at 6.9 GHz), and to outline the areal extent of significantly melting marginal sea ice zone (MIZ) (summer result at 6.9 GHz). The investigation of this study suggests an effective tool of passive microwave remote sensing in monitoring sea ice refractive index variability.

  2. Changes in satellite-derived spring vegetation green-up date and its linkage to climate in China from 1982 to 2010: a multimethod analysis.

    Science.gov (United States)

    Cong, Nan; Wang, Tao; Nan, Huijuan; Ma, Yuecun; Wang, Xuhui; Myneni, Ranga B; Piao, Shilong

    2013-03-01

    The change in spring phenology is recognized to exert a major influence on carbon balance dynamics in temperate ecosystems. Over the past several decades, several studies focused on shifts in spring phenology; however, large uncertainties still exist, and one understudied source could be the method implemented in retrieving satellite-derived spring phenology. To account for this potential uncertainty, we conducted a multimethod investigation to quantify changes in vegetation green-up date from 1982 to 2010 over temperate China, and to characterize climatic controls on spring phenology. Over temperate China, the five methods estimated that the vegetation green-up onset date advanced, on average, at a rate of 1.3 ± 0.6 days per decade (ranging from 0.4 to 1.9 days per decade) over the last 29 years. Moreover, the sign of the trends in vegetation green-up date derived from the five methods were broadly consistent spatially and for different vegetation types, but with large differences in the magnitude of the trend. The large intermethod variance was notably observed in arid and semiarid vegetation types. Our results also showed that change in vegetation green-up date is more closely correlated with temperature than with precipitation. However, the temperature sensitivity of spring vegetation green-up date became higher as precipitation increased, implying that precipitation is an important regulator of the response of vegetation spring phenology to change in temperature. This intricate linkage between spring phenology and precipitation must be taken into account in current phenological models which are mostly driven by temperature. © 2012 Blackwell Publishing Ltd.

  3. Identification of Forest Vegetation Using Vegetation Indices

    Institute of Scientific and Technical Information of China (English)

    Yuan Jinguo; Wang Wei

    2004-01-01

    Spectral feature of forest vegetation with remote sensing techniques is the research topic all over the world, because forest plays an important role in human beings' living environment. Research on vegetation classification with vegetation index is still very little recently. This paper proposes a method of identifying forest types based on vegetation indices,because the contrast of absorbing red waveband with reflecting near-infrared waveband strongly for different vegetation types is recognized as the theoretic basis of vegetation analysis with remote sensing. Vegetation index is highly related to leaf area index, absorbed photosynthetically active radiation and vegetation cover. Vegetation index reflects photosynthesis intensity of plants and manifests different forest types. According to reflectance data of forest canopy and soil line equation NIR=1.506R+0.0076 in Jingyuetan, Changchun of China, many vegetation indices are calculated and analyzed. The result shows that the relationships between vegetation indices and forest types are that perpendicular vegetation index (PVI) identifies broadleaf forest and coniferous forest the most easily;the next is transformed soil-adjusted vegetation index(TSVI) and modified soil-adjusted vegetation index(MSVI), but their calculation is complex. Ratio vegetation index (RVT) values of different coniferous forest vary obviously, so RVI can classify conifers.Therefore, the combination of PVI and RVI is evaluated to classify different vegetation types.

  4. Effectiveness of Vegetation Index Transformation for Land Use Identifying and Mapping in the Area of Oil palm Plantation based on SPOT-6 Imagery (Case Study: PT.Tunggal Perkasa Plantations, Air Molek, Indragiri Hulu)

    Science.gov (United States)

    Setyowati, H. A.; S, S. H. Murti B.; Sukentyas, E. S.

    2016-11-01

    The reflection of land surface, atmosphere and vegetation conditions affect the reflectance value of the object is recorded on remote sensing image so that it can affect the outcome of information extraction from remote sensing imagery one multispectral classification. This study aims to assess the ability of the transformation of generic vegetation index (Wide Dynamic Range Vegetation Index), the vegetation index transformation that is capable reducing the influence of the atmosphere (Atmospherically Resistant Vegetation Index), and the transformation of vegetation index that is capable of reducing the influence of the background soil (Second Modified Soil Adjusted Vegetation Index) for the identification and mapping of land use in the oil palm plantation area based on SPOT-6 archived on June 13, 2013 from LAPAN. The study area selected oil palm plantations PT. Tunggal Perkasa Plantations, Air Molek, Indragiri Hulu, Riau Province. The method is using the transformation of the vegetation index ARVI, MSAVI2, and WDRVI. Sample selection method used was stratified random sampling. The test method used mapping accuracy of the confusion matrix. The results showed that the best transformation of the vegetation index for the identification and mapping of land use in the plantation area is ARVI transformation with a total of accuracy is 96%. Accuracy of mapping land use settlements 100%, replanting 82.35%, 81.25% young oil palm, old oil palm 99.46%, 100% bush, body of water 100%, and 100% bare-soil.

  5. Correlation between normalized difference vegetation index and malaria in a subtropical rain forest undergoing rapid anthropogenic alteration.

    Science.gov (United States)

    Wayant, Nicole M; Maldonado, Diego; Rojas de Arias, Antonieta; Cousiño, Blanca; Goodin, Douglas G

    2010-05-01

    Time-series of coarse-resolution greenness values derived through remote sensing have been used as a surrogate environmental variable to help monitor and predict occurrences of a number of vector-borne and zoonotic diseases, including malaria. Often, relationships between a remotely-sensed index of greenness, e.g. the normalized difference vegetation index (NDVI), and disease occurrence are established using temporal correlation analysis. However, the strength of these correlations can vary depending on type and change of land cover during the period of record as well as inter-annual variations in the climate drivers (precipitation, temperature) that control the NDVI values. In this paper, the correlation between a long (260 months) time-series of monthly disease case rates and NDVI values derived from the Global Inventory Modeling and Mapping Studies (GIMMS) data set were analysed for two departments (administrative units) located in the Atlantic Forest biome of eastern Paraguay. Each of these departments has undergone extensive deforestation during the period of record and our analysis considers the effect on correlation of active versus quiescent periods of case occurrence against a background of changing land cover. Our results show that timeseries data, smoothed using the Fourier Transform tool, showed the best correlation. A moving window analysis suggests that four years is the optimum time frame for correlating these values, and the strength of correlation depends on whether it is an active or a quiescent period. Finally, a spatial analysis of our data shows that areas where land cover has changed, particularly from forest to non-forest, are well correlated with malaria case rates.

  6. Performance of the Enhanced Vegetation Index to Detect Inner-annual Dry Season and Drought Impacts on Amazon Forest Canopies

    Science.gov (United States)

    Brede, B.; Verbesselt, J.; Dutrieux, L.; Herold, M.

    2015-04-01

    The Amazon rainforests represent the largest connected forested area in the tropics and play an integral role in the global carbon cycle. In the last years the discussion about their phenology and response to drought has intensified. A recent study argued that seasonality in greenness expressed as Enhanced Vegetation Index (EVI) is an artifact of variations in sun-sensor geometry throughout the year. We aimed to reproduce these results with the Moderate-Resolution Imaging Spectroradiometer (MODIS) MCD43 product suite, which allows modeling the Bidirectional Reflectance Distribution Function (BRDF) and keeping sun-sensor geometry constant. The derived BRDF-adjusted EVI was spatially aggregated over large areas of central Amazon forests. The resulting time series of EVI spanning the 2000-2013 period contained distinct seasonal patterns with peak values at the onset of the dry season, but also followed the same pattern of sun geometry expressed as Solar Zenith Angle (SZA). Additionally, we assessed EVI's sensitivity to precipitation anomalies. For that we compared BRDF-adjusted EVI dry season anomalies to two drought indices (Maximum Cumulative Water Deficit, Standardized Precipitation Index). This analysis covered the whole of Amazonia and data from the years 2000 to 2013. The results showed no meaningful connection between EVI anomalies and drought. This is in contrast to other studies that investigate the drought impact on EVI and forest photosynthetic capacity. The results from both sub-analyses question the predictive power of EVI for large scale assessments of forest ecosystem functioning in Amazonia. Based on the presented results, we recommend a careful evaluation of the EVI for applications in tropical forests, including rigorous validation supported by ground plots.

  7. Influence of the Vegetation Type on CH2O and NO2 Tropospheric Emissions during Biomass Burning: Synergistic use of Satellite Observations

    Science.gov (United States)

    Marbach, T.; Beirle, S.; Hollwedel, J.; Khokhar, F.; Platt, U.; Wagner, T.

    Satellite observations are a helpful tool for the identification of the sources for tropospheric emissions by providing global observations of the different trace gases. We present case studies for the combined observations of CH2O and NO2 derived from observations made by the Global Ozone Monitoring Experiment (GOME). Launched on the ERS-2 satellite in April, 1995, GOME has already performed continuous operations over 8 years. The satellite CH2O observations provide information concerning the localization of biomass burning (intense source of CH2O). The principal biomass burning areas can be observed in the amazonian forest and in central Africa. Other high CH2O emissions can be correlated with climatic events like El Nino in 1997, which induced dry conditions in Indonesia causing many forest fires. Tree isoprene emissions contribute also for high CH2O concentrations especially in southwest United States. Biomass burning are also an important tropospheric source for NO2 emissions and can be compared with the CH2O emissions to discriminate the influence of the vegetation type on the tropospheric emissions of both trace gases during biomass burning: the change in the vegetation type can be followed with the change in the intensity of CH2O and NO2 emissions.

  8. Evaluating interannual vegetation anomalies in the Basilicata region using satellite spot vegetation 1999-2011 time series: preliminary results from the Mitra project

    Science.gov (United States)

    Lasaponara, Rosa; Desantis, Fortunato; Aromando, Angelo; Lanorte, Antonio

    2013-04-01

    The Basilicata region funded a fesr project, MITRA to develop reliable low cost technologies to preserve and enhance natural and cultural heritage in some relevant areas selected as test cases. " Cultural heritage and the natural heritage are increasingly threatened with destruction not only by the traditional causes of decay, but also by changing social and economic conditions which aggravate the situation with even more formidable phenomena of damage or destruction, from THE GENERAL CONFERENCE of the United Nations Educational, Scientific and Cultural Organization meeting in Paris from 17 October to 21 November 1972, at its seventeenth session, available on line " (http://whc.unesco.org/en/conventiontext/). This paper is focused on the preliminary results obtained in the framework of the Mitra project. In particular, a temporal series (1999-2011) of the yearly Maximum Value Composit of SPOT/VEGETATION NDVI was used to carried out investigation on the whole Basilicata region. The PCA was used as a first step of data transform to enhance regions of localized change in multi-temporal data sets (Lasaponara 2006). Results from PCA were further processed using Support Vector machine (SVM) to identify and map land degradation phenomenon Both naturally vegetated areas (forest, shrub-land, herbaceous cover) and agricultural lands have been investigated in order to extract the most prominent natural and/or man induced alterations affecting vegetation behavior. Such analyses can provide valuable information for monitoring the status of vegetation which is an indicator of the degree of stress namely any disturbance that adversely influences plants in response to natural hazards and/or anthropogenic activities. Our findings suggest that the jointly use of PCA and SVM PCA can provide valuable information for environmental management policies involving biodiversity preservation and rational exploitation of natural and agricultural resources. Rosa Lasaponara 2006, On the use of

  9. Forest vegetation dynamics and its response to climate changes

    Science.gov (United States)

    Zoran, Maria A.; Zoran, Liviu Florin V.; Dida, Adrian I.

    2016-10-01

    Forest areas are experiencing rapid land cover change caused by human-induced land degradation and extreme climatic events. Satellite remote sensing provides a useful tool to capture the temporal dynamics of forest vegetation change in response to climate shifts, at spatial resolutions fine enough to capture the spatial heterogeneity. Frequent satellite data products, for example, can provide the basis for studying time-series of biophysical parameters related to vegetation dynamics. Vegetation index time series provide a useful way to monitor forest vegetation phenological variations. In this study, we used MODIS Terra/Aqua time-series data, along with yearly and monthly net radiation, air temperature, and precipitation data to examine the feedback mechanisms between climate and forest vegetation. Have been quantitatively described Normalized Difference Vegetation Index(NDVI) /Enhanced Vegetation Index (EVI), Leaf Area Index (LAI), Evapotranspiration (ET) and Gross Primary Production (GPP) temporal changes for Cernica- Branesti forest area, a periurban zone of Bucharest city in Romania, from the perspective of vegetation phenology and its relation with climate changes and extreme climate events (summer heat waves). A time series from 2000 to 2016 of the MODIS Terra was analyzed to extract forest biophysical parameters anomalies. Forest vegetation phenology analyses were developed for diverse forest land-covers providing a useful way to analyze and understand the phenology associated to those landcovers. Correlations between NDVI/EVI , LAI, ET and GPP time series and climatic variables have been computed.

  10. Assessing agricultural drought in summer over Oklahoma Mesonet sites using the water-related vegetation index from MODIS

    Science.gov (United States)

    Bajgain, Rajen; Xiao, Xiangming; Basara, Jeffrey; Wagle, Pradeep; Zhou, Yuting; Zhang, Yao; Mahan, Hayden

    2017-02-01

    Agricultural drought, a common phenomenon in most parts of the world, is one of the most challenging natural hazards to monitor effectively. Land surface water index (LSWI), calculated as a normalized ratio between near infrared (NIR) and short-wave infrared (SWIR), is sensitive to vegetation and soil water content. This study examined the potential of a LSWI-based, drought-monitoring algorithm to assess summer drought over 113 Oklahoma Mesonet stations comprising various land cover and soil types in Oklahoma. Drought duration in a year was determined by the number of days with LSWI 80 % (eastern Oklahoma) across regions. Our results illustrated that drought intensity thresholds can be established by counting DNLSWI (in days) and used as a simple complementary tool in several drought applications for semi-arid and semi-humid regions of Oklahoma. However, larger discrepancies between USDM and the LSWI-based algorithm in arid regions of western Oklahoma suggest the requirement of further adjustment in the algorithm for its application in arid regions.

  11. [Vegetable oil-induced acute respiratory distress syndrome (ARDS) in near drowning: evaluation based on extravascular lung water index].

    Science.gov (United States)

    Yoshida, Takeshi; Rinka, Hiroshi; Kaji, Arito

    2008-06-01

    Lipoid pneumonia usually presents after chronic recurrent ingestion of oily substances or accidental aspiration during "fire-eating" demonstrations. Massive exposure by near drowning extremely rare and potentially fatal. We present here a case of survival after total immersion in oil in her workplace. A 66-year-old woman who nearly drowned in a vat of vegetable oil was admitted as an emergency case with severe hypoxia after rescue. Chest computed tomography (CT) findings showed bilateral ground-glass opacity, consolidation, and the case fulfilled the criteria for acute respiratory distress syndrome (ARDS). Bronchoscopy and bronchoalveolar lavage performed on admission indicated oil droplets and marked neutrophilia (67%), which made us diagnose ARDS induced by lipoid pneumonia. We commenced treatment with pulsed steroids and strictly managed fluid balance under mechanical ventilation. Despite immediate improvement in oxygenation, the value of extravascular lung water index (EVLWI) measured by the PiCCO system consistently remained over 30 ml/Kg through her clinical course. We concluded that lipoid pneumonia is characterized by prolonged elevatation of pulmonary vascular permeability.

  12. Unmanned aircraft system-derived crop height and normalized difference vegetation index metrics for sorghum yield and aphid stress assessment

    Science.gov (United States)

    Stanton, Carly; Starek, Michael J.; Elliott, Norman; Brewer, Michael; Maeda, Murilo M.; Chu, Tianxing

    2017-04-01

    A small, fixed-wing unmanned aircraft system (UAS) was used to survey a replicated small plot field experiment designed to estimate sorghum damage caused by an invasive aphid. Plant stress varied among 40 plots through manipulation of aphid densities. Equipped with a consumer-grade near-infrared camera, the UAS was flown on a recurring basis over the growing season. The raw imagery was processed using structure-from-motion to generate normalized difference vegetation index (NDVI) maps of the fields and three-dimensional point clouds. NDVI and plant height metrics were averaged on a per plot basis and evaluated for their ability to identify aphid-induced plant stress. Experimental soil signal filtering was performed on both metrics, and a method filtering low near-infrared values before NDVI calculation was found to be the most effective. UAS NDVI was compared with NDVI from sensors onboard a manned aircraft and a tractor. The correlation results showed dependence on the growth stage. Plot averages of NDVI and canopy height values were compared with per-plot yield at 14% moisture and aphid density. The UAS measures of plant height and NDVI were correlated to plot averages of yield and insect density. Negative correlations between aphid density and NDVI were seen near the end of the season in the most damaged crops.

  13. Indexed

    CERN Document Server

    Hagy, Jessica

    2008-01-01

    Jessica Hagy is a different kind of thinker. She has an astonishing talent for visualizing relationships, capturing in pictures what is difficult for most of us to express in words. At indexed.blogspot.com, she posts charts, graphs, and Venn diagrams drawn on index cards that reveal in a simple and intuitive way the large and small truths of modern life. Praised throughout the blogosphere as “brilliant,” “incredibly creative,” and “comic genius,” Jessica turns her incisive, deadpan sense of humor on everything from office politics to relationships to religion. With new material along with some of Jessica’s greatest hits, this utterly unique book will thrill readers who demand humor that makes them both laugh and think.

  14. Exploring the Opportunities of a Balloon-Satellite in Bangladesh for Weather Data Collection and Vegetative Analysis

    Science.gov (United States)

    Shafique, Md. Ishraque Bin; Razzaq Halim, M. A.; Rabbi, Fazle; Khalilur Rhaman, Md.

    2016-07-01

    For a third world country like Bangladesh, satellite and space research is not feasible due to lack of funding. Therefore, in order to imitate the principles of such a satellite Balloon Satellite can easily and inexpensively be setup. Balloon satellites are miniature satellites, which are cheap and easy to construct. This paper discusses a BalloonSat developed using a Raspberry Pi, IMU module, UV sensor, GPS module, Camera and XBee Module. An interactive GUI was designed to display all the data collected after processing. To understand nitrogen concentration of a plant, a leaf color chart is used. This paper attempts to digitalize this process, which is applied on photos taken by the BallonSat.

  15. Inferring Amazon leaf demography from satellite observations of leaf area index

    Directory of Open Access Journals (Sweden)

    S. Caldararu

    2011-10-01

    Full Text Available Seasonal and year-to-year variations in leaf cover imprint significant spatial and temporal variability on biogeochemical cycles, and affect land-surface properties related to climate. We develop a demographic model of leaf phenology based on the hypothesis that trees seek an optimal Leaf Area Index (LAI as a function of available light and soil water, and fitted it to spaceborne observations of LAI over the Amazon Basin, 2001–2005. We find the model reproduces the spatial and temporal LAI distribution whilst also predicting geographic variation in leaf age from the basin center (2.1 ± 0.2 yr, through to the lowest values over the deciduous Eastern Amazon (6 ± 2 months. The model explains the observed increase in LAI during the dry season as a net addition of leaves in response to increased solar radiation. We anticipate our work to be a starting point from which to develop better descriptions of leaf phenology to incorporate into more sophisticated earth system models.

  16. Inferring Amazon leaf demography from satellite observations of leaf area index

    Directory of Open Access Journals (Sweden)

    S. Caldararu

    2012-04-01

    Full Text Available Seasonal and year-to-year variations in leaf cover imprint significant spatial and temporal variability on biogeochemical cycles, and affect land-surface properties related to climate. We develop a demographic model of leaf phenology based on the hypothesis that trees seek an optimal leaf area index (LAI as a function of available light and soil water, and fit it to spaceborne observations of LAI over the Amazon basin, 2001–2005. We find the model reproduces the spatial and temporal LAI distribution whilst also predicting geographic variation in leaf age from the basin centre (2.1 ± 0.2 years, through to the lowest values over the deciduous eastern and southern Amazon (6 ± 2 months. The model explains the observed increase in LAI during the dry season as a net addition of leaves in response to increased solar radiation. We anticipate our work to be a starting point from which to develop better descriptions of leaf phenology to incorporate into more sophisticated earth system models.

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

    Science.gov (United States)

    Chen, X.; Vogelmann, J.E.; Rollins, M.; Ohlen, D.; Key, C.H.; Yang, L.; Huang, C.; Shi, H.

    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. ?? 2011 Taylor & Francis.

  18. Initial Response of Normalized Difference Vegetation Index, Green Normalized Difference Vegetation Index and Soil Adjusted Vegetation Index to Infrared Warming in Highland Barley of the Tibet%西藏高原青稞三种植被指数对红外增温的初始响应

    Institute of Scientific and Technical Information of China (English)

    付刚; 沈振西; 钟志明

    2015-01-01

    Climatic warming affects the crop growth and its related vegetation indices. In order to understand the initial response of normalized difference vegetation index (NDVI), normalized green difference vegetation index (GNDVI) and soil adjusted vegetation index (SAVI) to climatic warming, a field warming experiment using infrared radiator was conducted in a highland barley located at the Dazi county of the Tibet since late May, 2015. There were three warming treatments, i.e., control, low (1000 W) and high (2000W) warming. The NDVI, GNDVI and SAVI were obtained using an agricultural digital camera during the period from June to September in 2015. Meanwhile, the soil temperature and soil moisture at depths of 5 cm and 20 cm were also obtained using HOBO microclimate observing systems. Then this study analyzed the response of NDVI, GNDVI and SAVI to infrared warming and the relationships between the three vegetation indices and soil temperature and moisture. The 1000 W and 2000 W infrared warming increased soil temperature at the depth of 5 cm (t5) by 1.62℃ and 1.77℃, and soil temperature at the depth of 20 cm (t20) by 1.16℃and 1.43℃, but decreased soil moisture at the depth of 5 cm (SM5) by 1.8% and 14.1%, and soil moisture at the depth of 20 cm (SM20) by 21.6% and 14.7%, respectively. The 1000 W infrared warming increased NDVI by 2.4%, GNDVI by 4.3% and SAVI by 0.5%, whereas the 2000 W infrared warming increased NDVI by 5.5%, GNDVI by 5.3% and SAVI by 4.8%, although these changes were non-significant. Simple regression analyses showed that (1) NDVI (r2=0.110,P=0.026) and GNDVI(r2=0.254, P=0.0004)decreased with increasingt5,whereas there was non-significant correlation between SAVI andt5 (r2=0.069,P=0.082); (2) GNDVI decreased with increasingt20, (r2=0.218,P=0.001), whereas there were non-significant relationships between NDVI (r2=0.040,P=0.190), SAVI (r2=0.014,P=0.443) andt20; (3) NDVI (r2=0.277,P=0.0002), GNDVI (r2=0.394,P=0.0000) and SAVI (r2=0.208,P=0

  19. Estimation of Carbon Stock Stands using EVI and NDVI Vegetation Index in Production Forest of Lembah Seulawah Sub-District, Aceh Indonesia

    Directory of Open Access Journals (Sweden)

    Jhon Pandapotan Situmorang

    2016-12-01

    Full Text Available This study aims to determine the distribution of the vegetation indexes to estimate the carbon stocks of forest stands in the Production Forest of Lembah Seulawah sub-district. Aceh Province, Indonesia. A non-destructive method using allometric equations and landscape scale method were applied, where in carbon stocks at the points of samples are correlated with the index values of each transformation of the vegetation indexes; EVI and NDVI.  Results show that EVI values of study area from 0.05 to 0.90 and NDVI values from 0.17 to 0.85. The regression analysis between EVI with carbon stock value of sample locations equation is Y = 151.7X-39.76. with the coefficient of determination (R2 is 0.83. From this calculation, the total carbon stocks in the Production Forest area of Lembah Seulawah sub-district using EVI is estimated 790.344.41 tonnes, and the average value of carbon stocks in average is 51.48 tons per hectare.  Regression analysis between NDVI values at the research locations for the carbon stack measured samples is Y = 204.Xx-102.1 with coefficient of determination (R2 is 0.728. Total carbon stocks in production forest of Lembah Seulawah sub-district using NDVI is estimated 711.061.81 tones. and the average value of carbon stocks is 46.32 tons per hectare. From the above results it can be concluded that the vegetation indexes: EVI and NDVI are vegetation indexed that have a very close correlation with carbon stocks stands estimation. The correlation between EVI with carbon stock and the correlation between NDVI with carbon stock is not significantly different

  20. Stay-green in spring wheat can be determined by spectral reflectance measurements (normalized difference vegetation index) independently from phenology.

    Science.gov (United States)

    Lopes, Marta S; Reynolds, Matthew P

    2012-06-01

    The green area displayed by a crop is a good indicator of its photosynthetic capacity, while chlorophyll retention or 'stay-green' is regarded as a key indicator of stress adaptation. Remote-sensing methods were tested to estimate these parameters in diverse wheat genotypes under different growing conditions. Two wheat populations (a diverse set of 294 advanced lines and a recombinant inbred line population of 169 sister lines derived from the cross between Seri and Babax) were grown in Mexico under three environments: drought, heat, and heat combined with drought. In the two populations studied here, a moderate heritable expression of stay-green was found-when the normalized difference vegetation index (NDVI) at physiological maturity was estimated using the regression of NDVI over time from the mid-stages of grain-filling to physiological maturity-and for the rate of senescence during the same period. Under heat and heat combined with drought environments, stay-green calculated as NDVI at physiological maturity and the rate of senescence, showed positive and negative correlations with yield, respectively. Moreover, stay-green calculated as an estimation of NDVI at physiological maturity and the rate of senescence regressed on degree days give an independent measurement of stay-green without the confounding effect of phenology. On average, in both populations under heat and heat combined with drought environments CTgf and stay-green variables accounted for around 30% of yield variability in multiple regression analysis. It is concluded that stay-green traits may provide cumulative effects, together with other traits, to improve adaptation under stress further.

  1. Assessing agricultural drought in summer over Oklahoma Mesonet sites using the water-related vegetation index from MODIS

    Science.gov (United States)

    Bajgain, Rajen; Xiao, Xiangming; Basara, Jeffrey; Wagle, Pradeep; Zhou, Yuting; Zhang, Yao; Mahan, Hayden

    2016-08-01

    Agricultural drought, a common phenomenon in most parts of the world, is one of the most challenging natural hazards to monitor effectively. Land surface water index (LSWI), calculated as a normalized ratio between near infrared (NIR) and short-wave infrared (SWIR), is sensitive to vegetation and soil water content. This study examined the potential of a LSWI-based, drought-monitoring algorithm to assess summer drought over 113 Oklahoma Mesonet stations comprising various land cover and soil types in Oklahoma. Drought duration in a year was determined by the number of days with LSWI drought years (2001, 2006, 2011, and 2012). The DNLSWI tracked the east-west gradient of summer rainfall in Oklahoma. Drought intensity increased with increasing duration of DNLSWI, and the intensity increased rapidly when DNLSWI was more than 48 days. The comparison between LSWI and the US Drought Monitor (USDM) showed a strong linear negative relationship; i.e., higher drought intensity tends to have lower LSWI values and vice versa. However, the agreement between LSWI-based algorithm and USDM indicators varied substantially from 32 % (D 2 class, moderate drought) to 77 % (0 and D 0 class, no drought) for different drought intensity classes and varied from ˜30 % (western Oklahoma) to >80 % (eastern Oklahoma) across regions. Our results illustrated that drought intensity thresholds can be established by counting DNLSWI (in days) and used as a simple complementary tool in several drought applications for semi-arid and semi-humid regions of Oklahoma. However, larger discrepancies between USDM and the LSWI-based algorithm in arid regions of western Oklahoma suggest the requirement of further adjustment in the algorithm for its application in arid regions.

  2. Evaluation of habitat suitability index models by global sensitivity and uncertainty analyses: a case study for submerged aquatic vegetation.

    Science.gov (United States)

    Zajac, Zuzanna; Stith, Bradley; Bowling, Andrea C; Langtimm, Catherine A; Swain, Eric D

    2015-07-01

    Habitat suitability index (HSI) models are commonly used to predict habitat quality and species distributions and are used to develop biological surveys, assess reserve and management priorities, and anticipate possible change under different management or climate change scenarios. Important management decisions may be based on model results, often without a clear understanding of the level of uncertainty associated with model outputs. We present an integrated methodology to assess the propagation of uncertainty from both inputs and structure of the HSI models on model outputs (uncertainty analysis: UA) and relative importance of uncertain model inputs and their interactions on the model output uncertainty (global sensitivity analysis: GSA). We illustrate the GSA/UA framework using simulated hydrology input data from a hydrodynamic model representing sea level changes and HSI models for two species of submerged aquatic vegetation (SAV) in southwest Everglades National Park: Vallisneria americana (tape grass) and Halodule wrightii (shoal grass). We found considerable spatial variation in uncertainty for both species, but distributions of HSI scores still allowed discrimination of sites with good versus poor conditions. Ranking of input parameter sensitivities also varied spatially for both species, with high habitat quality sites showing higher sensitivity to different parameters than low-quality sites. HSI models may be especially useful when species distribution data are unavailable, providing means of exploiting widely available environmental datasets to model past, current, and future habitat conditions. The GSA/UA approach provides a general method for better understanding HSI model dynamics, the spatial and temporal variation in uncertainties, and the parameters that contribute most to model uncertainty. Including an uncertainty and sensitivity analysis in modeling efforts as part of the decision-making framework will result in better-informed, more robust

  3. Normalized Difference Vegetation Index as a Tool for Wheat Yield Estimation: A Case Study from Faisalabad, Pakistan

    Directory of Open Access Journals (Sweden)

    Syeda Refat Sultana

    2014-01-01

    Full Text Available For estimation of grain yield in wheat, Normalized Difference Vegetation Index (NDVI is considered as a potential screening tool. Field experiments were conducted to scrutinize the response of NDVI to yield behavior of different wheat cultivars and nitrogen fertilization at agronomic research area, University of Agriculture Faisalabad (UAF during the two years 2008-09 and 2009-10. For recording the value of NDVI, Green seeker (Handheld-505 was used. Split plot design was used as experimental model in, keeping four nitrogen rates (N1= 0 kg ha−1, N2= 55 kg ha−1, N3=110 kg ha−1, and N4= 220 kg ha−1 in main plots and ten wheat cultivars (Bakkhar-2001, Chakwal-50, Chakwal-97, Faisalabad-2008, GA-2002, Inqlab-91, Lasani-2008, Miraj-2008, Sahar-2006, and Shafaq-2006 in subplots with four replications. Impact of nitrogen and difference between cultivars were forecasted through NDVI. The results suggested that nitrogen treatment N4 (220 kg ha−1 and cultivar Faisalabad-2008 gave maximum NDVI value (0.85 at grain filling stage among all treatments. The correlation among NDVI at booting, grain filling, and maturity stages with grain yield was positive (R2 = 0.90; R2 = 0.90; R2 = 0.95, respectively. So, booting, grain filling, and maturity can be good depictive stages during mid and later growth stages of wheat crop under agroclimatic conditions of Faisalabad and under similar other wheat growing environments in the country.

  4. Evaluation of habitat suitability index models by global sensitivity and uncertainty analyses: a case study for submerged aquatic vegetation

    Science.gov (United States)

    Zajac, Zuzanna; Stith, Bradley M.; Bowling, Andrea C.; Langtimm, Catherine A.; Swain, Eric D.

    2015-01-01

    Habitat suitability index (HSI) models are commonly used to predict habitat quality and species distributions and are used to develop biological surveys, assess reserve and management priorities, and anticipate possible change under different management or climate change scenarios. Important management decisions may be based on model results, often without a clear understanding of the level of uncertainty associated with model outputs. We present an integrated methodology to assess the propagation of uncertainty from both inputs and structure of the HSI models on model outputs (uncertainty analysis: UA) and relative importance of uncertain model inputs and their interactions on the model output uncertainty (global sensitivity analysis: GSA). We illustrate the GSA/UA framework using simulated hydrology input data from a hydrodynamic model representing sea level changes and HSI models for two species of submerged aquatic vegetation (SAV) in southwest Everglades National Park: Vallisneria americana (tape grass) and Halodule wrightii (shoal grass). We found considerable spatial variation in uncertainty for both species, but distributions of HSI scores still allowed discrimination of sites with good versus poor conditions. Ranking of input parameter sensitivities also varied spatially for both species, with high habitat quality sites showing higher sensitivity to different parameters than low-quality sites. HSI models may be especially useful when species distribution data are unavailable, providing means of exploiting widely available environmental datasets to model past, current, and future habitat conditions. The GSA/UA approach provides a general method for better understanding HSI model dynamics, the spatial and temporal variation in uncertainties, and the parameters that contribute most to model uncertainty. Including an uncertainty and sensitivity analysis in modeling efforts as part of the decision-making framework will result in better-informed, more robust

  5. ANALISA KESEHATAN TANAMAN PADI BERDASARKAN NILAI NORMALIZED DIFFERENCE VEGETATION INDEX (NDVI MENGGUNAKAN CITRA ASTER (STUDI KASUS : KABUPATEN INDRAMAYU - JAWA BARAT

    Directory of Open Access Journals (Sweden)

    Prasetyo Rahaldi

    2015-02-01

    Full Text Available Padi merupakan salah satu tanaman budidaya yang terpenting karena merupakan makanan pokok bagi 90% penduduk Indonesia. Oleh sebab itu dibutuhkan analisa yang cepat dan akurat mengenai kesehatan tanaman padi. Dalam Penelitian ini NDVI atau Normalized Difference Vegetation Index merupakan metode yang digunakan dalam membandingkan tingkat kehijauan vegetasi yang berasal dari citra ASTER. Dari nilai NDVI tersebut dapat diketahui klasifikasi kesehatan tanaman padi. Dalam penelitian ini klasifikasi kesehatan tanaman padi dibagi menjadi  4 kelas. Kesehatan sangat baik terdapat pada rentang nilai NDVI 0.721-0.92, untuk kesehatan baik rentang nilai NDVI antara 0.421-0.72, dan nilai NDVI kesehatan normal terdapat pada rentang 0.221-0.42, sedangkan kesehatan buruk nilai NDVI 0.11-0.22. Selain itu juga menggunakan data Field Spectrometer sebanyak 14 titik sebagai data lapangan yang digunakan untuk proses validasi. Validasi ini mempunyai koefisien korelasi (R sebesar 0.829. Sehingga dapat dikatakan antara nilai hasil prediksi dan hasil pengukuran lapangan berkolerasi sebesar 82,9 %. Dengan data citra ASTER juga dihasilkan pustaka spektral dan peta kesehatan tanaman padi, dalam pustaka spektral semakin sehat tanaman nilai Digital Number pada band 2 semakin kecil. Sedangkan band 3 banyak dipantulkan atau tidak digunakan sehingga nilai Digital Number pada tanaman padi yang semakin sehat, nilainya semakin tinggi. Sedangkan dalam peta kesehatan tanaman padi klasifikasi kesehatan buruk luas areanya 3.949.560 Ha. Pada klasifikasi kesehatan normal luas areanya 14.877.315 Ha. Sedangkan pada klasifikasi kesehatan baik luas areanya 9.846.833 Ha dan pada klasifikasi kesehatan sangat baik luas areanya 8.922.892.

  6. Satellite-Based Observations of Inter-annual Variation of Vegetation Water Content and Productivity in Northern Asia During 1998-2001

    Science.gov (United States)

    Xiao, X.; Braswell, B. H.; Zhang, Q.; Boles, S.; Frolking, S.; Moore, B.

    2002-05-01

    The terrestrial biosphere was largely carbon neutral during the 1980s, but became a much stronger net carbon sink in the 1990s. It is also thought that the unusually large carbon sink in the early 1990s can be largely attributed to climate variability. We analyzed multi-temporal images (1-km spatial resolution, 10-day composites) from the SPOT-4 VEGETATION (VGT) sensor over the period of April 1, 1998 to September 30, 2001 to characterize spatial and temporal variations of vegetation and water indices for Northern Asia (40oN - 75oN, and 45oE - 179oE). Three remote sensing proxies were derived from the VGT data: Normalized Difference Water Index (NDWI), Normalized Difference Vegetation Index (NDVI), and Enhanced Vegetation Index (EVI). We calculated anomalies of NDWI, NDVI and EVI at different temporal scales, i.e., 10-day, monthly, seasonal and plant growing season (April to September), and compared these with inter-annual variations in precipitation and temperature from the National Climate Data Center Global History Climate Network. Both anomalies of precipitation and NDWI over plant growing season (April to September) for Northern Asia were highest in 1998 but declined from 1999 to 2001. NDVI and EVI anomalies did not correlate well with each other overall. The EVI anomaly over plant growing season (April to September) was highest in 1998, and declined from 1999 to 2001,while the NDVI anomaly over plant growing season was lowest in 1998 and highest in 2000 for North Asia. The EVI includes information from the VGT blue band to account for the effects of residual atmospheric contamination (e.g., aerosols) and soil/vegetation background, while the NDVI does not. Large fires occurred in eastern Russia and Northeastern China in 1998 and may have increased the atmospheric aerosol burden; high precipitation in that year may have been associated with increased atmospheric water vapor. Both of these effects would lower the NDVI value in 1998. This continental-scale study

  7. Vegetation Height Estimation Near Power transmission poles Via satellite Stereo Images using 3D Depth Estimation Algorithms

    OpenAIRE

    Qayyum, A; A. S. Malik; Saad, M. N. M.; Iqbal, M.; F. Abdullah; W. Rahseed; T. A. R. B. T. Abdullah; A. Q. Ramli

    2015-01-01

    Monitoring vegetation encroachment under overhead high voltage power line is a challenging problem for electricity distribution companies. Absence of proper monitoring could result in damage to the power lines and consequently cause blackout. This will affect electric power supply to industries, businesses, and daily life. Therefore, to avoid the blackouts, it is mandatory to monitor the vegetation/trees near power transmission lines. Unfortunately, the existing approaches are more t...

  8. Combining Satellite-Based Precipitation and Vegetation Indices to Achieve a Mid-Summer Agricultural Forecast in Jamaica

    Science.gov (United States)

    Curtis, S.; Allen, T. L.; Gamble, D.

    2009-12-01

    In this study global Earth observations of precipitation and Normalized Difference Vegetation Indices (NDVI) are used to assess the mid-summer dry spell’s (MSD) strength and subsequent impact on agriculture in the St. Elizabeth parish of Jamaica. St. Elizabeth is known as the ‘bread basket’ of Jamaica and has been the top or second highest producer of domestic food crops in the last twenty years. Yet, St. Elizabeth sits in the Jamaican rain shadow and is highly affected by drought. In addition, the summer rainy season is regularly interrupted by an MSD, which often occurs in July, has strong interannual variability, and greatly affects cropping strategies and yields. The steps undertaken to achieve a mid-summer agricultural forecast are: 1) use relationships between Global Precipitation Climatology Project v2.1 data over western Jamaica and predictive climate modes from 1979 to present to develop a forecast of July rainfall 2) downscale the rainfall variability in time to sub-monthly and space to the St. Elizabeth parish using the Tropical Rainfall Measuring Mission 3) link rainfall variability to vegetation vigor with the MODIS NDVI data 4) communicate with St. Elizabeth farmers via the University of West Indies, Mona. An important finding from this study is a decrease in vegetative vigor follows the MSD by two to four weeks in St. Elizabeth and the vegetation in the southern portion of the parish appears to be more sensitive to the MSD than vegetation elsewhere in the country.

  9. Sensitivity Analysis of Remote Sensing Data: Comparing the Response of Vegetation Indices in Tropical Areas.

    Science.gov (United States)

    Bonifaz, R.

    2005-12-01

    During the past two decades, satellite remote sensing systems possessing high temporal resolution, but typically moderate or coarse spatial resolution, have increasingly been used to characterize and map vegetation dynamics. Assessing the seasonality of tropical vegetation has, however, been especially challenging. Tropical regimes of temperature and precipitation are generally less variable and pronounced than those in other biomes, and variations in plant growth are often more subtle. Using samples from selected tropical land cover types (tropical rain forest, tropical grasses, tropical deciduous forest, mixed forest and agricultural areas), sensitivity analysis will be carried out comparing different 'greenness' indices such as the Normalized Difference Vegetation Index (NDVI), the Enhanced Vegetation Index (EVI) and the Wide Dynamic Range Vegetation Index (WDRVI) derived from the MODIS/TERRA sensor. This analysis will potentially allow the selection of the best index to describe the particular behavior of tropical vegetation for further characterization of seasonal changes of such areas.

  10. Analysis of Vegetation Behavior in a North African Semi-Arid Region, Using SPOT-VEGETATION NDVI Data

    Directory of Open Access Journals (Sweden)

    Abdelghani Chehbouni

    2011-11-01

    Full Text Available The analysis of vegetation dynamics is essential in semi-arid regions, in particular because of the frequent occurrence of long periods of drought. In this paper, multi-temporal series of the Normalized Difference of Vegetation Index (NDVI, derived from SPOT-VEGETATION satellite data between September 1998 and June 2010, were used to analyze the vegetation dynamics over the semi-arid central region of Tunisia. A study of the persistence of three types of vegetation (pastures, annual agriculture and olive trees is proposed using fractal analysis, in order to gain insight into the stability/instability of vegetation dynamics. In order to estimate the state of vegetation cover stress, we propose evaluating the properties of an index referred to as the Vegetation Anomaly Index (VAI. A positive VAI indicates high vegetation dynamics, whereas a negative VAI indicates the presence of vegetation stress. The VAI is tested for the above three types of vegetation, during the study period from 1998 to 2010, and is compared with other drought indices. The VAI is found to be strongly correlated with precipitation.

  11. Forest fire danger index based on modifying Nesterov Index, fuel, and anthropogenic activities using MODIS TERRA, AQUA and TRMM satellite datasets

    Science.gov (United States)

    Suresh Babu, K. V.; Roy, Arijit; Ramachandra Prasad, P.

    2016-05-01

    Forest fire has been regarded as one of the major causes of degradation of Himalayan forests in Uttarakhand. Forest fires occur annually in more than 50% of forests in Uttarakhand state, mostly due to anthropogenic activities and spreads due to moisture conditions and type of forest fuels. Empirical drought indices such as Keetch-Byram drought index, the Nesterov index, Modified Nesterov index, the Zhdanko index which belongs to the cumulative type and the Angstrom Index which belongs to the daily type have been used throughout the world to assess the potential fire danger. In this study, the forest fire danger index has been developed from slightly modified Nesterov index, fuel and anthropogenic activities. Datasets such as MODIS TERRA Land Surface Temperature and emissivity (MOD11A1), MODIS AQUA Atmospheric profile product (MYD07) have been used to determine the dew point temperature and land surface temperature. Precipitation coefficient has been computed from Tropical Rainfall measuring Mission (TRMM) product (3B42RT). Nesterov index has been slightly modified according to the Indian context and computed using land surface temperature, dew point temperature and precipitation coefficient. Fuel type danger index has been derived from forest type map of ISRO based on historical fire location information and disturbance danger index has been derived from disturbance map of ISRO. Finally, forest fire danger index has been developed from the above mentioned indices and MODIS Thermal anomaly product (MOD14) has been used for validating the forest fire danger index.

  12. Satellite derived phenology of southern Africa for 1985-2000 and functional classification of vegetation based on phenometrics

    CSIR Research Space (South Africa)

    Steenkamp, K

    2009-05-01

    Full Text Available analyzed vegetation phenometrics across South Africa (SA) in order to characterize phenological patterns and their inter-annual variability. A second objective is to distinguish biomes and sub-biome “bioregions” based on functional patterns. The long term...

  13. Temporal variation of normalized difference vegetation index (NDVI and calculation of the crop coefficient (Kc from NDVI in areas cultivated with irrigated soybean

    Directory of Open Access Journals (Sweden)

    Thálita Carrijo de Oliveira

    2016-09-01

    Full Text Available ABSTRACT: Vegetation indices obtained by remote sensing products have various applications in agriculture. An important application of the Normalized Difference Vegetation Index (NDVI is obtaining the crop coefficient (Kc. The aims of this study were to analyze NDVI temporal profiles and to obtain Kc from the NDVI vegetation index product MOD13Q1. The analysis is based on the phenological stages of irrigated soybean crops in the municipality of Planura/MG during the 2010/2011 growing season. Areas planted with irrigated soybean were identified through fieldwork. Temporal series of the MOD13Q1 products were used to analyze NDVI, allowing the extraction of NDVI values for all points in the period studied. The NDVI temporal profiles showed a similar pattern to each other and corresponded to the crop cycle. The KcNDVI values for the MOD13Q1 products were well correlated to the FAO Kc values (r2=0.72. Thus, NDVI can be used as an alternative for obtaining crop coefficient (Kc.

  14. 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.

  15. Human induced dryland degradation in Ordos Plateau, China, revealed by multilevel statistical modeling of normalized difference vegetation index and rainfall time-series

    Institute of Scientific and Technical Information of China (English)

    Jing ZHANG; JianMing NIU; Tongliga BAO; Alexander BUYANTUYEV; Qing ZHANG; JianJun DONG; XueFeng ZHANG

    2014-01-01

    Land degradation causes serious environmental problems in many regions of the world, and although it can be effectively assessed and monitored using a time series of rainfall and a normalized difference vegetation index (NDVI) from remotely-sensed imagery, dividing human-induced land degradation from vegetation dynamics due to climate change is not a trivial task. This paper presented a multilevel statistical modeling of the NDVI-rainfall relationship to detect human-induced land degradation at local and landscape scales in the Ordos Plateau of Inner Mongolia, China, and recognized that anthropogenic activities result in either positive (land restoration and re-vegetation) or negative (degradation) trends. Linear regressions were used to assess the accuracy of the multi-level statistical model. The results show that:(1) land restoration was the dominant process in the Ordos Plateau between 1998 and 2012;(2) the effect of the statistical removal of precipitation revealed areas of human-induced land degradation and improvement, the latter reflecting successful restoration projects and changes in land man-agement in many parts of the Ordos; (3) compared to a simple linear regression, multilevel statistical modeling could be used to analyze the relationship between the NDVI and rainfall and improve the accuracy of detecting the effect of human activities. Additional factors should be included when analyzing the NDVI-rainfall relationship and detecting human-induced loss of vegetation cover in drylands to improve the accuracy of the approach and elimi-nate some observed non-significant residual trends.

  16. Attribution of satellite observed vegetation trends in a hyper-arid region of the Heihe River Basin, Central Asia

    Directory of Open Access Journals (Sweden)

    Y. Wang

    2014-02-01

    4.5% in 2012. The largest contribution to the overall greening was due to changes in green vegetation cover of the extensive desert areas with a smaller contribution due to changes in the area of irrigated land. Comprehensive analysis with different precipitation data sources found that the greening of the desert was associated with increases in regional precipitation. We found that the area of land irrigated each year was mostly dependent on the runoff gauged one year earlier. Taken together, water availability both from precipitation in the desert and runoff inflow for the irrigation agricultural lands can explain at least 52% of the total variance in regional vegetation cover from 2000 to 2010.

  17. Land mobile satellite transmission measurements at 869 MHz. A comparison of error probabilities for various message block durations and fade margins as a function of vegetation shadowing

    Science.gov (United States)

    Vogel, Wolfhard J.

    1985-01-01

    In order to give vehicles travelling in rural areas of the U.S. access to the telephone network, a Land Mobile Satellite System is being planned. Previously presented data by the author were analyzed for the probability that the received signal level dropped below a threshold during short time blocks of various signal durations and the conditional probability that such an event would reoccur after a given delay. If it assumed that a fade threshold crossing of even 1 msec would produce an error in the transmission, then the derived quantities can be considered error probabilities. Extensive tables and graphs are presented with the results from the analysis. They can be used to devise communication strategies which will provide improved link availability in the presence of vegetation shadowing.

  18. SAT-WIND project. Final report[Winds from satellites for offshore and coastal wind energy mapping and wind-indexing

    Energy Technology Data Exchange (ETDEWEB)

    Hasager, C.B.; Astrup, P.; Nielsen, M. (and others)

    2007-04-15

    The SAT-WIND project 'Winds from satellites for offshore and coastal wind energy mapping and wind-indexing' was a research project funded by STVF/DSF in the years 2003 to 2006 (Sagsnr. 2058-03-0006). The goal of the project was to verify the applicability of satellite wind maps derived from passive microwave, altimeter, scatterometer and imaging Synthetic Aperture Radar (SAR) technologies for wind energy tools for wind resources and wind-indexing. The study area was the Danish Seas including the North Sea, interior seas and the Baltic Sea. The report describes technical details on the satellite data sources including: 1) passive microwave (SSM/I, AMSR-E), 2) passive microwave polarimetric (WindSat), 3) scatterometer (ERS, QuikSCAT, Midori-2 and NSCAT), 4) altimeter (ERS, Topex, Poseidon, GFO-1, Jason-1), 5) SAR (ERS, Envisat). The SAR wind maps were treated in S-WAsP developed by Risoe National Laboratory in cooperation with GRAS A/S in the innovative project SAT-WIND-SMV (Sagsnr. 2104-05-0084) in the years 2005 and 2006 in parallel with SAT-WIND. The results from the SAT-WIND project are presented. These include ocean wind statistics, offshore wind resource estimates and comparison results for wind-indexing. (au)

  19. 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.

  20. Correlation analysis of Normalized Different Vegetation Index (NDVI)difference series and climate variables in the Xilingole steppe,China from 1983 to 1999

    Institute of Scientific and Technical Information of China (English)

    GU Zhihui; CHEN Jin; SHI Peijun; XU Ming

    2007-01-01

    There is a crucial need in the study of global change to understand how terrestrial ecosystems respond to the climate system.It has been demonstrated by many researches that Normalized Different Vegetation Index (NDVI)time series from remotely sensed data,which provide effective information of vegetation conditions on a large scale with highly temporal resolution,have a good relation with meteorological factors.However,few of these studies have taken the cumulative property of NDVI time series into account.In this study,NDVI difference series were proposed to replace the original NDVI time series with NDVI difference series to reappraise the relationship between NDVI and meteorological factors.As a proxy of the vegetation growing process,NDVI difference represents net primary productivity of vegetation at a certain time interval under an environment controlled by certain climatic conditions and other factors.This data replacement is helpful to eliminate the cumulative effect that exist in original NDVI time series,and thus is more appropriate to understand how climate system affects vegetation growth in a short time scale.By using the correlation analysis method,we studied the relationship between NOAA/AVHRR ten-day NDVI difference series and corresponding meteorological data from 1983 to 1999 from 11 meteorological stations located in the Xilingole steppe in Inner Mongolia.The results show that:(1)meteorological factors are found to be more significantly correlation with NDVI difference at the biomass-rising phase than that at the falling phase;(2)the relationship between NDVI difference and climate variables varies with vegetation types and vegetation communities.In a typical steppe dominated by Leymus chinensis,temperature has higher correlation with NDVI difference than precipitation does,and in a typical steppe dominated by Stipa krylovii,the correlation between temperature and NDVI difference is lower than that between precipitation and NDVI difference.In a

  1. A Satellite-Based Assessment of the Distribution and Biomass of Submerged Aquatic Vegetation in the Optically Shallow Basin of Lake Biwa

    Directory of Open Access Journals (Sweden)

    Shweta Yadav

    2017-09-01

    Full Text Available Assessing the abundance of submerged aquatic vegetation (SAV, particularly in shallow lakes, is essential for effective lake management activities. In the present study we applied satellite remote sensing (a Landsat-8 image in order to evaluate the SAV coverage area and its biomass for the peak growth period, which is mainly in September or October (2013 to 2016, in the eutrophic and shallow south basin of Lake Biwa. We developed and validated a satellite-based water transparency retrieval algorithm based on the linear regression approach (R2 = 0.77 to determine the water clarity (2013–2016, which was later used for SAV classification and biomass estimation. For SAV classification, we used Spectral Mixture Analysis (SMA, a Spectral Angle Mapper (SAM, and a binary decision tree, giving an overall classification accuracy of 86.5% and SAV classification accuracy of 76.5% (SAV kappa coefficient 0.74, based on in situ measurements. For biomass estimation, a new Spectral Decomposition Algorithm was developed. The satellite-derived biomass (R2 = 0.79 for the SAV classified area gives an overall root-mean-square error (RMSE of 0.26 kg Dry Weight (DW m-2. The mapped SAV coverage area was 20% and 40% in 2013 and 2016, respectively. Estimated SAV biomass for the mapped area shows an increase in recent years, with values of 3390 t (tons, dry weight in 2013 as compared to 4550 t in 2016. The maximum biomass density (4.89 kg DW m-2 was obtained for a year with high water transparency (September 2014. With the change in water clarity, a slow change in SAV growth was noted from 2013 to 2016. The study shows that water clarity is important for the SAV detection and biomass estimation using satellite remote sensing in shallow eutrophic lakes. The present study also demonstrates the successful application of the developed satellite-based approach for SAV biomass estimation in the shallow eutrophic lake, which can be tested in other lakes.

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

    Directory of Open Access Journals (Sweden)

    André Quintão de Almeida

    2008-12-01

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

  3. Analysis of Temporal and Spatial Changes in the Vegetation Density of Similipal Biosphere Reserve in Odisha (India Using Multitemporal Satellite Imagery

    Directory of Open Access Journals (Sweden)

    Anima Biswal

    2013-01-01

    Full Text Available National parks and protected areas require periodic monitoring because of changing land cover types and variability of landscape contexts within and adjacent to their boundaries. In this study, remote sensing and GIS techniques were used to analyse the changes in the vegetation density particularly in the zones of higher anthropogenic pressure in the Similipal Biosphere Reserve (SBR of Odisha (India, using Landsat imagery from 1975 to 2005. A technique for the detection of postclassification changes was followed and the change in vegetation density as expressed by normalized difference vegetation index was computed. Results indicate that high dense forest in the core zone has been conserved and the highest reforestation has also occurred in this zone of SBR. The results also reveal that anthropological interventions are more in the less dense forest areas and along the roads, whereas high dense forest areas have remained undisturbed and rejuvenated. This study provides baseline data demonstrating alteration in land cover over the past three decades and also serves as a foundation for monitoring future changes in the national parks and protected areas.

  4. LSA-SAF evapotranspiration products based on MSG/SEVIRI: improvement opportunities from moderate spatial resolution satellites sensors for vegetation (SPOT-VGT, MODIS, PROBA-V)

    Science.gov (United States)

    Ghilain, N.; De Roo, F.; Arboleda, A.; Gellens-Meulenberghs, F.

    2012-04-01

    The Satellite Application Facility on Land Surface Analysis (LSA-SAF) proposes a panel of land surface related products derived from the EUMETSAT satellites, MSG (Meteosat Second Generation) and EPS/METOP, and produced in near-real time over Europe, Africa and part of South America. With LSA-SAF products, key surface variables are observed, and allows to characterizing the main processes governing land atmosphere processes. Land evapotranspiration (ET) is one of the variables monitored within LSA-SAF. ET at a spatial resolution of approximately 3 km at the sub-satellite point above the equator is derived in near-real time, every 30 minutes, using a simplified land surface model, forced by LSA-SAF radiation products derived from MSG/SEVIRI data. Given that spatial resolution, some smaller scale processes cannot be resolved, though their contribution may affect the total MSG pixel area ET estimates. Besides, information with an increased resolution is expected to have a positive impact on the total accuracy of the modeled ET. A variety of new remote sensing products derived from EO data at a higher spatial resolution are now publicly available. This is an opportunity to assess the improvement that moderate spatial resolution (250 m to 1 km) satellites sensors for surface and vegetation characterization could offer to the evapotranspiration monitoring at the MSG/SEVIRI scale in the context of LSA-SAF. On the basis of a global analysis and on test cases, we show the usefulness of EO data acquired from moderate resolution satellites sensors (SPOT-VGT, MODIS/Terra&Aqua, MERIS) towards the improvement of the LSA-SAF ET products derived from MSG/SEVIRI. In particular, 4 different variables/indices (land cover map, LAI, surface albedo, open water bodies detection) are assessed regarding the LSA-SAF ET products: 1) the investigated processes at small scales unresolved by the geostationary satellite, e.g. open water bodies dynamics, are better taken into account in the final

  5. Description and validation of an automated methodology for mapping mineralogy, vegetation, and hydrothermal alteration type from ASTER satellite imagery with examples from the San Juan Mountains, Colorado

    Science.gov (United States)

    Rockwell, Barnaby W.

    2012-01-01

    The efficacy of airborne spectroscopic, or "hyperspectral," remote sensing for geoenvironmental watershed evaluations and deposit-scale mapping of exposed mineral deposits has been demonstrated. However, the acquisition, processing, and analysis of such airborne data at regional and national scales can be time and cost prohibitive. The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) sensor carried by the NASA Earth Observing System Terra satellite was designed for mineral mapping and the acquired data can be efficiently used to generate uniform mineral maps over very large areas. Multispectral remote sensing data acquired by the ASTER sensor were analyzed to identify and map minerals, mineral groups, hydrothermal alteration types, and vegetation groups in the western San Juan Mountains, Colorado, including the Silverton and Lake City calderas. This mapping was performed in support of multidisciplinary studies involving the predictive modeling of surface water geochemistry at watershed and regional scales. Detailed maps of minerals, vegetation groups, and water were produced from an ASTER scene using spectroscopic, expert system-based analysis techniques which have been previously described. New methodologies are presented for the modeling of hydrothermal alteration type based on the Boolean combination of the detailed mineral maps, and for the entirely automated mapping of alteration types, mineral groups, and green vegetation. Results of these methodologies are compared with the more detailed maps and with previously published mineral mapping results derived from analysis of high-resolution spectroscopic data acquired by the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) sensor. Such comparisons are also presented for other mineralized and (or) altered areas including the Goldfield and Cuprite mining districts, Nevada and the central Marysvale volcanic field, Wah Wah Mountains, and San Francisco Mountains, Utah. The automated

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

    Science.gov (United States)

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

    1981-01-01

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

  7. Application of Hyperspectral Vegetation Indices to Detect Variations in High Leaf Area Index Temperate Shrub Thicket Canopies

    Science.gov (United States)

    2011-01-01

    Ray, D. (2004). Drought stress and carbon uptake in an Amazon forest measured with spaceborne imaging spectroscopy. Proceedings of the National...Academy of Science, 101, 6039−6044. Asner, G. P., Townsend, A. R., & Braswell, B. H. (2000). Satellite observation of El Niño effects on Amazon forest...physiological responses for detection of salt and drought stress in coastal plant species. Physiologia Plantarum, 131, 422−433. Naumann, J. C., Young

  8. Spatial and radiometric characterization of multi-spectrum satellite images through multi-fractal analysis

    Science.gov (United States)

    Alonso, Carmelo; Tarquis, Ana M.; Zúñiga, Ignacio; Benito, Rosa M.

    2017-03-01

    Several studies have shown that vegetation indexes can be used to estimate root zone soil moisture. Earth surface images, obtained by high-resolution satellites, presently give a lot of information on these indexes, based on the data of several wavelengths. Because of the potential capacity for systematic observations at various scales, remote sensing technology extends the possible data archives from the present time to several decades back. Because of this advantage, enormous efforts have been made by researchers and application specialists to delineate vegetation indexes from local scale to global scale by applying remote sensing imagery. In this work, four band images have been considered, which are involved in these vegetation indexes, and were taken by satellites Ikonos-2 and Landsat-7 of the same geographic location, to study the effect of both spatial (pixel size) and radiometric (number of bits coding the image) resolution on these wavelength bands as well as two vegetation indexes: the Normalized Difference Vegetation Index (NDVI) and the Enhanced Vegetation Index (EVI). In order to do so, a multi-fractal analysis of these multi-spectral images was applied in each of these bands and the two indexes derived. The results showed that spatial resolution has a similar scaling effect in the four bands, but radiometric resolution has a larger influence in blue and green bands than in red and near-infrared bands. The NDVI showed a higher sensitivity to the radiometric resolution than EVI. Both were equally affected by the spatial resolution. From both factors, the spatial resolution has a major impact in the multi-fractal spectrum for all the bands and the vegetation indexes. This information should be taken in to account when vegetation indexes based on different satellite sensors are obtained.

  9. A comparative study of satellite and ground-based phenology.

    Science.gov (United States)

    Studer, S; Stöckli, R; Appenzeller, C; Vidale, P L

    2007-05-01

    Long time series of ground-based plant phenology, as well as more than two decades of satellite-derived phenological metrics, are currently available to assess the impacts of climate variability and trends on terrestrial vegetation. Traditional plant phenology provides very accurate information on individual plant species, but with limited spatial coverage. Satellite phenology allows monitoring of terrestrial vegetation on a global scale and provides an integrative view at the landscape level. Linking the strengths of both methodologies has high potential value for climate impact studies. We compared a multispecies index from ground-observed spring phases with two types (maximum slope and threshold approach) of satellite-derived start-of-season (SOS) metrics. We focus on Switzerland from 1982 to 2001 and show that temporal and spatial variability of the multispecies index correspond well with the satellite-derived metrics. All phenological metrics correlate with temperature anomalies as expected. The slope approach proved to deviate strongly from the temporal development of the ground observations as well as from the threshold-defined SOS satellite measure. The slope spring indicator is considered to indicate a different stage in vegetation development and is therefore less suited as a SOS parameter for comparative studies in relation to ground-observed phenology. Satellite-derived metrics are, however, very susceptible to snow cover, and it is suggested that this snow cover should be better accounted for by the use of newer satellite sensors.

  10. Interactions between river stage and wetland vegetation detected with a Seasonality Index derived from LANDSAT images in the Apalachicola delta, Florida

    Science.gov (United States)

    Fagherazzi, S.; Toffolon, M.; la Cecilia, D.; Woodcock, C. E.

    2016-12-01

    The distribution of swamp floodplain vegetation and its evolution in the lower non-tidal reaches of the Apalachicola River, Florida USA, is mapped using Landsat Thematic Mapper and Enhanced Thematic Mapper Plus (TM/ETM+) images captured over a period of 29 years. A newly developed seasonality index (SI), the ratio of the NDVI in winter months to the summer months, shows that the hardwood swamp, dominated by bald cypress and water tupelo, is slowly replaced by bottomland hardwood forest. This forest shift is driven by lower water levels in the Apalachicola River in the last 30 years, and predominantly occurs in the transitional area between low floodplains and high river banks. A negative correlation between maximum summer NDVI and water levels in winter suggests the growth of more vigorous vegetation in the vicinity of sloughs during years with low river flow. A negative correlation with SI further indicates that these vegetation patches are possibly replaced by species typical of drier floodplain conditions.

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

    Science.gov (United States)

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

    2016-10-01

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

  12. Sixteen Years of Agricultural Drought Assessment of the BioBío Region in Chile Using a 250 m Resolution Vegetation Condition Index (VCI

    Directory of Open Access Journals (Sweden)

    Francisco Zambrano

    2016-06-01

    Full Text Available 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 BioBío 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 250 m 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 (November–April instead of the regular growing season (September–April, 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 BioBío 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 (250 m with the measured crop yield to identify

  13. 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 vegetation...... greenness. The vegetation optical depth (VOD) derived from satellite passive microwave observations is mainly sensitive to the water content in total aboveground vegetation layer. VOD therefore provides a complementary data source to NDVI for monitoring biomass dynamics in drylands, yet further evaluations...... based on ground measurements are needed for an improved understanding of the potential advantages. In this study, we assess the capability of a long-term VOD dataset (1992-2011) to capture the temporal and spatial variability of in situ measured green biomass (herbaceous mass and woody plant foliage...

  14. 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 < 0.05) and a decrease from 2014 to 2015; however, 2015 levels were still significantly higher than in 2013. ETa was also higher in 2014 vs. 2013, with an estimated 74.5 million cubic meters in 2013 and 88.9 in 2014. The most intense greening occurred in the zone of inundation but also extended into the non-flooded part of the riparian zone, indicating replenishment of groundwater. These findings suggest the peak response by vegetation to the flow lasted about one year, followed by a decrease in 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.

  15. Índice de cobertura vegetal e sua modelagem para cultivares de soja no sul de Minas Gerais Index of vegetal cover and its modeling for soybean cultivars in the south of Minas Gerais

    Directory of Open Access Journals (Sweden)

    Vitor Corrêa de Mattos Barreto

    2010-10-01

    Full Text Available A cobertura vegetal do solo é decisiva para redução dos efeitos erosivos do impacto direto das gotas de chuva na superfície do solo. Desta forma, objetivou-se com este estudo determinar o índice de cobertura vegetal (CV e desenvolver modelos para sua estimativa para a cultura da soja, usando os atributos climáticos no período de chuvas intensas no Sul de Minas Gerais. As determinações da CV foram feitas semanalmente, na área experimental do Departamento de Ciência do Solo, Universidade Federal de Lavras, no período de novembro de 1999 a maio de 2000, em 28 cultivares de soja com potencial para cultivo nesta região. Para avaliação da cobertura vegetal foi utilizada a metodologia descrita por Stocking (1988. Na modelagem procurou-se relacionar a CV com os valores acumulados dos seguintes atributos climáticos: temperatura média (Tmed, precipitação (PREC e umidade relativa do ar (UR. Os valores de cobertura vegetal apresentaram uma amplitude de variação de 56 a 83%, sendo BR 162, LO 12 L e M. Soy 108 as cultivares mais eficientes e FT Abyara e Tucano as menos eficientes. O hábito diferencial de crescimento das cultivares ajuda a explicar esse comportamento. O modelo ajustado adequado para estimativa da CV foi: CV = 116589,976 + 0,422 . Tmed + 0,132 . PREC - 0,095 . UR + 0,000024 . Tmed², R² = 0,99 (P Vegetal cover of soil is decisive to reduce the erosive effects of direct impact of raindrops on the soil surface. Therefore, the objective of this study was to determine the vegetal cover (CC index and to develop models to estimate it for soybean cultivars, using climatic attributes in the period of intense rains in the South of the State of Minas Gerais in Brazil. CC was measured weekly in the experimental area of the Department of Soil Science, Federal University of Lavras, from November 1999 to May 2000, for 28 soybean cultivars with yield potential in this region. To evaluate the vegetal cover, the method described by

  16. Algorithm developing of gross primary production from its capacity and a canopy conductance index using flux and global observing satellite data

    Science.gov (United States)

    Muramatsu, Kanako; Furumi, Shinobu; Daigo, Motomasa

    2015-10-01

    We plan to estimate gross primary production (GPP) using the SGLI sensor on-board the GCOM-C1 satellite after it is launched in 2017 by the Japan Aerospace Exploration Agency, as we have developed a GPP estimation algorithm that uses SGLI sensor data. The characteristics of this GPP estimation method correspond to photosynthesis. The rate of plant photosynthesis depends on the plant's photosynthesis capacity and the degree to which photosynthesis is suppressed. The photosynthesis capacity depends on the chlorophyll content of leaves, which is a plant physiological parameter, and the degree of suppression of photosynthesis depends on weather conditions. The framework of the estimation method to determine the light-response curve parameters was developed using ux and satellite data in a previous study[1]. We estimated one of the light-response curve parameters based on the linear relationship between GPP capacity at 2000 (μmolm-2s-1) of photosynthetically active radiation and a chlorophyll index (CIgreen [2;3] ). The relationship was determined for seven plant functional types. Decreases in the photosynthetic rate are controlled by stomatal opening and closing. Leaf stomatal conductance is maximal during the morning and decreases in the afternoon. We focused on daily changes in leaf stomatal conductance. We used open shrub flux data and MODIS reflectance data to develop an algorithm for a canopy. We first evaluated the daily changes in GPP capacity estimated from CIgreen and photosynthesis active radiation using light response curves, and GPP observed during a flux experiment. Next, we estimated the canopy conductance using flux data and a big-leaf model using the Penman-Monteith equation[4]. We estimated GPP by multiplying GPP capacity by the normalized canopy conductance at 10:30, the time of satellite observations. The results showed that the estimated daily change in GPP was almost the same as the observed GPP. From this result, we defined a normalized canopy

  17. Satellite derived 30-year trends in terrestrial frozen and non-frozen seasons and associated impacts to vegetation and atmospheric CO2

    Science.gov (United States)

    Kim, Y.; Kimball, J. S.; McDonald, K. C.; Glassy, J. M.

    2010-12-01

    Approximately 66 million km2 (52.5 %) of the global vegetated land area experiences seasonally frozen temperatures as a major constraint to ecosystem processes. The freeze-thaw (F/T) status of the landscape as derived from satellite microwave remote sensing is closely linked to surface energy budget and hydrological activity, vegetation phenology, terrestrial carbon budgets and land-atmosphere trace gas exchange. We utilized a seasonal threshold algorithm based temporal change classification of 37GHz frequency, vertically polarized brightness temperatures (Tb) from the Nimbus-7 Scanning Multichannel Microwave Radiometer (SMMR) pathfinder and Special Sensor Microwave Imager (SSM/I) to classify daily F/T status for all global land areas where seasonal frozen temperatures are a major constraint to ecosystem processes. A temporally consistent, long-term (30 year) daily F/T record was created by pixel-wise correction of the SMMR Tb record based on empirical analyses of overlapping SMMR and SSM/I measurements acquired during 1987. The resulting combined F/T record was validated against in situ temperature measurements from the global weather station network and applied to quantify regional patterns and trends in timing and length of frozen and non-frozen seasons. The F/T results were compared against other surrogate measures of biosphere activity including satellite AVHRR (GIMMS) based vegetation greenness (NDVI) and atmospheric CO2 concentrations over northern (>50N) land areas. The resulting F/T record showed mean annual classification accuracies of 91 (+/-1.0) and 84 (+/- 0.9) percent for PM and AM overpass retrievals relative to in situ weather station records. The F/T record showed significant (P=0.008) long-term trends in non-frozen period (0.207 days/yr) that were largely driven by earlier onset of spring thaw (-0.121 days/yr) and a small, delayed trend the arrival of the frozen period (0.107 days/yr). These results coincide with 0.025 C/yr warming trends in

  18. Using NASA Earth Observing Satellites and Statistical Model Analysis to Monitor Vegetation and Habitat Rehabilitation in Southwest Virginia's Reclaimed Mine Lands

    Science.gov (United States)

    Tate, Z.; Dusenge, D.; Elliot, T. S.; Hafashimana, P.; Medley, S.; Porter, R. P.; Rajappan, R.; Rodriguez, P.; Spangler, J.; Swaminathan, R. S.; VanGundy, R. D.

    2014-12-01

    The majority of the population in southwest Virginia depends economically on coal mining. In 2011, coal mining generated $2,000,000 in tax revenue to Wise County alone. However, surface mining completely removes land cover and leaves the land exposed to erosion. The destruction of the forest cover directly impacts local species, as some are displaced and others perish in the mining process. Even though surface mining has a negative impact on the environment, land reclamation efforts are in place to either restore mined areas to their natural vegetated state or to transform these areas for economic purposes. This project aimed to monitor the progress of land reclamation and the effect on the return of local species. By incorporating NASA Earth observations, such as Landsat 8 Operational Land Imager (OLI) and Landsat 5 Thematic Mapper (TM), re-vegetation process in reclamation sites was estimated through a Time series analysis using the Normalized Difference Vegetation Index (NDVI). A continuous source of cloud free images was accomplished by utilizing the Spatial and Temporal Adaptive Reflectance Fusion Model (STAR-FM). This model developed synthetic Landsat imagery by integrating the high-frequency temporal information from Terra/Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) and high-resolution spatial information from Landsat sensors In addition, the Maximum Entropy Modeling (MaxENT), an eco-niche model was used to estimate the adaptation of animal species to the newly formed habitats. By combining factors such as land type, precipitation from Tropical Rainfall Measuring Mission (TRMM), and slope from Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), the MaxENT model produced a statistical analysis on the probability of species habitat. Altogether, the project compiled the ecological information which can be used to identify suitable habitats for local species in reclaimed mined areas.

  19. 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.

  20. On the Role of Urban and Vegetative Land Cover in the Identification of Tornado Damage Using Dual-Resolution Multispectral Satellite Imagery

    Science.gov (United States)

    Kingfield, D.; de Beurs, K.

    2014-12-01

    It has been demonstrated through various case studies that multispectral satellite imagery can be utilized in the identification of damage caused by a tornado through the change detection process. This process involves the difference in returned surface reflectance between two images and is often summarized through a variety of ratio-based vegetation indices (VIs). Land cover type plays a large contributing role in the change detection process as the reflectance properties of vegetation can vary based on several factors (e.g. species, greenness, density). Consequently, this provides the possibility for a variable magnitude of loss, making certain land cover regimes less reliable in the damage identification process. Furthermore, the tradeoff between sensor resolution and orbital return period may also play a role in the ability to detect catastrophic loss. Moderate resolution imagery (e.g. Moderate Resolution Imaging Spectroradiometer (MODIS)) provides relatively coarse surface detail with a higher update rate which could hinder the identification of small regions that underwent a dynamic change. Alternatively, imagery with higher spatial resolution (e.g. Landsat) have a longer temporal return period between successive images which could result in natural recovery underestimating the absolute magnitude of damage incurred. This study evaluates the role of land cover type and sensor resolution on four high-end (EF3+) tornado events occurring in four different land cover groups (agriculture, forest, grassland, urban) in the spring season. The closest successive clear images from both Landsat 5 and MODIS are quality controlled for each case. Transacts of surface reflectance across a homogenous land cover type both inside and outside the damage swath are extracted. These metrics are synthesized through the calculation of six different VIs to rank the calculated change metrics by land cover type, sensor resolution and VI.

  1. Comparison of satellite imagery and infrared aerial photography as vegetation mapping methods in an arctic study area: Jameson Land, East Greenland

    DEFF Research Database (Denmark)

    Hansen, Birger Ulf; Mosbech, Anders

    1994-01-01

    Remote Sensing, vegetation mapping, SPOT, Landsat TM, aerial photography, Jameson Land, East Greenland......Remote Sensing, vegetation mapping, SPOT, Landsat TM, aerial photography, Jameson Land, East Greenland...

  2. An angular vegetation index for imaging spectroscopy data—Preliminary results on forest damage detection in the Bavarian National Park, Germany

    Science.gov (United States)

    Fassnacht, Fabian Ewald; Latifi, Hooman; Koch, Barbara

    2012-10-01

    A vegetation index (VI) is presented which is calculated as the inner angles of a triangle. The triangle is spanned between three distinct points (on a spectral curve of imaging spectroscopy data) which are defined for each individual pixel by the wavelength (x-axis) and the reflection value (y-axis). The ideal wavelengths of the three points are dependent on the response variable investigated. The case-study within this paper in which this angular VI is applied, aims at the development of an index to automatically detect spruce bark beetle infections in the Bavarian National Park, Germany. In order to determine the optimum wavelengths to separate damaged from non-damaged trees the three-angle-indices (TAIs) for all possible combinations of available wavelengths of HyMap imaging spectroscopy data in the vis-NIR-region (0.455-0.986 μm) were calculated. The resulting 27,417 images served as input predictor variables to a genetic algorithm (GA) which used nearest centroid classifier as fitness functions to detect the most stable predictors and separate the six classes (three damage classes) defined within the study area. The fitness functions integrated in the GA reached classification accuracies of up to 94.8% when using forward selection models of the most stable genes featuring maximum 50 predictors. Based on those results, three from the original 27,417 predictors were extracted to map forest damages over the full image extent based on a support vector machines (SVMs) classification. We conducted the same experiment with 82 vegetation indices described in literature and achieved slightly lower GA overall accuracies of 86.8% using the nearest centroid classifier. The SVM maps produced with the three best VI predictors were comparable to the TAI results.

  3. EPIC-Simulated and MODIS-Derived Leaf Area Index (LAI) Comparisons Across mMltiple Spatial Scales RSAD Oral Poster based session

    Science.gov (United States)

    Leaf Area Index (LAI) is an important parameter in assessing vegetation structure for characterizing forest canopies over large areas at broad spatial scales using satellite remote sensing data. However, satellite-derived LAI products can be limited by obstructed atmospheric cond...

  4. Evaluating Vegetation Health Condition Using MODIS Data in the Three Gorges Area, China

    Institute of Scientific and Technical Information of China (English)

    韩贵锋; 谢雨丝; 蔡智

    2015-01-01

    The satellite-based vegetation condition index (VCI) and temperature condition index (TCI) have been used extensively for drought detection and tracking, the assessment of weather impacts on vegetation and evaluation of the health and productivity of vegetation. In this study, in order to detect and monitor the growth condition of vegetation, we have collected data on vegetation indices and land surface temperature derived from MODIS (2001-2012) and deifned a vegetation health index (VHI) based on VCI and TCI for assessing vegetation health condition in the Three Gorges Area, China (TGA). The results of the study show that temporal and spatial characteristics of vegetation health condition can be detected, tracked and mapped by the VHI index. In most parts of the TGA, the vegetation health condition showed an overall increasing trend during the study period, especially in Wulong, Fengdu, Shizhu and other regions located in the midstream sections of the Three Gorges Reservoir. In addition, the four studied vegetation types all showed clear increasing trends during the study period. The increasing trend in the vegetation health condition shows a strong positive correlation with topographical slope and altitude (below 500 m). Over the seasons, this trend is strongest in autumn, followed by spring. However, the correlations between vegetation health condition and climatic factors are more frequently significant in summer and winter than in autumn and spring. The vegetation health condition has been low in 2006 and 2011. This finding is consistent with the extreme weather conditions in those two years. However, only in the summer is vegetation health condition signiifcantly correlated with three climatic factors in most of the study area. This result implies that vegetation growth may show a lagged response to climatic factors and may also be affected by human activities, including agricultural activities, industrial activities and other economic activities.

  5. The experience of land cover change detection by satellite data

    Institute of Scientific and Technical Information of China (English)

    Lev SPIVAK; Irina VITKOVSKAYA; Madina BATYRBAYEVA; Alexey TEREKHOV

    2012-01-01

    Sigificant dependence from climate and anthropogenic influences characterize ecological systems of Kazakhstan.As result of the geographical location of the republic and ecological situation vegetative degradation sites exist throughout the territory of Kazakhstan.The major process of desertification takes place in the arid and semi-arid areas.To allocate spots of stable degradation of vegetation,the transition zone was first identified.Productivity of vegetation in transfer zone is slightly dependent on climate conditions.Multi-year digital maps of vegetation index were generated with NOAA satellite images.According to the result,the territory of the republic was zoned by means of vegetation productivity criterion.All the arable lands in Kazakhstan are in the risky agriculture zone.Estimation of the productivity of agricultural lands is highly important in the context of risky agriculture,where natural factors,such as wind and water erosion,can significantly change land quality in a relatively short time period.We used an integrated vegetation index to indicate land degradation measures to assess the inter-annual features in the response of vegetation to variations in climate conditions from lowresolution satellite data for all of Kazakhstan.This analysis allowed a better understanding of the spatial and temporal variations of land degradation in the country.

  6. Using precipitation, vertical root distribution, and satellite-retrieved vegetation information to parameterize water stress in a Penman-Monteith approach to evapotranspiration modeling under Mediterranean climate

    Science.gov (United States)

    Bai, Yun; Zhang, Jiahua; Zhang, Sha; Koju, Upama Ashish; Yao, Fengmei; Igbawua, Tertsea

    2017-03-01

    Recent studies have shown that global Penman-Monteith equation based (PM-based) models poorly simulate water stress when estimating evapotranspiration (ET) in areas having a Mediterranean climate (AMC). In this study, we propose a novel approach using precipitation, vertical root distribution (VRD), and satellite-retrieved vegetation information to simulate water stress in a PM-based model (RS-WBPM) to address this issue. A multilayer water balance module is employed to simulate the soil water stress factor (SWSF) of multiple soil layers at different depths. The water stress factor (WSF) for surface evapotranspiration is determined by VRD information and SWSF in each layer. Additionally, four older PM-based models (PMOV) are evaluated at 27 flux sites in AMC. Results show that PMOV fails to estimate the magnitude or capture the variation of ET in summer at most sites, whereas RS-WBPM is successful. The daily ET resulting from RS-WBPM incorporating recommended VI (NDVI for shrub and EVI for other biomes) agrees well with observations, with R2=0.60 (RMSE = 18.72 W m-2) for all 27 sites and R2=0.62 (RMSE = 18.21 W m-2) for 25 nonagricultural sites. However, combined results from the optimum older PM-based models at specific sites show R2 values of only 0.50 (RMSE = 20.74 W m-2) for all 27 sites. RS-WBPM is also found to outperform other ET models that also incorporate a soil water balance module. As all inputs of RS-WBPM are globally available, the results from RS-WBPM are encouraging and imply the potential of its implementation on a regional and global scale.

  7. Analysis of the Scaling Effects in the Area-Averaged Fraction of Vegetation Cover Retrieved Using an NDVI-Isoline-Based Linear Mixture Model

    OpenAIRE

    Hiroki Yoshioka; Kenta Obata; Tomoaki Miura

    2012-01-01

    The spectral unmixing of a linear mixture model (LMM) with Normalized Difference Vegetation Index (NDVI) constraints was performed to estimate the fraction of vegetation cover (FVC) over the earth’s surface in an effort to facilitate long-term surface vegetation monitoring using a set of environmental satellites. Although the integrated use of multiple sensors improves the spatial and temporal quality of the data sets, area-averaged FVC values obtained using an LMM-based algorithm suffer from...

  8. Prediction of high spatio-temporal resolution land surface temperature under cloudy conditions using microwave vegetation index and ANN

    Science.gov (United States)

    Shwetha, H. R.; Kumar, D. Nagesh

    2016-07-01

    Land Surface Temperature (LST) with high spatio-temporal resolution is in demand for hydrology, climate change, ecology, urban climate and environmental studies, etc. Moderate Resolution Imaging Spectroradiometer (MODIS) is one of the most commonly used sensors owing to its high spatial and temporal availability over the globe, but is incapable of providing LST data under cloudy conditions, resulting in gaps in the data. In contrast, microwave measurements have a capability to penetrate under clouds. The current study proposes a methodology by exploring this property to predict high spatio-temporal resolution LST under cloudy conditions during daytime and nighttime without employing in-situ LST measurements. To achieve this, Artificial Neural Networks (ANNs) based models are employed for different land cover classes, utilizing Microwave Polarization Difference Index (MPDI) at finer resolution with ancillary data. MPDI was derived using resampled (from 0.25° to 1 km) brightness temperatures (Tb) at 36.5 GHz channel of dual polarization from Advance Microwave Scanning Radiometer (AMSR)-Earth Observing System and AMSR2 sensors. The proposed methodology is tested over Cauvery basin in India and the performance of the model is quantitatively evaluated through performance measures such as correlation coefficient (r), Nash Sutcliffe Efficiency (NSE) and Root Mean Square Error (RMSE). Results revealed that during daytime, AMSR-E(AMSR2) derived LST under clear sky conditions corresponds well with MODIS LST resulting in values of r ranging from 0.76(0.78) to 0.90(0.96), RMSE from 1.76(1.86) K to 4.34(4.00) K and NSE from 0.58(0.61) to 0.81(0.90) for different land cover classes. During nighttime, r values ranged from 0.76(0.56) to 0.87(0.90), RMSE from 1.71(1.70) K to 2.43(2.12) K and NSE from 0.43(0.28) to 0.80(0.81) for different land cover classes. RMSE values found between predicted LST and MODIS LST during daytime under clear sky conditions were within acceptable

  9. Development Of Index To Assess Drought Conditions Using Geospatial Data A Case Study Of Jaisalmer District, Rajasthan, India

    Science.gov (United States)

    Chhajer, Vaidehi; Prabhakar, Sumati; Rama Chandra Prasad, P.

    2015-12-01

    The Jaisalmer district of Rajasthan province of India was known to suffer with frequent drought due to poor and delayed monsoon, abnormally high summer-temperature and insufficient water resources. However flood-like situation prevails in the drought prone Jaisalmer district of Rajasthan as torrential rains are seen to affect the region in the recent years. In the present study, detailed analysis of meteorological, hydrological and satellite data of the Jaisalmer district has been carried out for the years 2006-2008. Standardized Precipitation Index (SPI), Consecutive Dry Days (CDD) and Effective Drought Index (EDI) have been used to quantify the precipitation deficit. Standardized Water-Level Index (SWI) has been developed to assess ground-water recharge-deficit. Vegetative drought indices like Vegetation Condition Index (VCI), Temperature Condition Index (TCI), Vegetation Health Index (VHI), Normalized Difference Vegetation Index (NDVI) and Modified Soil-Adjusted Vegetation Index 2 have been calculated. We also introduce two new indices Soil based Vegetation Condition Index (SVCI) and Composite Drought Index (CDI) specifically for regions like Jaisalmer where aridity in soil and affects vegetation and water-level.

  10. 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.

  11. Development and testing of an index of biotic integrity based on submersed and floating vegetation and its application to assess reclamation wetlands in Alberta's oil sands area, Canada.

    Science.gov (United States)

    Rooney, Rebecca C; Bayley, Suzanne E

    2012-01-01

    We developed and tested a plant-based index of biological integrity (IBI) and used it to evaluate the existing reclamation wetlands in Alberta's oil sands mining region. Reclamation plans call for >15,000 ha of wetlands to be constructed, but currently, only about 25 wetlands are of suitable age for evaluation. Reclamation wetlands are typically of the shallow open water type and range from fresh to sub-saline. Tailings-contaminated wetlands in particular may have problems with hydrocarbon- and salt-related toxicity. From 60 initial candidate metrics in the submersed aquatic and floating vegetation communities, we selected five to quantify biological integrity. The IBI included two diversity-based metrics: the species richness of floating vegetation and the percent of total richness contributed by Potamogeton spp. It also included three relative abundance-based metrics: that of Ceratophyllum demersum, of floating leafed species and of alkali-tolerant species. We evaluated the contribution of nonlinear metrics to IBI performance but concluded that the correlation between IBI scores and wetland condition was not improved. The method used to score metrics had an influence on the IBI sensitivity. We conclude that continuous scoring relative to the distribution of values found in reference sites was superior. This scoring approach provided good sensitivity and resolution and was grounded in reference condition theory. Based on these IBI scores, both tailings-contaminated and tailings-free reclamation wetlands have significantly lower average biological integrity than reference wetlands (ANOVA: F(2,59) = 34.7, p = 0.000000000107).

  12. Integrating vegetation index time series and meteorological data to understand the effect of the land use/land cover (LULC) in the climatic seasonality of the Brazilian Cerrado

    Science.gov (United States)

    Lins, D. B.; Zullo, J.; Friedel, M. J.

    2013-12-01

    The Cerrado (savanna ecosystem) of São Paulo state (Brazil) represent a complex mosaic of different typologies of uses, actors and biophysical and social restrictions. Originally, 14% of the state of São Paulo area was covered by the diversity of Cerrado phytophysiognomies. Currently, only 1% of this original composition remains fragmented into numerous relicts of biodiversity, mainly concentrated in the central-eastern of the state. A relevant part of the fragments are found in areas of intense coverage change by human activities, whereas the greatest pressure comes from sugar cane cultivation, either by direct replacement of Cerrado vegetation or occupying pasture areas in the fragments edges. As a result, new local level dynamics has been introduced, directly or indirectly, affecting the established of processes in climate systems. In this study, the main goal is analyzing the relationship between the Cerrado landscape changing and the climate dynamics in regional and local areas. The multi-temporal MODIS 250 m Vegetation Index (VI) datasets (period of 2000 to 2012) are integrated with precipitation data of the correspondent period (http://www.agritempo.gov.br/),one of the most important variable of the spatial phytophysiognomies distribution. The integration of meteorological data enable the development of an integrated approach to understand the relationship between climatic seasonality and the changes in the spatial patterns. A procedure to congregated diverse dynamics information is the Self Organizing Map (SOM, Kohonen, 2001), a technique that relies on unsupervised competitive learning (Kohonen and Somervuo 2002) to recognize patterns. In this approach, high-dimensional data are represented on two dimensions, making possible to obtain patterns that takes into account information from different natures. Observed advances will contribute to bring machine-learning techniques as a valid tool to provide improve in land use/land cover (LULC) analyzes at

  13. Assessing vegetation response to drought in the northern Great Plains using vegetation and drought indices

    Science.gov (United States)

    Ji, Lei; Peters, Albert J.

    2003-01-01

    The Normalized Difference Vegetation Index (NDVI) derived from the Advanced Very High Resolution Radiometer (AVHRR) has been widely used to monitor moisture-related vegetation condition. The relationship between vegetation vigor and moisture availability, however, is complex and has not been adequately studied with satellite sensor data. To better understand this relationship, an analysis was conducted on time series of monthly NDVI (1989–2000) during the growing season in the north and central U.S. Great Plains. The NDVI was correlated to the Standardized Precipitation Index (SPI), a multiple-time scale meteorological-drought index based on precipitation. The 3-month SPI was found to have the best correlation with the NDVI, indicating lag and cumulative effects of precipitation on vegetation, but the correlation between NDVI and SPI varies significantly between months. The highest correlations occurred during the middle of the growing season, and lower correlations were noted at the beginning and end of the growing season in most of the area. A regression model with seasonal dummy variables reveals that the relationship between the NDVI and SPI is significant in both grasslands and croplands, if this seasonal effect is taken into account. Spatially, the best NDVI–SPI relationship occurred in areas with low soil water-holding capacity. Our most important finding is that NDVI is an effective indicator of vegetation-moisture condition, but seasonal timing should be taken into consideration when monitoring drought with the NDVI.

  14. Índice de vegetação do sensor MODIS na estimativa da produtividade agrícola da cana-de-açúcar Vegetation index from MODIS sensor to estimate sugarcane yield

    Directory of Open Access Journals (Sweden)

    Michelle Cristina Araujo Picoli

    2009-09-01

    Full Text Available A participação da cultura da cana-de-açúcar no fornecimento de matéria prima para produção de açúcar e também de álcool, como fonte alternativa de energia, tem sido relevante para o crescimento econômico do Brasil. Consequentemente, a disponibilidade de informações precisas sobre a produção agrícola dessa cultura é importante para auxiliar no planejamento e na tomada de decisões em toda a cadeia produtiva. O presente trabalho teve como objetivo estimar a produtividade agrícola de talhões de cana-de-açúcar para as safras 2004/2005 e 2005/2006, a partir de um modelo agronômico ajustado com dados orbitais. A inovação deste modelo consiste no uso do índice de área foliar (IAF estimado a partir do produto índice de vegetação NDVI (Normalized Difference Vegetation Index do sensor MODIS (Moderate Resolution Imaging Spectroradiometer a bordo do satélite Terra da NASA (National Aeronautics Space Administration. O modelo agronômico explicou 31% e 25% da variação da produtividade observada entre talhões nos anos safra 2004/2005 e 2005/2006, respectivamente, o que se deve fundamentalmente ao uso das imagens NDVI do MODIS. O resultado do modelo pode ser usado para auxiliar e aprimorar a previsão da estimativa da produtividade feita in loco.The contribution of sugarcane crop to provide raw material to produce sugar and also alcohol as an alternative energy source has been relevant to the economic growth of Brazil. Therefore, the availability of precise agricultural production information about this crop is important for planning and decision-making in the entire productive chain. The present work has the objective to estimate sugarcane yield in crop fields during the crop years 2004/2005 and 2005/2006, based on an agronomic model fit with orbital data. The innovation of this model consists in the use of the leaf area index (LAI estimated from the NDVI (Normalized Difference Vegetation Index produced by the MODIS sensor

  15. Variability of the infrared complex refractive index of African mineral dust: experimental estimation and implications for radiative transfer and satellite remote sensing

    Directory of Open Access Journals (Sweden)

    C. Di Biagio

    2014-04-01

    relevant to radiative transfer (mass extinction efficiency, kext, single scattering albedo, ω, and asymmetry factor, g, have been calculated, by using the Mie theory, for the five analysed dust samples, based on the estimated refractive index and measured particle size distribution. The optical properties show a large sample-to-sample variability. This variability is expected to significantly impact satellite retrievals of atmospheric and surface parameters and estimates of the dust radiative forcing.

  16. 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.

  17. 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

  18. Functional analysis of normalized difference vegetation index curves reveals overwinter mule deer survival is driven by both spring and autumn phenology.

    Science.gov (United States)

    Hurley, Mark A; Hebblewhite, Mark; Gaillard, Jean-Michel; Dray, Stéphane; Taylor, Kyle A; Smith, W K; Zager, Pete; Bonenfant, Christophe

    2014-01-01

    Large herbivore populations respond strongly to remotely sensed measures of primary productivity. Whereas most studies in seasonal environments have focused on the effects of spring plant phenology on juvenile survival, recent studies demonstrated that autumn nutrition also plays a crucial role. We tested for both direct and indirect (through body mass) effects of spring and autumn phenology on winter survival of 2315 mule deer fawns across a wide range of environmental conditions in Idaho, USA. We first performed a functional analysis that identified spring and autumn as the key periods for structuring the among-population and among-year variation of primary production (approximated from 1 km Advanced Very High Resolution Radiometer Normalized Difference Vegetation Index (NDVI)) along the growing season. A path analysis showed that early winter precipitation and direct and indirect effects of spring and autumn NDVI functional components accounted for 45% of observed variation in overwinter survival. The effect size of autumn phenology on body mass was about twice that of spring phenology, while direct effects of phenology on survival were similar between spring and autumn. We demonstrate that the effects of plant phenology vary across ecosystems, and that in semi-arid systems, autumn may be more important than spring for overwinter survival.

  19. Consumption Frequency of Foods Away from Home Linked with Higher Body Mass Index and Lower Fruit and Vegetable Intake among Adults: A Cross-Sectional Study

    Directory of Open Access Journals (Sweden)

    Rebecca A. Seguin

    2016-01-01

    Full Text Available Introduction. Consumption of foods prepared away from home (FAFH has grown steadily since the 1970s. We examined the relationship between FAFH and body mass index (BMI and fruit and vegetable (FV consumption. Methods. Frequency of FAFH, daily FV intake, height and weight, and sociodemographic data were collected using a telephone survey in 2008-2009. Participants included a representative sample of 2,001 adult men and women (mean age 54±15 years residing in King County, WA, with an analytical sample of 1,570. Frequency of FAFH was categorized as 0-1, 2–4, or 5+ times per week. BMI was calculated from self-reported height and weight. We examined the relationship between FAFH with FV consumption and BMI using multivariate models. Results. Higher frequency of FAFH was associated with higher BMI, after adjusting for age, income, education, race, smoking, marital status, and physical activity (women: p=0.001; men: p=0.003. There was a negative association between frequency of FAFH and FV consumption. FAFH frequency was significantly (p<0.001 higher among males than females (43.1% versus 54.0% eating out 0-1 meal per week, resp.. Females reported eating significantly (p<0.001 more FV than males. Conclusion. Among adults, higher frequency of FAFH was related to higher BMI and less FV consumption.

  20. Atmospheric COS measurements and satellite-derived vegetation fluorescence data to evaluate the terrestrial gross primary productivity of CMIP5 model

    Science.gov (United States)

    Peylin, Philippe; MacBean, Natasha; Launois, Thomas; Belviso, Sauveur; Cadule, Patricia; Maignan, Fabienne

    2016-04-01

    Predicting the fate of the ecosystem carbon stocks and their sensitivity to climate change strongly relies on our ability to accurately model the gross carbon fluxes, i.e. photosynthesis and respiration. The Gross Primary Productivity (GPP) simulated by the different terrestrial models used in CMIP5 show large differences however, not only in terms of mean value but also in terms of phase and amplitude, thus hampering accurate investigations into carbon-climate feedbacks. While the net C flux of an ecosystem (NEE) can be measured in situ with the eddy covariance technique, the GPP is not directly accessible at larger scales and usually estimates are based on indirect measurements combining different tracers. Recent measurements of a new atmospheric tracer, the Carbonyl sulphide (COS), as well as the global measurement of Solar Induced Fluorescence (SIF) from satellite instruments (GOSAT, GOME2) open a new window for evaluating the GPP of earth system models. The use of COS relies on the fact that it is absorbed by the leaves in a similar manner to CO2, while there seems to be nothing equivalent to respiration for COS. Following recent work by Launois et al. (ACP, 2015), there is a potential to evaluate model GPP from atmospheric COS and CO2 measurements, using a transport model and recent parameterizations for the non-photosynthetic sinks (oxic soils, atmospheric oxidation) and biogenic sources (oceans and anoxic soils) of COS. Vegetation uptake of COS is modeled as a linear function of GPP and the ratio of COS to CO2 rate of uptake by plants. For the fluorescence, recent measurements of SIF from space appear to be highly correlated with monthly variations of data-driven GPP estimates (Guanter et al., 2012), following a strong dependence of vegetation SIF on photosynthetic activity. These global measurements thus provide new indications on the timing of canopy carbon uptake. In this work, we propose a dual approach that combines the strength of both COS and SIF

  1. Evaluation of satellite based indices for gross primary production estimates in a sparse savanna in the Sudan

    Directory of Open Access Journals (Sweden)

    M. Sjöström

    2009-01-01

    Full Text Available One of the more frequently applied methods for integrating controls on primary production through satellite data is the Light Use Efficiency (LUE approach. Satellite indices such as the Normalized Difference Vegetation Index (NDVI, Enhanced Vegetation Index (EVI and the Shortwave Infrared Water Stress Index (SIWSI have previously shown promise as predictors of primary production in several different environments. In this study, we evaluate NDVI, EVI and SIWSI derived from the Moderate Resolution Imaging Spectroradiometer (MODIS satellite sensor against in-situ measurements from central Sudan in order to asses their applicability in LUE-based primary production modeling within a water limited environment. Results show a strong correlation between vegetation indices and gross primary production (GPP, demonstrating the significance of vegetation indices for deriving information on primary production with relatively high accuracy at similar areas. Evaluation of SIWSI however, reveal that the fraction of vegetation apparently is to low for the index to provide accurate information on canopy water content, indicating that the use of SIWSI as a predictor of water stress in satellite data-driven primary production modeling in similar semi-arid ecosystems is limited.

  2. The influence of seasonal rainfall upon Sahel vegetation

    DEFF Research Database (Denmark)

    Proud, Simon Richard; Rasmussen, Laura Vang

    2011-01-01

    include changes in total yearly rainfall, land-use change and migration. But these factors are not fully explanatory. This study addresses other possible factors for variation in vegetation patterns through the analysis of the Normalized Difference Vegetation Index (NDVI) produced by satellite sensors. We...... focus on precipitation, but instead of looking at the total yearly amount of rainfall, the intra-annual variation is examined. Here we show that plant growth is strongly correlated with the number and frequency of days within the rainy season upon which there is no rainfall. Furthermore, we find...

  3. Interpretation of Aura satellite observations of CO and aerosol index related to the December 2006 Australia fires

    Directory of Open Access Journals (Sweden)

    N. Livesey

    2009-11-01

    Full Text Available Enhanced Carbon Monoxide (CO in the upper troposphere (UT is shown by collocated Tropospheric Emission Spectrometer (TES and Microwave Limb Sounder (MLS measurements near and down-wind from the known wildfire region of SE Australia from 12–19 December 2006. Enhanced UV aerosol index (AI derived from Ozone Monitoring Instrument (OMI measurements correlate with these high CO concentrations. HYSPLIT model back trajectories trace selected air parcels to the SE Australia fire region as their initial location, where TES observes enhanced CO in the upper and lower troposphere. Simultaneously, they show a lack of vertical advection along their tracks. TES retrieved CO vertical profiles in the higher and lower southern latitudes are examined together with the averaging kernels and show that TES CO retrievals are most sensitive at approximately 300–400 hPa. The enhanced CO observed by TES at the upper (215 hPa and lower (681 hPa troposphere are, therefore, influenced by mid-tropospheric CO. GEOS-Chem model simulations with an 8-day emission inventory, as the wildfire source over Australia, are sampled to the TES/MLS observation times and locations. These simulations only show CO enhancements in the lower troposphere near and down-wind from the wildfire region of SE Australia with drastic underestimates of UT CO. Although CloudSat along-track ice-water content curtains are examined to see whether possible vertical convection events can explain the high UT CO values, sparse observations of collocated Aura CO and CloudSat along-track ice-water content measurements for the single event precludes any conclusive correlation. Vertical convection that uplift fire-induced CO (i.e. most notably referred to as pyro-cumulonimbus, pyroCb may provide an explanation for the incongruence between these simulations and the TES/MLS observations of enhanced CO in the UT. Future GEOS-Chem simulations are needed to validate this conjecture as the the PyroCb mechanism is

  4. Vegetation Change Prediction with Geo-Information Techniques in the Three Gorges Area of China

    Institute of Scientific and Technical Information of China (English)

    M.T.JABBAR; SHI Zhi-Hua; WANG Tian-Wei; CAI Chong-Fa

    2006-01-01

    A computerized parametric methodology was applied to monitor, map, and estimate vegetation change in combination with "3S" (RS-remote sensing, GIS-geographic information systems, and GPS-global positioning system) technology and change detection techniques at a 1:50 000 mapping scale in the Letianxi Watershed of western Hubei Province, China.Satellite images (Landsat TM 1997 and Landsat ETM 2002) and thematic maps were used to provide comprehensive views of surface conditions such as vegetation cover and land use change. With ER Mapper and ERDAS software, the normalized difference vegetation index (NDVI) was computed and then classified into six vegetation density classes. ARC/INFO and ArcView software were used along with field observation data by GPS for analysis. Results obtained using spatial analysis methods showed that NDVI was a valuable first cut indicator for vegetation and land use systems. A regression analysis revealed that NDVI explained 94.5% of the variations for vegetation cover in the largest vegetation area, indicating that the relationship between vegetation and NDVI was not a simple linear process. Vegetation cover increased in four of areas.This meant 60.9% of land area had very slight to slight vegetation change, while 39.1% had moderate to severe vegetation change. Thus, the study area, in general, was exposed to a high risk of vegetation cover change.

  5. The relationship of hyper-spectral vegetation indices with leaf area index (LAI) over the growth cycle of wheat and chickpea at 3 nm spectral resolution

    Science.gov (United States)

    Gupta, R. K.; Vijayan, D.; Prasad, T. S.

    2006-01-01

    Hyperspectral ratio and normalized difference vegetation indices were computed from the 3 nm bandwidth ground-based spectral data taken in 400-950 nm wave length region over the crop growth cycle (CGC) of wheat and chickpea. Synthesized broad band Landsat TM-RVI, TM-NDVI and TM-SAVI were also computed using this narrow bandwidth spectral observations. Regression analysis was carried out for these indices with leaf area index (LAI) for wheat and chickpea over CGC and the r2 values were found poor in 0.2-0.53 range for wheat and in 0.41-0.82 range for chickpea. Significant relationship with LAI were found for wheat ( r2 in 0.86-0.97 range) when growth and decline phases were analyzed independently. Here, r2 values for chickpea were less than that for wheat. The high difference in rate of change of slope for hRVI is a good discriminator for high ET (wheat) and low ET (chickpea) crops. To find out the potential hyperspectral ratios and normalized difference indices that could provide strong relationship with LAI, a correlation-based analysis was carried out for LAI with all the possible combinations of ratios and normalized difference indices in 400-950 nm region (at 3 nm spectral interval) independently for growth and decline phases of LAI and found that in addition to traditional near-IR and red pairs, the pairs within near-IR, near-IR and visible extending to near-IR were also significantly related to LAI.

  6. 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.

  7. 基于光谱分析与角度斜率指数的植被含水量研究%The Research of Vegetation Water Content Based on Spectrum Analysis and Angle Slope Index

    Institute of Scientific and Technical Information of China (English)

    邓兵; 杨武年; 慕楠; 张超

    2016-01-01

    植被含水量是植被生长状态的重要指示因子,是农业、生态和水文等研究中的重要参数,其诊断对于监测自然植被群落的干旱状况、预报森林火灾等都具有重要意义。通过对植被光谱反射率与植被含水量的相关性分析,发现植被波谱不同波段的光谱反射率与植被含水量的相关性差异很大,其中可见光红光波段(620~700 nm)、近红外波段(800~1350,1600~1950,2200~2400 nm)的光谱反射率与植被含水量具有较好的相关性,选取了660,850,1630和2200 nm 的光谱反射率作为 RED,NIR,SWIR1和 SWIR2的波段值来建立角度斜率指数;分析了植被含水量与角度斜率指数的关系,将角度斜率指数(SANI,SASI, ANIR)作为反演植被含水量的参量,建立植被含水量与角度斜率指数之间线性回归模型。通过对近红外角度指数 ANIR 改进,提出了近红外角度归一化指数 NANI(near infrared angle normalized index)与近红外角度斜率指数 NASI(near infrared angle slope index),建立植被含水量与 NANI 和 NASI 之间线性回归模型,结果显示:NANI 与 Palacios-Orueta 等提出的角度斜率指数(SANI,SASI,ANIR)相比有一定的优势,模型可决系数 R 2从原最高0.791提高到0.853,RMSE 也从原最小0.047降低到0.039。确定了 NANI 为反演植被含水量的最佳角度斜率指数,并建立了植被含水量反演模型。该研究主要创新点:在前人研究成果基础上,通过对原角度斜率指数的改进,提出了 NANI 和 NASI 角度斜率指数,使其在植被含水量反演上具有更高的精度。%Vegetation water content is an important indicator of vegetal state,and a vital parameter of studying agriculture,eco-logical and hydrological.The diagnosis of vegetation water content has great significance for forest fire forecast and natural vege-tation drought condition monitoring.The correlation analysis of the vegetation spectral reflectance and vegetation water content

  8. Evaluation of MODIS NDVI and NDWI for vegetation drought monitoring using Oklahoma Mesonet soil moisture data

    Science.gov (United States)

    Gu, Y.; Hunt, E.; Wardlow, B.; Basara, J.B.; Brown, J.F.; Verdin, J.P.

    2008-01-01

    The evaluation of the relationship between satellite-derived vegetation indices (normalized difference vegetation index and normalized difference water index) and soil moisture improves our understanding of how these indices respond to soil moisture fluctuations. Soil moisture deficits are ultimately tied to drought stress on plants. The diverse terrain and climate of Oklahoma, the extensive soil moisture network of the Oklahoma Mesonet, and satellite-derived indices from the Moderate Resolution Imaging Spectroradiometer (MODIS) provided an opportunity to study correlations between soil moisture and vegetation indices over the 2002-2006 growing seasons. Results showed that the correlation between both indices and the fractional water index (FWI) was highly dependent on land cover heterogeneity and soil type. Sites surrounded by relatively homogeneous vegetation cover with silt loam soils had the highest correlation between the FWI and both vegetation-related indices (r???0.73), while sites with heterogeneous vegetation cover and loam soils had the lowest correlation (r???0.22). Copyright 2008 by the American Geophysical Union.

  9. Composition, peat-forming vegetation and kerogen paraffinicity of Cenozoic coals: Relationship to variations in the petroleum generation potential (Hydrogen Index)

    Energy Technology Data Exchange (ETDEWEB)

    Petersen, H.I.; Lindstroem, S.; Nytoft, H.P.; Rosenberg, P. [Geological Survey of Denmark and Greenland (GEUS), Oester Voldgade 10, DK-1350 Copenhagen (Denmark)

    2009-04-01

    Coals with similar thermal maturity and from the same deposit normally show a considerable range in petroleum generation potential as measured by the Hydrogen Index (HI). This variation may partly be related to variations in plant input to the precursor mires and organic matter preservation. It is widely accepted that some Cenozoic coals and coaly sediments have the potential to generate oil, which is related to the coal's paraffinicity. Coal paraffinicity is not readily reflected in the bulk HI. In this paper, the relationships between measured HI and coal composition, coal kerogen paraffinicity and floral input have been investigated in detail for three sets of coals from Colombia/Venezuela, Indonesia, and Vietnam. The samples in each coal set are largely of iso-rank. The petroleum generation potential was determined by Rock-Eval pyrolysis. Reflected light microscopy was used to analyse the organic matter (maceral) composition and the thermal maturity was determined by vitrinite reflectance (VR) measurements. The botanical affinity of pollen and spores was analysed by palynology. Coal kerogen paraffinicity was determined by ruthenium tetroxide-catalysed oxidation (RTCO) followed by chain length analysis and quantification (mg/g TOC) of the liberated aliphatic chains. The coals are dominated by huminite, in particular detrohuminite. Only the Vietnamese coals are rich in microscopically visible liptinite. The pollen and spores suggest that the coals were derived principally from complex angiosperm mire vegetations, with subordinate proportions of ferns that generally grew in a subtropical to tropical climate. Measured HI values vary considerably, but for the majority of the coals the values lie between approximately 200 mg HC/g TOC and 300 mg HC/g TOC. Aliphatics yielding monocarboxylic acids dominate in the coal kerogen, whereas aliphatics yielding dicarboxylic acids are secondary. However, the dicarboxylic acids show that cross-linking long-chain aliphatics

  10. A probabilistic assessment of the likelihood of vegetation drought under varying climate conditions across China.

    Science.gov (United States)

    Liu, Zhiyong; Li, Chao; Zhou, Ping; Chen, Xiuzhi

    2016-10-07

    Climate change significantly impacts the vegetation growth and terrestrial ecosystems. Using satellite remote sensing observations, here we focus on investigating vegetation dynamics and the likelihood of vegetation-related drought under varying climate conditions across China. We first compare temporal trends of Normalized Difference Vegetation Index (NDVI) and climatic variables over China. We find that in fact there is no significant change in vegetation over the cold regions where warming is significant. Then, we propose a joint probability model to estimate the likelihood of vegetation-related drought conditioned on different precipitation/temperature scenarios in growing season across China. To the best of our knowledge, this study is the first to examine the vegetation-related drought risk over China from a perspective based on joint probability. Our results demonstrate risk patterns of vegetation-related drought under both low and high precipitation/temperature conditions. We further identify the variations in vegetation-related drought risk under different climate conditions and the sensitivity of drought risk to climate variability. These findings pro