Search results for "DIFFERENCE VEGETATION INDEX"
showing 10 items of 141 documents
Analysis of winter dust activity off the coast of West Africa using a new 24-year over-water advanced very high resolution radiometer satellite dust …
2006
A 24-year (1982-2005) winter daytime advanced very high resolution radiometer (AVHRR) data set has been processed utilizing a new over-water dust detection algorithm. The dust data are for the oceanic regions surrounding West Africa and provide a long-term remotely sensed continuous record of dustiness in the region. These AVHRR dust observations are comparable to dust records produced via the Total Ozone Mapping Spectrometer and Meteosat instruments. Strong positive correlations between the wintertime Jones North Atlantic Oscillation index and this dust record are observed across the entire oceanic region, corroborating earlier studies on the relationship between the two. Also consistent w…
Integrated remote sensing approach to global agricultural drought monitoring
2018
Abstract This study explores the use of the Soil Moisture Agricultural Drought Index (SMADI) as a global estimator of agricultural drought. Previous research presented SMADI as a novel index based on the joint use of remotely sensed datasets of land surface temperature (LST) and normalized difference vegetation index (NDVI) from the Moderate Resolution Imaging Spectroradiometer (MODIS) together with the surface soil moisture (SSM) from the Soil Moisture and Ocean Salinity (SMOS) mission. This study presents the results of applying SMADI at the global scale with a spatial resolution of 0.05° every 15 days. The period of the study spanned from 2010 to 2015. Three spatial scales (local, region…
Trend Analysis of Global MODIS-Terra Vegetation Indices and Land Surface Temperature Between 2000 and 2011
2013
Previous works have shown that the combination of vegetation indices with land surface temperature (LST) improves the analysis of vegetation changes. Here, global MODIS-Terra monthly data from 2000 to 2011 were downloaded and organized into LST, NDVI (Normalized Difference Vegetation Index) and EVI (Enhanced Vegetation Index) time series. These time series were then corrected from cloud and atmospheric residual contamination through the IDR (iterative Interpolation for Data Reconstruction) method. Then, statistics were retrieved from both corrected time series, and the YLCD (Yearly Land Cover Dynamics) approach has been applied to data sources (NDVI-LST and EVI-LST) to analyze changes in th…
Comparative study of three satellite image time-series decomposition methods for vegetation change detection
2018
International audience; Satellite image time-series (SITS) methods have contributed notably to detection of global change over the last decades, for instance by tracking vegetation changes. Compared with multi-temporal change detection methods, temporally highly resolved SITS methods provide more information in a single analysis, for instance on the type and consistency of change. In particular, SITS decomposition methods show a great potential in extracting various components from non-stationary time series, which allows for an improved interpretation of the temporal variability. Even though many case studies have applied SITS decomposition methods, a systematic comparison of common algori…
Accelerated Changes of Environmental Conditions on the Tibetan Plateau Caused by Climate Change
2011
Abstract Variations of land surface parameters over the Tibetan Plateau have great importance on local energy and water cycles, the Asian monsoon, and climate change studies. In this paper, the NOAA/NASA Pathfinder Advanced Very High Resolution Radiometer (AVHRR) Land (PAL) dataset is used to retrieve the land surface temperature (LST), the normalized difference vegetation index (NDVI), and albedo, from 1982 to 2000. Simultaneously, meteorological parameters and land surface heat fluxes are acquired from the 40-yr European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERA-40) dataset and the Global Land Data Assimilation System (GLDAS), respectively. Results show that from …
Landsat TM/ETM+ and tree-ring based assessment of spatiotemporal patterns of the autumnal moth (Epirrita autumnata) in northernmost Fennoscandia
2010
Abstract We used fine-spatial resolution remotely sensed data combined with tree-ring parameters in order to assess and reconstruct disturbances in mountain birch ( Betula pubescens ) forests caused by Epirrita autumnata (autumnal moth). Research was conducted in the area of Lake Tornetrask in northern Sweden where we utilized five proxy parameters to detect insect outbreak events over the 19th and 20th centuries. Digital change detection was applied on three pairs of multi-temporal NDVI images from Landsat TM/ETM+ to detect significant reductions in the photosynthetic activity of forested areas during disturbed growing seasons. An image segmentation gap-fill procedure was developed in orde…
Monitoring barley and corn growth from remote sensing data at field scale
2004
Vegetation indices have been used for operational quantitative monitoring of vegetation. Here, corn and barley cultures have been used to relate meaningful biophysical parameters such as dry biomass and Crop Growth Rate (CGR) to the well-established Normalized Difference Vegetation Index (NDVI). We explain these relationships by means of the use of the Light Use Efficiency (LUE) models, based on the positive relation between primary production and Absorbed Photosynthetically Active Radiation (APAR). In these models we introduce NDVI as a linear estimator of f APAR. Experimental data over corn and barley show that dry biomass is linearly related to the Time-Integrated Value of the NDVI (TIND…
Global Scale IB AMSR2 Vegetation Optical Depth at X-Band
2021
Vegetation Optical Depth (VOD) plays an increasingly important role in studying global carbon, water and energy transformation [1], [2]. This study explores the performance of the X-MEB (X-band microwave emission of the biosphere) model at global scale. Similar to the L-MEB model, the X-MEB model, built by INRAE (Institut national de recherche pour l'agriculture, l'alimentation et l'environnement) Bordeaux, aims to retrieve VOD (referred to as IB X-VOD) at X-band. To avoid the ill-posed problem caused by retrieving two parameters of interest (soil moisture (SM) and VOD) from mono-angular and dual-polarized observations (AMSR2), which are strongly correlated, we used the ERA5 SM product as a…
Validation of a mapping and prediction model for human fasciolosis transmission in Andean very high altitude endemic areas using remote sensing data.
2001
The present paper aims to validate the usefulness of the Normalized Difference Vegetation Index (NDVI) obtained by satellite remote sensing for the development of local maps of risk and for prediction of human fasciolosis in the Northern Bolivian Altiplano. The endemic area, which is located at very high altitudes (3800-4100 m) between Lake Titicaca and the valley of the city of La Paz, presents the highest prevalences and intensities of fasciolosis known in humans. NDVI images of 1.1 km resolution from the Advanced Very High Resolution Radiometer (AVHRR) sensor on board the National Oceanic and Atmospheric Administration (NOAA) series of environmental satellites appear to provide adequate …
A generalized soil-adjusted vegetation index
2002
Operational monitoring of vegetative cover by remote sensing currently involves the utilisation of vegetation indices (VIs), most of them being functions of the reflectance in red (R) and near-infrared (NIR) spectral bands. A generalized soil-adjusted vegetation index (GESAVI), theoretically based on a simple vegetation canopy model, is introduced. It is defined in terms of the soil line parameters (A and B) as: GESAVI=(NIRBRA)/(R+Z), where Z is related to the red reflectance at the cross point between the soil line and vegetation isolines. As Z is a soil adjustment coefficient, this new index can be considered as belonging to the SAVI family. In order to analyze the GESAVI sensitivity to s…