This paper evaluated the capacity of SPOT VEGETATION time-series to monitor herbaceous fuel moisture content (FMC) in order to improve fire risk assessment in the savanna ecosystem of Kruger National Park in South Africa. In situ herbaceous FMC data were used to assess the Normalized Difference Vegetation Index (NDVI), Normalized Difference Water Index (NDWI), Vegetation Dryness Index (VDI), Im...

The Normalized Di erence Vegetation Index (NDVI) is widely accepted as a good indicator for providing vegetation properties and associated changes for large scale geographic regions. Using multivariate time series data analysis methods based on Principal Component transform and Wavelet Decomposition, a sequence of 11-year monthly Advanced Very High Resolution Radiometer (AVHRR)-derived NDVI dat...

Global change affects vegetation cover and processes through multiple pathways. Long 1 time series of surface land surface properties derived from satellite remote sensing give unique 2 abilities to observe these changes, particularly in areas with complex topography and limited research 3 infrastructure. Here, we focus on Nepal, a biodiversity hotspot where vegetation productivity is 4 limited...

Crop condition assessment in the early growing stage is essential for crop monitoring and crop yield prediction. A normalized difference vegetation index (NDVI)-based method is employed to evaluate crop condition by inter-annual comparisons of both spatial variability (using NDVI images) and seasonal dynamics (based on crop condition profiles). Since this type of method will generate false info...

Detailed information from global remote sensing has greatly advanced our understanding of Earth as a system in general and of agricultural processes in particular. Vegetation monitoring with global remote sensing systems over long time periods is critical to gain a better understanding of processes related to agricultural change over long time periods. This specifically relates to sub-humid to ...

The objectives of the study are to integrate the conditional Latin Hypercube Sampling (cLHS), sequential Gaussian simulation (SGS) and spatial analysis in remotely sensed images, to monitor the effects of large chronological disturbances on spatial characteristics of landscape changes including spatial heterogeneity and variability. The multiple NDVI images demonstrate that spatial patterns of ...

Species richness generally promotes ecosystem productivity, although the shape of the relationship varies and remains the subject of debate. One reason for this uncertainty lies in the multitude of methodological approaches to sampling biodiversity and productivity, some of which can be subjective. Remote sensing offers new, objective ways of assessing productivity and biodiversity. In this stu...

Under the framework of the soil–wheat system, the sampling area was selected in the demonstration site of Lingxian country of Shandong province, Normalized Difference Vegetation Index (NDVI) of 195 sites were collected by GreenSeeker optical sensor based on the GPS localization data. The main objective of the paper developed the comparison study by Kriging and BPNN algorithm for NDVI continuity...

The Hawaiian Islands are an ideal location to study the response of tropical forests to climate variability because of their extreme isolation in the middle of the Pacific, which makes them especially sensitive to El Niño-Southern Oscillation (ENSO). Most research examining the response of tropical forests to drought or El Niño have focused on rainforests, however, tropical dry forests cover a ...

Vegetation health can be monitored using a time series of remotely sensed images by calculating the Normalized Difference Vegetation Index (NDVI). We assessed temporal trends throughout an NDVI time series with three sensors: Advanced Very High Resolution Radiometer (AVHRR), the Moderate Resolution Imaging Spectroradiometer (MODIS) and Landsat Thematic Mapper/Enhanced Thematic Mapper Plus (TM/E...