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Assessment of Multi-Spectral Vegetation Indices Using Remote Sensing and Grid Computing

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Executive Summary

A primary goal of many remote sensing projects is to characterize the type, size and condition of vegetation present within a region. By combining data from two or more spectral bands the authors obtain what is commonly known as a Vegetation Index (VI), which enhances the vegetation signal, while minimizing solar irradiance and soil background effects. This paper addresses the computation of Normalized Difference Vegetation Index (NDVI), Ratio Vegetation Index (RVI), Enhanced Vegetation Index (EVI), Atmospherically Resistant Vegetation Index (ARVI), Normalized Difference Snow Index (NDSI) and Normalized Burn Ratio (NBR) based on satellite imagery.

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