Quantitative Assessment of Vegetation Coverage Factor in USLE Model Using Remote Sensing Data

Abstract

Vegetation coverage represents an important role in lessening soil loss, protecting environment and improving the standard of living. USLE, as a convenient model, is applied widely. The studies mainly on method extracting vegetation coverage by using spatial and temporal remote sensing data. As a result of mixing pixels, there is something itself shortcoming for the technique of NDVI monitoring vegetation coverage, and it needs much manpower and time for field sampling. Linear spectral unmixing is a simpler way reducing workload and improving accuracy of extracting vegetation coverage in remote sensing image. It need not field sampling and regressive analysis. The value extent of vegetation coverage factor C in USLE model lies between 0 and 1, but the value changed greatly. So the precision of C value is a key to USLE model.