Study of the desertification index based on the albedo-MSAVI feature space for semi-arid steppe region

Abstract

Desertification has been listed as the top of ten major problems affecting global environmental changes, and represents one of the important reasons of semi-arid grassland degradation. It is therefore crucial to understand ecological environment of semi-arid grasslands and temporal and spatial changes in real time for regional and local environmental protection and management. At present, remote sensing technology is being widely used in monitoring and evaluation of land desertification due to its wide observation range, large amount of information, fast data updating and high accuracy. It represents an advanced method for remote sensing monitoring of desertification by extracting various indicators and constructing feature space. Based on this, this study used Landsat images and field survey data to establish a desertification index (SASDI) model based on the albedo-MSAVI (Modified Soil Adjusted Vegetation Index) feature space and analyze the relationship between desertification and surface quantitative parameters in semi-arid grassland area. Results show that the SASDI model has a high correlation (R2 = 0.7585) with the organic matter in the soil surface and makes full use of multi-dimensional remote sensing information. The index reflects the surface cover, water, and heat combination as well as changes of the desertification land, with a clear biophysical significance. Moreover, the index is simple and easy to obtain, facilitating to quantitative analysis and continuous monitoring of desertification in semi-arid grasslands.