基于沙地植被指数的荒漠化评价方法

混合像元是影响基于遥感技术的荒漠化评价精度的主要原因。本研究通过光谱混合分析技术进行了亚像元尺度上荒漠化信息提取,并在深入研究荒漠化评价指标的基础上,利用所提取的农田信息与沙生植被信息构建了用于荒漠化评价的沙地植被指数,并与常用植被归一化指数进行比较。结果表明,沙地植被指数对荒漠化地区植被探测能力明显优于植被归一化指数,更适合于区分不同程度的荒漠化土地。对毛乌素沙地评价结果表明,毛乌素沙地荒漠化十分严重。

Desertification Evaluation Based on Sand Vegetation Index

Mixed pixel is the major cause which leads to the low accuracy of desertification evaluation based on remote sensing.In this study,desertification information is extracted at the sub-pixel scale.A desertification evaluation index,sand vegetation index(SVI),is constructed using extracted farmland information and psammophytic vegetation information based on in-depth study of the desertification evaluation indexes.The vegetation detection capability of SVI is better than that of the commonly used vegetation index NDVI in desertified areas,and SVI is particularly suited for distinguishing different levels of desertification lands.Evaluation result shows that desertification in Mu Us Sandy Land is very serious.