大尺度上的土壤水分变化监测对于建立全球的水循环模型意义重大，是实现气候变化预测和洪涝监测的基础。星载辐射计为实现大尺度上土壤水分的监测提供了监测途径。但是在星载辐射计观测时，地表植被层的吸收和散射作用会对土壤向上的微波辐射产生衰减影响，这种影响在反演土壤水分的过程中必须予以计算和消除。原有的反演算法中，在计算这部分影响的时候，需要大量的关于地表植被状况的辅助数据，而这些即时的辅助数据往往不易获得。以AMSR—E数据为例，研究证明了微波极化差异指数（MPDI）能够反映地表植被覆盖状况。以中国华北、华东地区为实验区，选择2004年4月8日的AMSR—E亮温数据和MODIS数据为样本数据，建立起MPDI与NDVI之间的负指数关系方程。基于对NDVI的认识，得到植被覆盖度高、中、低三种状况所对应的MPDI域值，以此域值为依据对中等植被覆盖度地区作出自动判断，并用MPDI计算植被层不透明度。

Monitoring the soil moisture variety in large-scale is very important to establishing the global water-cycle model,and to forecasting the weather and the floods.The spaceborne microwave radiometer is an efficient way to monitor the soil moisture variety in large-scale.When the radiometer observes the earth from the space,the absorbing and the scattering affection in the vegetation layer will attenuate the up-forward radiance from the soil,and this affection must be counted and reduced during the process of soil moisture retrieval.Much ancillary data are needed for computing the attenuating effects of the vegetation layer in the soil moisture retrieval model before,and the ancillary data are often unavailable.This paper proves that the Microwave Polarization Difference Index(MPDI) can be used to indicate the vegetation coverage conditions with the AMSR-E L2A brightness temperature data product.In this paper,we select the north-east and east part of China as the experiment area and the AMSR-E L2A brightness temperature and MODIS data as the sample data,and get the negative exponent relationship between MPDI and NDVI.Based on the relationship function and the knowledge about NDVI,MPDI has three threshold values that stand for High,Medium and Low vegetation coverage level.The threshold values can be used in the process of the soil moisture retrieval to judge the vegetation coverage level at the observed point and work out vegetation opacity.