土壤湿度是陆表极其重要的参数之一，对全球水循环、能量平衡、以及气候变化有着重大影响。研究基于雷达植被指数发展有效消除植被影响的SMAP/Aquarius土壤湿度反演算法，改进与提高FY-3土壤湿度算法与产品精度。 （1）建立雷达植被指数与植被含水量和植被透过率之间的关系，发展有效消除植被的主被动联合土壤湿度反演算法；（2）利用SMAP/Aquarius高精度的土壤湿度和植被参数信息改进与提高FY-3卫星土壤湿度算法与产品精度。实现全球中尺度土壤湿度的长时间序列可靠反演，提升土壤湿度产品在气象和干旱监测中的应用。

Soil Moisture is one of important parameters in land surface, and have an important influence on global water cycle, energy balance and climate change. Research on vegetation correction method base on radar vegetation index, develop an effective method to elimate vegetation effects for retrieving SMAP/Aquarius soil moisture, and improve the precision of FY-3 soil moisture algorithm and products accuracy.（1）Establish a clear mathematical relationship between the radar vegetation index (RVI) and vegetation water content/vegetation transmissivity, and develop a soil moisture inversion algorithm for the vegetation correction combined the radar and radiometer observations;（2）Improve FY-3 soil moisture algorithm and products accuracy using SMAP/Aquarius high precision of soil moisture and vegetation parameters. Realization of long time series of global scale soil moisture reliable retrieval, improve soil moisture application in the meteorological and monitoring of drought.