The microwave remote sensing has long been considered as an important technique to determine and quantify the state and amount of soil moisture. With the improved knowledge of land-air interaction and the advance of sensor technology, using microwave remote sensing to estimate the soil moisture has achieved a practical level. In this paper, we compare and evaluate four soil moisture retrieval algorithms developed by Jackson , Liou et al. , Macelloni et al.  and Paloscia et al. . Data used to analyze the performance of these retrieval algorithms includes TRMM-TMI data acquired in 1998 and 2001, and AMSR-E data taken in July 2006. The result indicates that the soil moisture retrieval algorithm developed by Liou et al.  has better correlation and less bias as compared with the in situ measurement. The Liou model is further applied to study the spatial variability of the soil moisture in the Tibetan Plateau and has achieved a promising result. In future, we attempt to further refine the Liou model for global soil moisture study.