A comparison on the soil moisture retrieval algorithms by using passive microwave remote sensing data

Microwave radiometry remote sensing has been considered as a major technique to determine and quantify the state and amount of soil moisture. In this paper, we compare and evaluate four soil moisture retrieval algorithms developed by Jackson (1993), Liou et al. (1999), Macelloni et al. (2000) and Paloscia et al. (2001). 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. (1999) has better correlation and less bias as compared with the in situ measurements. 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 will attempt to further refine the Liou model for global soil moisture study.