卫星遥感反演土壤水分研究综述

土壤水分是影响地表过程的核心变量之一。精准地测量土壤水分及其时空分布,长期以来是定量遥感研究领域的难点问题。简要回顾基于光学、被动微波、主动微波和多传感器联合反演等卫星遥感反演土壤水分的主要反演算法、存在的难点和前沿性研究问题,介绍了应用土壤水分反演算法所形成的3种主要全球土壤水分数据集,包括欧洲气象业务卫星（ERS/MetOp）数据集、高级微波扫描辐射计（AMSR-E）数据集、土壤湿度与海洋盐分卫星（SMOS）数据集,并结合目前存在的问题探讨卫星遥感反演土壤水分研究的发展趋势。

Satellite Retrieval of Soil Moisture:An Overview

Soil moisture is a key variable influencing a variety of land surface processes. Accurate estimation of spatio-temporally distributed soil moisture is one of the challenging issues in quantitative remote sensing. This paper briefly describes the major algorithms for retrieving soil moisture using optical, passive-microwave and active-microwave remote sensing, or their combinations. The optical algorithms have relatively low accuracy of retrieval, but good spatial and temporal resolutions. The typical algorithms include the Index-based approach and the soil thermal inertia-based approach. The passive-microwave algorithms have relative high accuracy but low spatial resolutions. It can be grouped into the retrieval approaches for soil moisture only and the approaches for relevant parameters in addition to soil moisture. The active-microwave algorithms have generally high accuracy with a high spatial resolution. The algorithms can be divided into three classes: empirical, physical and semi-empirical approaches. In addition, a number of algorithms have been proposed, which combines in particular optical, passive microwave, or active-microwave data. Because the algorithms often combine the advantages of the multi-sensors, they can achieve a high accuracy with a good spatial resolution. With the achievement of retrieval techniques, several global soil moisture data sets have been generated. The widely used data sets include the European Remote Sensing satellites/ Meteorological Operational satellite programme (ERS/MetOp) data sets, the Advanced Microwave Scanning Radiometer for EOS (AMSR-E) data sets, and the Soil Moisture and Ocean Salinity (SMOS) data sets. The ERS/MetOp data sets provides global soil moisture data with a spatial resolution of 25-km so far since July, 1991, retrieved from the TU-Wien approach using C-band microwave data. The AMSR-E data sets provides global soil moisture data with a spatial resolution of 25-km for the period from June, 2002 to September, 2011, retrieved from the Land Parameter Retrieval Model (LPRM) using C-band and X-band microwave data. The SMOS data sets provides global soil moisture data with a spatial resolution of 40-km so far since November, 2009, retrieved from the L-band Microwave Emission of the Biosphere model (L MEB) using L-band microwave data. To improve retrieval accuracy of soil moisture, the new satellite sensors are scheduled to be launched into space, for example, the Phased Array type L-band Synthetic Aperture Radar-2 (PALSAR 2) in 2013 and the Soil Moisture Active Passive (SMAP) in 2014.