卫星遥感反演土壤水分研究综述  

Satellite Retrieval of Soil Moisture:An Overview

作　　者：陈书林[1,2] 刘元波[2] 温作民[1] 

机构地区：[1]南京林业大学经济管理学院,江苏南京210037 [2]中国科学院南京地理与湖泊研究所,江苏南京210008

出　　处：《地球科学进展》2012年第11期1192-1203,共12页Advances in Earth Science

基　　金：国家重点基础研究发展计划项目"长江中游通江湖泊江湖关系演变及环境生态效应与调控"(编号:2012CB417003);国家引进国际先进农业科学技术计划项目"森林生态系统适应性管理模式与技术标准引进"(编号:2009-4-44);南京林业大学科技创新基金项目"基于遥感的森林植被水文效应监测模型研究"(编号:163060077)资助

摘　　要：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。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） u

关 键 词：土壤水分反演算法 光学遥感 微波遥感 多传感器联合反演 全球数据集 

分 类 号：TP751.1[自动化与计算机技术—检测技术与自动化装置]