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基于微波遥感和陆面模型的流域土壤水分研究
引用本文:李斌,李震,魏小兰.基于微波遥感和陆面模型的流域土壤水分研究[J].遥感信息,2007(5):96-101.
作者姓名:李斌  李震  魏小兰
作者单位:中国科学院遥感应用研究所遥感信息科学重点实验室,北京,100101
基金项目:国家自然科学基金;中国科学院知识创新工程项目
摘    要:土壤水分是陆地水文的重要因子。微波遥感是测量土壤水分的一种重要方法。本文总结了基于微波遥感和陆面模型的土壤水分监测方法,包括被动微波法、主动微波法、主被动微波结合法、陆面模型模拟法和数据同化法五种。被动微波对表面土壤水分敏感,但其空间分辨率低;主动微波具有较好的分辨率但运作费用也较高;主被动微波结合则能够充分利用各自的优势。陆面模型在研究中也有重要作用,通过模型模拟能够得到根区土壤水分。而将观测值同化到模型的数据同化法,则能极大的提高土壤水分估计的能力。通过比较,指出数据同化是最有前景的研究领域。

关 键 词:微波遥感  陆面模型  土壤水分  数据同化
文章编号:1000-3177(2007)93-0096-06
修稿时间:2007-01-262007-03-16

Study on Soil Moisture at River Basin Scale Based on Microwave Remote Sensing and Land Surface Models
LI Bin,LI Zhen,WEI Xiao-lan.Study on Soil Moisture at River Basin Scale Based on Microwave Remote Sensing and Land Surface Models[J].Remote Sensing Information,2007(5):96-101.
Authors:LI Bin  LI Zhen  WEI Xiao-lan
Affiliation:laboratory of Remote Sensing Information Sciences, Chinese Academy of Sciences, Beijing 10010
Abstract:Soil moisture is a highly variable component in land surface hydrology, but it is difficult to gain. The use of microwave remote sensing has demonstrated great potential for measurement of soil moisture.This paper has made a review on different methods based on microwave and land surface models for monitoring soil moisture, which can be classified as passive microwave method, active microwave method, combined active and passive method, model simulation method, and data assimilation method. Passive microwave is sensitive to the surface soil moisture, but the resolution is poor. Active microwave has higher resolution, but it costs too much. Combined passive and active microwave remote sensing can fully utilize the two kinds of data. Surface models are also useful tools. Simulations by land surface models has strong ability to get profile soil moisture and data assimilation, which is a way of integrating observations with model simulation results, can significantly improve the soil moisture estimation in the surface layer and the root zone. By comparing all of these methods, we believe that data assimilation is the most promising avenue for research.
Keywords:microwave remote sensing  land surface models  soil moisture  data assimilation
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