植被覆盖地区AMSR-E反演土壤水分算法研究
王磊[1,2] 李震[1] 陈权[1,2]
[1]中国科学院研究生院,北京100049 [2]中国科学院遥感应用研究所遥感信息科学国家重点实验室,北京100101
摘 要:
在已有基于微波辐射传输模型的反演算法基础上,对2003年中国5种地区的AMSR-E观测数据进行了比较分析,引入了微波极化差异指数(MPDl)概念,提出了一种自动区分地面植被覆盖情况的方法。使用这种方法,反演过程中无需地面土地利用分类的辅助数据,同时在对有植被覆盖地区消除植被层的影响的过程中,改进了Richard提出的计算植被消光系数的方程,提高了反演应用中的运算效率。最后给出了AMSR-E反演土壤水分的工作流程,并对反演结果进行了分析。[著者文摘]

文章出处:
《高技术通讯》-2006年16卷2期 -204-209页
栏目信息:
Soil moisture retrieval with AMSR-E in the region with vegetation coverage
Wang Lei, Li Zhen,Chen Quan(1.Graduate School of Chinese Academy of Science, Beijing 100049;2. Laboratory of Remote Sensing Information Sciences, Institute of Remote Sensing Applications, CAS, Beijing 100101)
Abstract:
Based on the theoretical soil moisture retrieval model, the paper analyses the AMSR-E data acquired at 5 example fields in China, 2003, and gives out a method to classify vegetation coverage condition automatically with the Microwave Polarization Difference Index (MPDI), which works without ancillary data about vegetation information. This paper also develops the function to compute vegetation opacity with MDPI, which is put forward by Richard, and improves the efficiency of the retrieval. This paper also gives out the flow chart of the soil moisture retrieval with AMSR-E, and analyzes the retrieval results.[著者文摘]
Key words:
AMSR-E, land parameters, soil moisture, opacity depth, MPDI
基金资助:
863计划(2003AA131053)和KGW资助项目.致谢:文中所用AMSR-E数据由美国国家雪冰数据中心(National Snow and Ice Data Center)提供,谨致谢意.

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