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利用TRMM/TMI资料提取地表层湿度信息试验
引用本文:谷松岩,李万彪,张文建.利用TRMM/TMI资料提取地表层湿度信息试验[J].遥感学报,2005,9(2):166-175.
作者姓名:谷松岩  李万彪  张文建
作者单位:1. 北京大学,物理学院大气科学系,北京,100871;国家卫星气象中心,北京,100081
2. 北京大学,物理学院大气科学系,北京,100871
3. 国家卫星气象中心,北京,100081
基金项目:国家自然科学基金(2001CB309402)、(90102010)和(40305003)共同资助
摘    要:模拟分析了地表层湿度反演过程中地表及大气各种因素(卫星扫描角、地表粗糙度、地表植被覆盖和大气)对反演结果的影响情况;应用正演模拟技术得到了利用TMI低频10GHz通道微波极化比反演地表层湿度信息时,斜率和截距随像元植被覆盖度可调的反演方程;确定了反演方程中斜率、截距系数随像元植被覆盖度变化的对数关系和线性关系;反演技术中综合应用了多种途径获取到的被动微波像元中动态的植被覆盖信息;尝试了将这些因子用于地表层湿度反演的可行性;对于反演结果,研究工作中利用地表HUBEX外场观测资料进行了对比分析,得到了空间分布特征和时间演变趋势比较一致的对比分析结果。

关 键 词:被动微波  正演模拟  地表层湿度  遥感反演
文章编号:1007-4619(2005)02-0166-10
修稿时间:2003年8月11日

Retrieving Soil Moisture from TRMM/TMI
GU Song-yan,LI Wan-biao and ZHANG Wen-jian.Retrieving Soil Moisture from TRMM/TMI[J].Journal of Remote Sensing,2005,9(2):166-175.
Authors:GU Song-yan  LI Wan-biao and ZHANG Wen-jian
Institution:Atmospheric Department,School of Physics,Peking University,Beijing 100871,China;National Satellite Meteorology Center,Beijing 100081,China;Atmospheric Department,School of Physics,Peking University,Beijing 100871,China;National Satellite Meteorology Center,Beijing 100081,China
Abstract:Remote sensing of soil moisture by microwave radiometry has been a subject of intensive studies in the past two decades. Following the studies done before, a new approach to retrieve surface layer soil moisture is accomplished in this paper, in which the passive microwave data of TRMM/TMI and ground observation data have been used to retrieve surface soil moisture. Surface and atmosphere microwave radiance transfer models have been applied to analyze the effects of surface and atmosphere, e. g. scan angle, surface roughness, and canopy layer. In the retrieval technique for TMI low frequency, variable gain and intercept appeared. Multi-spectrum remote sensing information, surface digital elevation measurement data, and mixed-pixel information were involved. The consistency was obtained between the retrieval results and ground observation or HUBEX IOP data.
Keywords:passive microwave  forward simulation  surface soil moisture remote sensing retrieval
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