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基于物理模型的被动微波遥感反演土壤水分
Physically based retrieval of soil moisture using passive microwave remote sensing

查看参考文献15篇

陈亮 1   施建成 1   蒋玲梅 2   杜今阳 1  
文摘 利用土壤水分和海洋盐度(SMOS)卫星进行土壤水分反演的算法中, 对地表发射率的描述仍采用半经验Q/H模型,该模型描述地表粗糙度对有效发射率在V和H极化下影响相同.基于微波散射理论模型-高级积分方程模型(AIEM)建立了一个针对SMOS传感器的参数配置, 包含各种地表粗糙度和介电特性的裸露地表辐射模拟数据库, 发展了L波段多角度地表辐射参数化模型.在此基础上, 利用SMOS多角度双极化特点, 建立了土壤水分反演算法.该算法可以消除粗糙度对土壤水分反演的影响, 同时最小化反演过程中辅助信息引入带来影响.反演算法通过美国农业部提供的L波段多角度地基辐射计数据(BARC)进行验证, 在20°~50°入射角,土壤水分反演精度在4% 左右.
其他语种文摘 The soil moisture inversion algorithm,which is adopted in the soil moisture and ocean salinity(SMOS) mission,uses the semi-empirical Q/H model to figure out the surface emissivity.The Q/H model shows the effects of the surface roughness on the emissivity at V polarization are same as that of H polarization.In this study,we use the advanced integral equation model to generate a simulated database with a wide range of the surface roughness and soil moisture conditions under SMOS sensor configurations and develop a simplified multi-angular surface emission model based on the simulated database.Based on the parameterized model,an inversion procedure is set up in terms of dual-polarization microwave brightness temperatures to retrieve soil moisture with the minimum auxiliary information about the ground.The inversion technique is validated with multi-angular ground microwave radiometer experiment data at L-band from several test sites at Beltsville,MD.The accuracy in random-mean-square error is about 4% at inciden angles of 20°~50°.The results reveal that the proposed inversion procedure decreases the perturbing effects of the surface roughness on the soil moisture estimation.
来源 水科学进展 ,2009,20(5):663-667 【核心库】
关键词 物理模型 ; 微波遥感 ; 土壤水分 ; L波段 ; 多角度
地址

1. 中国科学院遥感应用研究所, 北京, 100101  

2. 北京师范大学地理学与遥感科学学院, 北京, 100875

语种 中文
文献类型 研究性论文
ISSN 1001-6791
学科 地球物理学
基金 国家863计划
文献收藏号 CSCD:3689062

参考文献 共 15 共1页

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引证文献 5

1 田辉 主动微波遥感黄河上游玛曲地区夏季土壤水分 水科学进展,2011,22(1):59-66
被引 8

2 何媛 卫星微波遥感结合可见光遥感估算黄河源区土壤湿度研究 遥感技术与应用,2013,28(2):300-308
被引 7

显示所有5篇文献

论文科学数据集

1. 基于风云卫星FY-3B微波成像仪MWRI数据的全球日尺度土壤水分数据集(2010-2019)

2. 黑河综合遥感联合试验:扁都口加密观测区Envisat ASAR地面同步观测数据集(2008年3月14日)

3. 黑河综合遥感联合试验:阿柔加密观测区Envisat ASAR地面同步观测数据集(2008年7月14日)

数据来源:
国家青藏高原科学数据中心
PlumX Metrics
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