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

  • 摘要: 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.

     

    Abstract: 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 Hpolarization.In this study,we use the advanced integrale-quation 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.

     

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