Zhang, Tao等:Soil temperature independent algorithm for estimating bare surface soil moisture
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Soil temperature independent algorithm for estimating bare surface soil moisture
作者:Zhang, T (Zhang, Tao)[ 1,2 ] ; Jiang, LM (Jiang, Lingmei)[ 1,2 ] ; Zhao, TJ (Zhao, Tianjie)[ 3 ] ; Li, YQ (Li, Yunqing)[ 3,4 ] ; Zhang, ZJ (Zhang, Zhongjun)[ 5 ]
卷: 8
文献号: 083558
DOI: 10.1117/1.JRS.8.083558
出版年: SEP 3 2014
In this study, a bare surface soil moisture retrieval algorithm independent of the soil temperature is developed for use with advanced microwave scanning radiometer-Earth observing system measurements. The quasiemissivity is parameterized as the ratio of the brightness temperature in the other channels to that in the 36.5 GHz vertical (V-) polarization in order to correct the soil temperature effects in the estimation of soil moisture. To analyze the surface roughness effect on quasiemissivity, a simulation database covering a large range of soil properties is generated. The advanced integral equation model (AIEM) is used to simulate the soil emissivities at different frequencies. The parameters describing the soil roughness effect on quasiemissivity at two polarizations are found to be expressed by a linear function. Using this relationship and the quasiemissivity at two polarizations, the surface roughness effect is minimized in the estimation of the soil moisture. Thus, soil moisture can be estimated using the brightness temperatures at a given frequency in the V-and horizontal (H-) polarizations and at 36.5 GHz of V-polarization. Compared with the data simulated using AIEM, the algorithm has a root-mean-square error (RMSE) of approximately 0.009 cm(3)/cm(3) for the volumetric soil moisture. For validation, a controlled field experiment is conducted using a truck-mounted multifrequency microwave radiometer. Moreover, the experimental data acquired from the Institute National de Recherches Agronomiques (INRA) field experiment are also used to evaluate the accuracy of the algorithm. The RMSE is approximately 0.04 cm(3)/cm(3) for these two experimental data. In order to analyze the performance or capability of this algorithm using satellite data, the soil moisture derived from WindSat data using this algorithm is compared to the Murrumbidgee soil moisture monitoring network dataset. These results indicate that the newly developed inversion technique has an acceptable accuracy and is expected to be useful for application for bare surface soil moisture estimation. (C) 2014 Society of Photo-Optical Instrumentation Engineers (SPIE)
通讯作者地址: Jiang, LM (通讯作者)
Beijing Normal Univ, State Key Lab Remote Sensing Sci, Beijing 100875, Peoples R China.
[ 1 ] Beijing Normal Univ, State Key Lab Remote Sensing Sci, Beijing 100875, Peoples R China
[ 2 ] Sch Geog, Beijing 100875, Peoples R China
[ 3 ] Chinese Acad Sci, Inst Remote Sensing & Digital Earth, State Key Lab Remote Sensing Sci, Beijing 100101, Peoples R China
[ 4 ] Univ Chinese Acad Sci, Beijing 100049, Peoples R China
[ 5 ] Beijing Normal Univ, Coll Informat Sci & Technol, Beijing 100875, Peoples R China