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PIER PIER B PIER C PIER M PIER Letters
2021-04-03
L-Band Radar Scattering and Soil Moisture Retrieval of Wheat, Canola and Pasture Fields for SMAP Active Algorithms
By
Huanting Huang,

    Dr. Huanting Huang

    Department of Electrical Engineering and Computer Science

    University of Michigan

    USA

    Homepage

Tien-Hao Liao,

    Dr. Tien-Hao Liao

    California Institute of Technology

    USA

    Homepage

Seung Bum Kim,

    Dr. Seung Bum Kim

    California Institute of Technology

    USA

    Homepage

Xiaolan Xu,

    Dr. Xiaolan Xu

    California Institute of Technology

    USA

    Homepage

Leung Tsang,

    Professor Leung Tsang

    Department of Electrical Engineering and Computer Science

    University of Michigan

    USA

    Homepage

Thomas J. Jackson,

    Professor Thomas J. Jackson

    USDA ARS Hydrology and Remote Sensing Lab

    USA

    Homepage

Simon Yueh

    Dr. Simon Yueh

    Jet Propulsion Laboratory

    USA

    Homepage

Progress In Electromagnetics Research, Vol. 170, 129-152, 2021
doi:10.2528/PIER21020702
Abstract
Wheat, canola, and pasture are three of the major vegetation types studied during the Soil Moisture Active Passive Validation Experiment 2012 (SMAPVEX12) conducted to support NASA's Soil Moisture Active Passive (SMAP) mission. The utilized model structure is integrated in the SMAP baseline active retrieval algorithm. Forward lookup tables (data-cubes) for VV and HH backscatters at L-band are developed for wheat and canola fields. The data-cubes have three axes: vegetation water content (VWC), root mean square (RMS) height of rough soil surface and soil permittivity. The volume scattering and doublebounce scattering of the fields are calculated using the distorted Born approximation and the coherent reflectivity in the double-bounce scattering. The surface scattering is determined by the numerical solutions of Maxwell equations (NMM3D). The results of the data-cubes are validated with airborne radar measurements collected during SMAPVEX12 for ten wheat fields, five canola fields, and three pasture fields. The results show good agreement between the data-cube simulation and the airborne data. The root mean squared errors (RMSE) were 0.82 dB, 0.78 dB, and 1.62 dB for HH, and 0.97 dB, 1.30 dB, and 1.82 dB for VV of wheat, canola, and pasture fields, respectively. The data-cubes are next used to perform the time-series retrieval of the soil moisture. The RMSEs of the soil moisture retrieval are 0.043 cm3/cm3, 0.082 cm3/cm3, and 0.082 cm3/cm3 for wheat, canola, and pasture fields, respectively. The results of this paper expand the scope of the SMAP baseline radar algorithm for wheat, canola, and pastures formed and provide a quantitative validation of its performance. It will also have applications for the upcoming NISAR (NASA-ISRO SAR Mission).
Citation
Huanting Huang, Tien-Hao Liao, Seung Bum Kim, Xiaolan Xu, Leung Tsang, Thomas J. Jackson, and Simon Yueh, "L-Band Radar Scattering and Soil Moisture Retrieval of Wheat, Canola and Pasture Fields for SMAP Active Algorithms," Progress In Electromagnetics Research, Vol. 170, 129-152, 2021.
doi:10.2528/PIER21020702
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