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23 September 2017 Implementation of a multiangle soil moisture retrieval model using RADARSAT-2 imagery over arid Juyanze, northwest China
Liping Yang, Yanfei Li, Qi Li, Xiaohui Sun, Jinling Kong, Le Wang
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Journal of Applied Remote Sensing, Vol. 11, Issue 3, 036029 (September 2017). https://doi.org/10.1117/1.JRS.11.036029
Abstract
Accurate retrieval of soil moisture is important for understanding regional environmental changes and sustainable development in arid regions. Through numerical simulation and regression analysis based on advanced integral equation model (AIEM), the study aims to establish a multiangle soil moisture retrieval model based on RADARSAT-2 image in arid Juyanze. A combined roughness parameter Rs was established, and then the influences of roughness and soil moisture on the backscattering simulations were discussed. Finally, the empirical multiangle soil moisture retrieval model was implemented and validated in Juyanze. Inversion results show that the model has favorable validity. The coefficient of determination R2 between the inferred and measured soil moisture is 0.775 with a root-mean-square error (rmse) of 0.626%, implying better retrieval accuracy. Soil moisture varies from about 0.1% to 25% and is no more than 10% in most parts of this region, which is in reasonable agreement with the factual circumstances. The model directly relates the Fresnel reflection coefficient and soil moisture and is independent of ground roughness measurements. With a wider angular range, it has great potential for soil moisture evaluation in arid regions.
CC BY: © The Authors. Published by SPIE under a Creative Commons Attribution 4.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.
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Liping Yang, Yanfei Li, Qi Li, Xiaohui Sun, Jinling Kong, and Le Wang "Implementation of a multiangle soil moisture retrieval model using RADARSAT-2 imagery over arid Juyanze, northwest China," Journal of Applied Remote Sensing 11(3), 036029 (23 September 2017). https://doi.org/10.1117/1.JRS.11.036029
Received: 24 March 2017; Accepted: 29 August 2017; Published: 23 September 2017
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Cited by 4 scholarly publications.
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KEYWORDS
Soil science
Backscatter
Lithium
Surface roughness
Dielectric polarization
Reflection
Synthetic aperture radar
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