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Remote Sens. 2017, 9(2), 168; doi:10.3390/rs9020168

A Soil Moisture Retrieval Method Based on Typical Polarization Decomposition Techniques for a Maize Field from Full-Polarization Radarsat-2 Data

Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China
Geomatics College, Shandong University of Science and Technology, Qingdao 266590, China
Sanya Institute of Remote Sensing, Hainan 572029, China
Author to whom correspondence should be addressed.
Received: 10 November 2016 / Accepted: 9 February 2017 / Published: 17 February 2017
(This article belongs to the Special Issue Earth Observations for Precision Farming in China (EO4PFiC))
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Soil moisture (SM) estimates are important to research, but are not accurately predictable in areas with tall vegetation. Full-polarization Radarsat-2 C-band data were used to retrieve SM contents using typical polarization decomposition (Freeman–Durden, Yamaguchi and VanZly) at different growth stages of maize. Applicability analyses were conducted, including proportion, regression and surface scattering model analyses. Furthermore, the Bragg, the extended Bragg scattering model (X-Bragg) and improved surface scattering models (ISSM) were used to retrieve SM content. The results indicated that the VanZly decomposition method was the best. The proportion of surface scattering in the proportion analysis was highest (>52%), followed by that in the Yamaguchi method (>41%). The R2 (>0.6144) between surface scattering and SM was significantly higher (R2 < 0.4484) between dihedral scattering and SM in the regression analysis. The ISSM was better at different maize growth stages than the Bragg and X-Bragg models with a higher R2 (>0.6599) and lower absolute error (AE) (<5.82) and root mean square error (RMSE) (<3.73). The best algorithm was obtained at the sowing stage (R2 = 0.8843, AE = 3.13, RMSE = 1.76). In addition, the X-Bragg model provided better approximation of actual surface scattering without the measured data (better algorithm: R2 = 0.8314, AE = 4.39, RMSE = 2.81). View Full-Text
Keywords: soil moisture; polarization decomposition; Radarsat-2 data; scattering mechanisms soil moisture; polarization decomposition; Radarsat-2 data; scattering mechanisms

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Xie, Q.; Meng, Q.; Zhang, L.; Wang, C.; Sun, Y.; Sun, Z. A Soil Moisture Retrieval Method Based on Typical Polarization Decomposition Techniques for a Maize Field from Full-Polarization Radarsat-2 Data. Remote Sens. 2017, 9, 168.

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