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

机译:基于全极化Radarsat-2数据的基于典型极化分解技术的玉米田土壤水分反演方法

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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).
机译:土壤湿度(SM)估计值对研究很重要,但在植被高的地区无法准确预测。使用全极化Radarsat-2 C波段数据,通过玉米不同生长阶段的典型极化分解(Freeman-Durden,Yamaguchi和VanZly)来检索SM含量。进行了适用性分析,包括比例,回归和表面散射模型分析。此外,使用布拉格,扩展的布拉格散射模型(X-Bragg)和改进的表面散射模型(ISSM)来检索SM含量。结果表明,VanZly分解方法是最好的。比例分析中表面散射的比例最高(> 52%),其次是山口法(> 41%)。在回归分析中,表面散射与SM之间的R2(> 0.6144)显着高于二面体散射与SM之间的R2(R2 <0.4484)。在不同的玉米生长阶段,ISSM优于Bragg和X-Bragg模型,具有更高的R2(> 0.6599)和更低的绝对误差(AE)(<5.82)和均方根误差(RMSE)(<3.73)。在播种阶段获得了最佳算法(R2 = 0.8843,AE = 3.13,RMSE = 1.76)。此外,X-Bragg模型无需提供测量数据即可更好地逼近实际表面散射(更好的算法:R2 = 0.8314,AE = 4.39,RMSE = 2.81)。

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