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Empirical model for surface soil moisture estimation over wheat fields using C-band polarimetric SAR

机译:基于C波段极化SAR的麦田表层土壤水分估算的实证模型。

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This study proposes a simple empirical model based on polarimetric parameters extracted from RADARSAT-2 imagery to retrieve surface soil moisture (0-5 cm) over agricultural fields. The model is calibrated with ground data acquired from 13 wheat fields, over their whole growth cycle, during the SMAPVEX12 campaign. Sensitivity analysis of the extracted polarimetric variables to soil moisture demonstrated distinct correlations before and after the beginning of the crops flowering stage. Linear backscattering showed significant correlations for all polarizations before crops flowering. The empirical model based on combined linear backscattering coefficients and polarimetric variables allowed to retrieve soil moisture with a 0.076 m3/m3. RMSE if calibrated for the whole growth cycle, 0.067 m3/m3. RMSE if calibrated for data before crop flowering and 0.042 m3/m3. With the data after flowering.
机译:这项研究提出了一个简单的经验模型,该模型基于从RADARSAT-2影像中提取的极化参数,以检索农田上的表层土壤水分(0-5厘米)。在SMAPVEX12活动期间,使用从13个麦田的整个生长周期中获取的地面数据对模型进行了校准。提取的极化变量对土壤水分的敏感性分析表明,在作物开花期开始之前和之后都有明显的相关性。线性反向散射显示出作物开花前所有极化的显着相关性。基于线性反向散射系数和极化变量的经验模型可以获取0.076 m3 / m3的土壤水分。如果对整个生长周期进行校准,则RMSE为0.067 m3 / m3。如果对作物开花前的数据和0.042 m3 / m3的数据进行了校准,则RMSE。随着开花后的数据。

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