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A Synergistic Methodology for Soil Moisture Estimation in an Alpine Prairie Using Radar and Optical Satellite Data

机译:利用雷达和光学卫星数据估算高寒草原土壤水分的协同方法

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This paper presents a microwave/optical synergistic methodology to retrieve soil moisture in an alpine prairie. The methodology adequately represents the scattering behavior of the vegetation-covered area by defining the scattering of the vegetation and the soil below. The Integral Equation Method (IEM) was employed to determine the backscattering of the underlying soil. The modified Water Cloud Model (WCM) was used to reduce the effect of vegetation. Vegetation coverage, which can be easily derived from optical data, was incorporated in this method to account for the vegetation gap information. Then, an inversion scheme of soil moisture was developed that made use of the dual polarizations (HH and VV) available from the quad polarization Radarsat-2 data. The method developed in this study was assessed by comparing the reproduction of the backscattering, which was calculated from an area with full vegetation cover to that with relatively sparse cover. The accuracy and sources of error in this soil moisture retrieval method were evaluated. The results showed a good correlation between the measured and estimated soil moisture (R2 = 0.71, RMSE = 3.32 vol.%, p 0.01). Therefore, this method has operational potential for estimating soil moisture under the vegetated area of an alpine prairie.
机译:本文提出了一种微波/光学协同方法来检索高寒草原中的土壤水分。该方法通过定义下面植被和土壤的散射来充分表示植被覆盖区域的散射行为。积分方程法(IEM)用于确定下层土壤的反向散射。修改后的水云模型(WCM)用于减少植被的影响。该方法结合了植被覆盖度,可以轻松地从光学数据中得出植被覆盖度,以说明植被间隙信息。然后,开发了土壤水分的反演方案,该方案利用了从四极化Radarsat-2数据获得的双极化(HH和VV)。本研究开发的方法是通过比较反向散射的再现来评估的,该散射是从植被完全覆盖的区域到植被相对稀疏的区域计算得出的。评价了这种土壤水分反演方法的准确性和误差来源。结果表明,测得的土壤湿度与估计的土壤湿度之间具有良好的相关性(R 2 = 0.71,RMSE = 3.32 vol。%,p <0.01)。因此,该方法具有估算高寒草原植被区土壤水分的操作潜力。

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