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Estimation of surface soil moisture using FengYun-2E (FY-2E) data: A case study over the source area of the Yellow River

机译:利用FengYun-2E(FY-2E)数据估算地表土壤水分:以黄河源区为例

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Surface soil moisture (SSM) is a significant variable in various fields of science. This paper aims to analyze and improve a SSM retrieval model to apply it to estimate SSM at the regional scale. Firstly, the model parameters were been analyzed. The rotation angle was transformed into exponential form and the ellipse center horizontal coordinate was decreased for the improved SSM retrieval model. After validation with the simulated data from Common Land Model (CoLM), the result indicated that the accuracy of improved model was not lower than the original one after one model coefficient removed. Subsequently, regional SSM was mapped with improved model from FengYun-2E (FY-2E) observation. In addition, the improved SSM retrieval model showed a good consistency with Climate Change Initiative soil moisture (CCI SM) product. Ultimately, a preliminary validation was conducted using the ground measurements in the source area of the Yellow River (SAYR). The result presented an R of 0.53, a RMSE of 0.06 m3/m3 and a bias of 0.03 m3/m3.
机译:在各种科学领域中,地表土壤水分(SSM)是一个重要的变量。本文旨在分析和改进SSM检索模型,以将其应用于区域规模的SSM估算。首先,分析了模型参数。改进的SSM检索模型将旋转角度转换为指数形式,并减小了椭圆中心水平坐标。经过来自公共土地模型(CoLM)的模拟数据验证,结果表明,改进模型的精度不低于一个模型系数后的原始模型精度。随后,利用风云2E(FY-2E)观测的改进模型对区域SSM进行了测绘。此外,改进的SSM检索模型显示出与“气候变化倡议”土壤水分(CCI SM)产品具有良好的一致性。最终,使用黄河源区(SAYR)的地面测量结果进行了初步验证。结果显示R为0.53,RMSE为0.06 m3 / m3,偏差为0.03 m3 / m3。

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