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Bare Surface Soil Moisture Estimation Using Double-Angle and Dual-Polarization L-Band Radar Data

机译:利用双角度和双极化L波段雷达数据估算裸露的土壤水分

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摘要

Based on today's most widely used surface scattering model, the advanced integral equation model (AIEM), this study proposes a novel soil moisture inversion model that estimates bare surface soil moisture using double-incidence angle and dual-polarized L-band radar data. Compared with previous studies at L-/C-band, the proposed method provides the estimation of soil moisture without referring to the measured soil roughness and eliminates the requirement of an initial dry season condition. The root-mean-square error (rmse) of volumetric soil moisture varies from 0.8% to 3.2% at different incidence-angle combinations validated by simulated solving and from 4.0% to 7.9% by field measurements when the paired incidence angles are not both large. In case the paired angels are both large, not particularly suitable for soil moisture estimation, the rmse increases to 10.3%. Therefore, this method is applicable to bare surface soil moisture retrieval when at least one of the incidence angles is not large.
机译:基于当今使用最广泛的表面散射模型,高级积分方程模型(AIEM),本研究提出了一种新颖的土壤水分反演模型,该模型使用双入射角和双极化L波段雷达数据估算裸露的土壤水分。与以前在L波段/ C波段进行的研究相比,该方法可以在不参考测得的土壤粗糙度的情况下提供对土壤湿度的估算,并且不需要初始干旱季节条件。当成对的入射角都不大时,在通过模拟求解验证的不同入射角组合下,土壤含水量的均方根误差(rmse)从0.8%变化到3.2%,通过现场测量从4.0%变化到7.9%。 。如果成对的天使都很大,特别不适合估算土壤湿度,则均方根值将增加到10.3%。因此,当至少一个入射角不大时,该方法适用于裸露的表层土壤水分的获取。

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