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Soil Moisture Retrival Based on Sentinel-1 Imagery under Sparse Vegetation Coverage

机译:稀疏植被覆盖下基于Sentinel-1图像的土壤水分反演

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摘要

Soil moisture is an important aspect of heat transfer process and energy exchange between land-atmosphere systems, and it is a key link to the surface and groundwater circulation and land carbon cycles. In this study, according to the characteristics of the study area, an advanced integral equation model was used for numerical simulation analysis to establish a database of surface microwave scattering characteristics under sparse vegetation cover. Thus, a soil moisture retrieval model suitable for arid area was constructed. The results were as follows: (1) The response of the backscattering coefficient to soil moisture and associated surface roughness is significantly and logarithmically correlated under different incidence angles and polarization modes, and, a database of microwave scattering characteristics of arid soil surface under sparse vegetation cover was established. (2) According to the Sentinel-1 radar system parameters, a model for retrieving spatial distribution information of soil moisture was constructed; the soil moisture content information was extracted, and the results were consistent with the spatial distribution characteristics of soil moisture in the same period in the research area. (3) For the 0–10 cm surface soil moisture, the correlation coefficient between the simulated value and the measured value reached 0.8488, which means that the developed retrieval model has applicability to derive surface soil moisture in the oasis region of arid regions. This study can provide method for real-time and large-scale detection of soil moisture content in arid areas.
机译:土壤水分是土地-大气系统之间传热过程和能量交换的重要方面,并且是与地表水和地下水循环以及土地碳循环的关键环节。本研究根据研究区的特点,利用先进的积分方程模型进行了数值模拟分析,建立了植被稀疏条件下地表微波散射特征的数据库。因此,构建了适合干旱地区的土壤水分反演模型。研究结果如下:(1)在不同入射角和极化模式下,土壤水分和相关表面粗糙度对后向散射系数的响应呈显着对数相关关系,且稀疏植被下干旱土壤表面的微波散射特性数据库封面成立。 (2)根据Sentinel-1雷达系统参数,建立了土壤水分空间分布信息反演模型。提取土壤含水量信息,结果与研究区同期土壤水分的空间分布特征相吻合。 (3)对于0–10 cm表层土壤水分,模拟值与测量值之间的相关系数达到0.8488,这意味着所开发的检索模型适用于得出干旱区绿洲地区的表层土壤水分。该研究可以为干旱地区土壤水分的实时,大规模检测提供方法。

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