array(2) { ["lab"]=> string(3) "770" ["publication"]=> string(4) "4877" } Soil Moisture Retrival Based on Sentinel-1 Imagery under Sparse Vegetation Coverage - 丁建丽团队—干旱区遥感科学与技术 | LabXing

丁建丽团队—干旱区遥感科学与技术

简介 聚焦干旱区科学前沿研究,包括智能遥感应用、土壤盐渍化、生态水文、大气环境、遥感科学、智慧城市等方向。

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

2019
期刊 Sensors
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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.