数字农科院2.0

An Innovative Framework for Hourly Satellite Soil Moisture Retrieval via Integrated Spatiotemporal Downscaling Techniques

文献类型： 外文期刊

作者： Peilin Song;;Mengran Wang;; Lixin Dong;;Tianjie Zhao;; Haigen Zhao ;;Jingfeng Huang;; Yongqiang Zhang

关键词： soil moisture; remote sensiing

期刊名称： IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING

ISSN： 0196-2892

年卷期： 2025 年

页码：

收录情况： SCIE（2025版） ; ; EI（2025版）

摘要： Satellite microwave remote sensing is acknowledged as the primary method for obtaining global-scale surface soil moisture (SSM) data. Typically, spaceborne microwave sensors aboard polar-orbiting satellites yield SSM estimates with a native spatial resolution of several tens of kilometers and a temporal resolution of about once or twice daily. This indicates considerable potential for enhancing both of their spatial and temporal resolutions. Although spatial downscaling of spaceborne microwave SSM has garnered significant attention recently, the enhancement of their temporal resolution has received less focus. This study pioneers a methodology for generating hourly scale satellite SSM estimates. The developed approach integrates a novel blending module that combines geostationary satellite observations with a spatially downscaled SSM dataset derived from traditional fusion among microwave and optical observations on polar-orbiting platforms. This blending module leverages land surface temperature (LST) data from geostationary satellites, which effectively quantify SSM variations on an hourly interval upon the thermal inertia theory. Consequently, a comprehensive spatiotemporal integrated framework for SSM downscaling is established to produce hourly scale SSM at a resolution of 6 km, enhancing upon the daily and 36-km resolutions of existing

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