结合参量统计与时空融合的土壤水分降尺度方法

Soil Moisture Downscaling Method Combining Parameter Statistics and Spatio-temporal Fusion

土壤水分的降尺度研究为解决被动微波产品的粗分辨率问题,更好地服务于流域小尺度应用提供了技术手段。以美国俄克拉荷马州为研究区域,基于SMAP土壤水分产品和MODIS产品等多种辅助数据,在地表分类数据的支持下,结合参量统计降尺度和时空融合降尺度发展了一种土壤水分混合降尺度方法,并利用SMAP 9 km产品和站点实测数据对降尺度效果进行了评估。结果表明:混合降尺度方法可以得到细节丰富、空间覆盖完整的降尺度结果。相较于参量统计或时空融合两种单一降尺度而言,混合降尺度结果的空间分布与SMAP 9 km真实产品最为相似,并且混合降尺度结果与站点的整体时序精度最高,在不同地表分类下的时序精度也优于单一方法的降尺度结果。由此证明结合参量统计与时空融合的降尺度方法是可行的。

Research on downscaling Soil Moisture(SM)provides a technical means to solve the coarse resolu⁃tion problem of passive microwave SM products and to better serve small-scale regional applications.On the ba⁃sis of SMAP SM products and multiple remote sensing auxiliary data including the MODIS product and so on,supported by the land use data,a hybrid downscaling method was developed by combining the parameter statis⁃tics and spatio-temporal fusion downscaling method.And taking Oklahoma,USA as the study area,the down⁃scaled results were evaluated using SMAP 9 km products and in-site data.The results show that:the hybrid downscaling method could obtain downscaled results with rich details and complete spatial coverage.Compared with the two single downscaling method based on parameter statistics or spatio-temporal fusion,the spatial dis⁃tribution of the hybrid downscaled result was the most similar to the real SMAP 9 km product,and it has the highest temporal accuracy against site data whether on the whole or under different land use.Therefore,the pro⁃posed hybrid downscaling method combining parameter statistics and spatio-temporal fusion was feasible.