Reconstruction of a Global 9km,8-Day SMAP Surface Soil Moisture Dataset during 2015-2020 by Spatiotemporal Fusion
作者机构：College of Surveying and Geo-InformaticsTongji University1239 Siping RoadShanghai 200092China Institute of Mountain Hazards and EnvironmentChinese Academy of SciencesChengdu 610041China Faculty of Science and TechnologyLancaster UniversityLancaster LA14YRUK Geography and EnvironmentUniversity of SouthamptonHighfieldSouthampton SO171BJUK
出 版 物：《Journal of Remote Sensing》 (国际遥感学报（英文）)
年 卷 期：2022年第2022卷第1期
页 面：116-138页
核心收录：
学科分类：06[历史学]
基 金：This research was supported by the National Natural Science Foundation of China under Grants 42171345 and 41971297 Tongji University under Grant 02502350047
主 题：details moisture Reconstruction
摘 要：Soil moisture,a crucial property for Earth surface research,has been focused widely in various *** Soil Moisture Active Passive(SMAP)global products at 36 km and 9 km(called P36 and AP9 in this research)have been published from April ***,the 9 km AP9 product was retrieved from the active radar and L-band passive radiometer and the active radar failed in July *** this research,the virtual image pair-based spatiotemporal fusion model was coupled with a spatial weighting scheme(VIPSTF-SW)to simulate the 9 km AP9 data after failure of the active *** method makes full use of all the historical AP9 and P36 data available between April and July *** a result,8-day composited 9 km SMAP data at the global scale were produced from 2015 to 2020,by downscaling the corresponding 8-day composited P36 *** available AP9 data and in situ reference data were used to validate the predicted 9 km ***,the predicted 9 km SMAP data can provide more spatial details than P36 and are more accurate than the existing EP9 *** VIPSTF-SW-predicted 9 km SMAP data are an accurate substitute for AP9 and will be made freely available to support research and applications in hydrology,climatology,ecology,and many other fields at the global scale.
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