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In this study, we proposed a spatial downscaling method for SM based on random forest considering soil moisture memory and mass conservation to improve downscaling performance. The lagged SM was added as a predictor to represent soil moisture memory, in addition to the regular predictors in previous downscaling studies. The Soil Moisture Active Passive (SMAP) SM data of the Pearl River Basin were used to test our downscaling method. The results show that the downscaling model obtained good performance on the test set (R2 = 0.848, ubRMSE = 0.034 m3\/m3 and Bias = 0.008 m3\/m3). The spatial and temporal performance of the RF downscaling model can be improved by adding lagged SM variables. Downscaled data obtained can retain the information of the original SMAP SM data well and show more spatial details, and mass conservation correction is considered to be useful to eliminate systematic bias of the downscaling model. Downscaled SM achieved acceptable performance in in situ validation, though it was inevitably limited by the performance of the original SMAP data. The proposed downscaling method can serve as a powerful tool for the development of high-resolution SM information.<\/jats:p>","DOI":"10.3390\/rs14163858","type":"journal-article","created":{"date-parts":[[2022,8,10]],"date-time":"2022-08-10T04:20:32Z","timestamp":1660105232000},"page":"3858","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":33,"title":["A Spatial Downscaling Method for Remote Sensing Soil Moisture Based on Random Forest Considering Soil Moisture Memory and Mass Conservation"],"prefix":"10.3390","volume":"14","author":[{"given":"Taoning","family":"Mao","sequence":"first","affiliation":[{"name":"Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Guangdong Province Key Laboratory for Climate Change and Natural Disaster Studies, School of Atmospheric Sciences, Sun Yat-sen University, Guangzhou 510275, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7622-8210","authenticated-orcid":false,"given":"Wei","family":"Shangguan","sequence":"additional","affiliation":[{"name":"Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Guangdong Province Key Laboratory for Climate Change and Natural Disaster Studies, School of Atmospheric Sciences, Sun Yat-sen University, Guangzhou 510275, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6541-9916","authenticated-orcid":false,"given":"Qingliang","family":"Li","sequence":"additional","affiliation":[{"name":"College of Computer Science and Technology, Changchun Normal University, Changchun 130032, China"}]},{"given":"Lu","family":"Li","sequence":"additional","affiliation":[{"name":"Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Guangdong Province Key Laboratory for Climate Change and Natural Disaster Studies, School of Atmospheric Sciences, Sun Yat-sen University, Guangzhou 510275, China"}]},{"given":"Ye","family":"Zhang","sequence":"additional","affiliation":[{"name":"Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Guangdong Province Key Laboratory for Climate Change and Natural Disaster Studies, School of Atmospheric Sciences, Sun Yat-sen University, Guangzhou 510275, China"}]},{"given":"Feini","family":"Huang","sequence":"additional","affiliation":[{"name":"Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Guangdong Province Key Laboratory for Climate Change and Natural Disaster Studies, School of Atmospheric Sciences, Sun Yat-sen University, Guangzhou 510275, China"}]},{"given":"Jianduo","family":"Li","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Severe Weather, Chinese Academy of Meteorological Sciences, Beijing 100081, China"}]},{"given":"Wei","family":"Liu","sequence":"additional","affiliation":[{"name":"Guangdong Climate Center, Guangzhou 510275, China"}]},{"given":"Ruqing","family":"Zhang","sequence":"additional","affiliation":[{"name":"Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Guangdong Province Key Laboratory for Climate Change and Natural Disaster Studies, School of Atmospheric Sciences, Sun Yat-sen University, Guangzhou 510275, China"}]}],"member":"1968","published-online":{"date-parts":[[2022,8,9]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"125","DOI":"10.1016\/j.earscirev.2010.02.004","article-title":"Investigating Soil Moisture-Climate Interactions in a Changing Climate: A Review","volume":"99","author":"Seneviratne","year":"2010","journal-title":"Earth-Sci. 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