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The Soil Moisture Active Passive (SMAP) offers daily global composites of SM at coarse-resolution 9 and 36 km, with data gaps limiting its local application to depict SM distribution in detail. To overcome the aforementioned problem, a downscaling and gap-filling novel approach was adopted, using random forest (RF) and artificial neural network (ANN) algorithms to downscale SMAP SM data, using land-surface variables from moderate-resolution imaging spectroradiometer (MODIS) onboard Aqua and Terra satellites from the years 2018 to 2019. Firstly, four combinations (RF+Aqua, RF+Terra, ANN+Aqua, and ANN+Terra) were developed. Each combination downscaled SMAP SM at a high resolution (1 km). These combinations were evaluated by using error matrices and in situ SM at different scales in the ShanDian River (SDR) Basin. The combination RF+Terra showed a better performance, with a low averaged unbiased root mean square error (ubRMSE) of 0.034 m3\/m3 and high averaged correlation (R) of 0.54 against the small-, medium-, and large-scale in situ SM. Secondly, the impact of various land covers was examined by using downscaled SMAP and in situ SM. Vegetation attenuation makes woodland more error-prone and less correlated than grassland and farmland. Finally, the RF+Terra and ANN+Terra combinations were selected for their higher accuracy in gap filling of downscaled SMAP SM. The gap-filled downscaled SMAP SM results were compared spatially with China Land Data Assimilation System (CLDAS) SM and in situ SM. The RF+Terra combination outcomes were more humid than ANN+Terra combination results in the SDR basin. Overall, the RF+Terra combination gap-filled data showed high R (0.40) and less ubRMSE (0.064 m3\/m3) against in situ SM, which was close to CLDAS SM. This study showed that the proposed RF- and ANN-based downscaling methods have a potential to improve the spatial resolution and gap-filling of SMAP SM at a high resolution (1 km).<\/jats:p>","DOI":"10.3390\/rs15030812","type":"journal-article","created":{"date-parts":[[2023,2,1]],"date-time":"2023-02-01T05:33:53Z","timestamp":1675229633000},"page":"812","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":37,"title":["Spatial Downscaling and Gap-Filling of SMAP Soil Moisture to High Resolution Using MODIS Surface Variables and Machine Learning Approaches over ShanDian River Basin, China"],"prefix":"10.3390","volume":"15","author":[{"given":"Adeel Ahmad","family":"Nadeem","sequence":"first","affiliation":[{"name":"State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, Wuhan 430072, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4323-0730","authenticated-orcid":false,"given":"Yuanyuan","family":"Zha","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, Wuhan 430072, China"},{"name":"Guangxi Key Laboratory of Water Engineering Materials and Structures, Guangxi Institute of Water Resources Research, Nanning 530015, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0446-0488","authenticated-orcid":false,"given":"Liangsheng","family":"Shi","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, Wuhan 430072, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6377-6610","authenticated-orcid":false,"given":"Shoaib","family":"Ali","sequence":"additional","affiliation":[{"name":"School of Water Conservancy & Civil Engineering, Northeast Agricultural University, Harbin 150030, China"}]},{"given":"Xi","family":"Wang","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, Wuhan 430072, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1575-9242","authenticated-orcid":false,"given":"Zeeshan","family":"Zafar","sequence":"additional","affiliation":[{"name":"Shaanxi Key Laboratory of Earth Surface System and Environmental Carrying Capacity, College of Urban and Environmental Sciences, Northwest University, Xi\u2019an 710127, China"}]},{"given":"Zeeshan","family":"Afzal","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0226-7310","authenticated-orcid":false,"given":"Muhammad Atiq Ur Rehman","family":"Tariq","sequence":"additional","affiliation":[{"name":"Institute for Sustainable Industries & Liveable Cities, Victoria University, P.O. 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