{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,12]],"date-time":"2025-11-12T14:16:30Z","timestamp":1762956990803,"version":"build-2065373602"},"reference-count":52,"publisher":"MDPI AG","issue":"19","license":[{"start":{"date-parts":[[2022,9,28]],"date-time":"2022-09-28T00:00:00Z","timestamp":1664323200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"the Ministry of Science and Technology","award":["2019YFC1510600","42171021","U2243203","41901037","2019B05214","2021ZY0027","XSKJ2019081-17","2019AB20003"],"award-info":[{"award-number":["2019YFC1510600","42171021","U2243203","41901037","2019B05214","2021ZY0027","XSKJ2019081-17","2019AB20003"]}]},{"name":"National Natural Science Foundation of China","award":["2019YFC1510600","42171021","U2243203","41901037","2019B05214","2021ZY0027","XSKJ2019081-17","2019AB20003"],"award-info":[{"award-number":["2019YFC1510600","42171021","U2243203","41901037","2019B05214","2021ZY0027","XSKJ2019081-17","2019AB20003"]}]},{"name":"Fundamental Research Funds for the Central Universities","award":["2019YFC1510600","42171021","U2243203","41901037","2019B05214","2021ZY0027","XSKJ2019081-17","2019AB20003"],"award-info":[{"award-number":["2019YFC1510600","42171021","U2243203","41901037","2019B05214","2021ZY0027","XSKJ2019081-17","2019AB20003"]}]},{"name":"Central Guidance for Local Science and Technology Development fund projects","award":["2019YFC1510600","42171021","U2243203","41901037","2019B05214","2021ZY0027","XSKJ2019081-17","2019AB20003"],"award-info":[{"award-number":["2019YFC1510600","42171021","U2243203","41901037","2019B05214","2021ZY0027","XSKJ2019081-17","2019AB20003"]}]},{"name":"Hunan Provincial Water Conservancy Science and Technology Project","award":["2019YFC1510600","42171021","U2243203","41901037","2019B05214","2021ZY0027","XSKJ2019081-17","2019AB20003"],"award-info":[{"award-number":["2019YFC1510600","42171021","U2243203","41901037","2019B05214","2021ZY0027","XSKJ2019081-17","2019AB20003"]}]},{"name":"Guangxi province Key R&amp;D projects","award":["2019YFC1510600","42171021","U2243203","41901037","2019B05214","2021ZY0027","XSKJ2019081-17","2019AB20003"],"award-info":[{"award-number":["2019YFC1510600","42171021","U2243203","41901037","2019B05214","2021ZY0027","XSKJ2019081-17","2019AB20003"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Intermittent records of satellite soil moisture data are major obstacles that constrain their hydrometeorological applications. Based on the European Space Agency Climate Change Initiative (ESA CCI) soil moisture combined product, two machine learning models were employed to reconstruct soil moisture in China during 1979\u20132019 in both temporal and spatial domains, and latent errors for reconstructed series, as well as their performances for tracing climate extremes, were analyzed. The results showed that with the homogeneity of available data over space, the spatial approach performed well in reproducing the spatial heterogeneity of soil moisture (with medians of the correlation coefficient (CC) above 0.8 and root mean square errors (RMSEs) ranging from 0.02 to 0.03 m3\u2219m\u22123). The temporal approach (CC values of 0.7 and RMSEs ranging between 0.02 and 0.03 m3\u2219m\u22123) was superior in capturing the seasonality features and the timely and accurate mapping of short-term soil moisture dynamics impacted by rainstorms. However, both approaches failed to identify the location and severity of droughts accurately. The findings highlight the benefits of combining the strengths of both temporal and spatial gap-filling approaches for improving the estimation of missing values and hydrometeorological applications.<\/jats:p>","DOI":"10.3390\/rs14194841","type":"journal-article","created":{"date-parts":[[2022,9,28]],"date-time":"2022-09-28T22:53:19Z","timestamp":1664405599000},"page":"4841","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Satellite Soil Moisture Data Reconstruction in the Temporal and Spatial Domains: Latent Error Assessments and Performances for Tracing Rainstorms and Droughts"],"prefix":"10.3390","volume":"14","author":[{"given":"Yi","family":"Liu","sequence":"first","affiliation":[{"name":"College of Hydrology and Water Resources, Hohai University, Nanjing 210098, China"}]},{"given":"Ruiqi","family":"Chen","sequence":"additional","affiliation":[{"name":"College of Hydrology and Water Resources, Hohai University, Nanjing 210098, China"}]},{"given":"Shanshui","family":"Yuan","sequence":"additional","affiliation":[{"name":"Yangtze Institute for Conservation and Development, Hohai University, Nanjing 210098, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3329-5787","authenticated-orcid":false,"given":"Liliang","family":"Ren","sequence":"additional","affiliation":[{"name":"College of Hydrology and Water Resources, Hohai University, Nanjing 210098, China"}]},{"given":"Xiaoxiang","family":"Zhang","sequence":"additional","affiliation":[{"name":"College of Hydrology and Water Resources, Hohai University, Nanjing 210098, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4146-9510","authenticated-orcid":false,"given":"Changjun","family":"Liu","sequence":"additional","affiliation":[{"name":"China Institute of Water Resources and Hydropower Research, Beijing 650599, China"}]},{"given":"Qiang","family":"Ma","sequence":"additional","affiliation":[{"name":"China Institute of Water Resources and Hydropower Research, Beijing 650599, China"}]}],"member":"1968","published-online":{"date-parts":[[2022,9,28]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"112162","DOI":"10.1016\/j.rse.2020.112162","article-title":"A roadmap for high-resolution satellite soil moisture applications\u2013confronting product characteristics with user requirements","volume":"252","author":"Peng","year":"2021","journal-title":"Remote Sens. 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