Departamento de Ingeniería Topográfica y Cartográfica, E.T.S.I. en Topografía, Geodesia y Cartografía, Universidad Politécnica de Madrid, Campus Sur, A-3, Km 7, 28031 Madrid, Spain
Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente, 7522 NH Enschede, the Netherlands
Key Laboratory of Subsurface Hydrology and Ecological Effect in Arid Region of the Ministry of Education, School of Water and Environment, Chang'an University, Xi'an 710054, China
Viewed
Total article views: 4,010 (including HTML, PDF, and XML)
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2,889
1,008
113
4,010
246
107
145
HTML: 2,889
PDF: 1,008
XML: 113
Total: 4,010
Supplement: 246
BibTeX: 107
EndNote: 145
Views and downloads (calculated since 08 Jun 2023)
Cumulative views and downloads
(calculated since 08 Jun 2023)
Total article views: 2,624 (including HTML, PDF, and XML)
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1,951
594
79
2,624
136
93
132
HTML: 1,951
PDF: 594
XML: 79
Total: 2,624
Supplement: 136
BibTeX: 93
EndNote: 132
Views and downloads (calculated since 19 Oct 2023)
Cumulative views and downloads
(calculated since 19 Oct 2023)
Total article views: 1,386 (including HTML, PDF, and XML)
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938
414
34
1,386
110
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13
HTML: 938
PDF: 414
XML: 34
Total: 1,386
Supplement: 110
BibTeX: 14
EndNote: 13
Views and downloads (calculated since 08 Jun 2023)
Cumulative views and downloads
(calculated since 08 Jun 2023)
Viewed (geographical distribution)
Total article views: 4,010 (including HTML, PDF, and XML)
Thereof 3,969 with geography defined
and 41 with unknown origin.
Total article views: 2,624 (including HTML, PDF, and XML)
Thereof 2,614 with geography defined
and 10 with unknown origin.
Total article views: 1,386 (including HTML, PDF, and XML)
Thereof 1,355 with geography defined
and 31 with unknown origin.
Using machine learning, we estimated global surface soil moisture (SSM) to aid in understanding water, energy, and carbon exchange. Ensemble models outperformed individual algorithms in predicting SSM under different climates. The best-performing ensemble included K-neighbours Regressor, Random Forest Regressor, and Extreme Gradient Boosting. This is important for hydrological and climatological applications such as water cycle monitoring, irrigation management, and crop yield prediction.
Using machine learning, we estimated global surface soil moisture (SSM) to aid in understanding...
