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
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Total article views: 4,499 (including HTML, PDF, and XML)
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3,192
1,186
121
4,499
276
115
170
HTML: 3,192
PDF: 1,186
XML: 121
Total: 4,499
Supplement: 276
BibTeX: 115
EndNote: 170
Views and downloads (calculated since 08 Jun 2023)
Cumulative views and downloads
(calculated since 08 Jun 2023)
Total article views: 3,011 (including HTML, PDF, and XML)
HTML
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2,187
737
87
3,011
151
101
149
HTML: 2,187
PDF: 737
XML: 87
Total: 3,011
Supplement: 151
BibTeX: 101
EndNote: 149
Views and downloads (calculated since 19 Oct 2023)
Cumulative views and downloads
(calculated since 19 Oct 2023)
Total article views: 1,488 (including HTML, PDF, and XML)
HTML
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1,005
449
34
1,488
125
14
21
HTML: 1,005
PDF: 449
XML: 34
Total: 1,488
Supplement: 125
BibTeX: 14
EndNote: 21
Views and downloads (calculated since 08 Jun 2023)
Cumulative views and downloads
(calculated since 08 Jun 2023)
Viewed (geographical distribution)
Total article views: 4,499 (including HTML, PDF, and XML)
Thereof 4,462 with geography defined
and 37 with unknown origin.
Total article views: 3,011 (including HTML, PDF, and XML)
Thereof 3,008 with geography defined
and 3 with unknown origin.
Total article views: 1,488 (including HTML, PDF, and XML)
Thereof 1,454 with geography defined
and 34 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...
