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: 4,607 (including HTML, PDF, and XML)
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3,265
1,218
124
4,607
289
118
174
HTML: 3,265
PDF: 1,218
XML: 124
Total: 4,607
Supplement: 289
BibTeX: 118
EndNote: 174
Views and downloads (calculated since 08 Jun 2023)
Cumulative views and downloads
(calculated since 08 Jun 2023)
Total article views: 3,088 (including HTML, PDF, and XML)
HTML
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2,234
764
90
3,088
158
104
153
HTML: 2,234
PDF: 764
XML: 90
Total: 3,088
Supplement: 158
BibTeX: 104
EndNote: 153
Views and downloads (calculated since 19 Oct 2023)
Cumulative views and downloads
(calculated since 19 Oct 2023)
Total article views: 1,519 (including HTML, PDF, and XML)
HTML
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1,031
454
34
1,519
131
14
21
HTML: 1,031
PDF: 454
XML: 34
Total: 1,519
Supplement: 131
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: 4,607 (including HTML, PDF, and XML)
Thereof 4,566 with geography defined
and 41 with unknown origin.
Total article views: 3,088 (including HTML, PDF, and XML)
Thereof 3,081 with geography defined
and 7 with unknown origin.
Total article views: 1,519 (including HTML, PDF, and XML)
Thereof 1,485 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...
