UNESCO/UNITWIN Chair Appropriate Technologies for Human Development, Department of Geodynamic, Stratigraphy and Paleontology, Faculty of Geology,
Complutense University of Madrid, 28040
Madrid, Spain
Pedro Martínez-Santos
UNESCO/UNITWIN Chair Appropriate Technologies for Human Development, Department of Geodynamic, Stratigraphy and Paleontology, Faculty of Geology,
Complutense University of Madrid, 28040
Madrid, Spain
Miguel Martín-Loeches
Department of Geology, Geography and Environmental Science,
University of Alcalá, Alcalá de Henares, Madrid, Spain
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Cumulative views and downloads
(calculated since 30 Jun 2021)
Total article views: 4,804 (including HTML, PDF, and XML)
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3,385
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4,804
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HTML: 3,385
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Total: 4,804
BibTeX: 114
EndNote: 126
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519
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Cumulative views and downloads
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Viewed (geographical distribution)
Total article views: 5,703 (including HTML, PDF, and XML)
Thereof 5,396 with geography defined
and 307 with unknown origin.
Total article views: 4,804 (including HTML, PDF, and XML)
Thereof 4,585 with geography defined
and 219 with unknown origin.
Total article views: 899 (including HTML, PDF, and XML)
Thereof 811 with geography defined
and 88 with unknown origin.
Many communities in the Sahel rely solely on groundwater. We develop a machine learning technique to map areas of groundwater potential. Algorithms are trained to detect areas where there is a confluence of factors that facilitate groundwater occurrence. Our contribution focuses on using variable scaling to minimize expert bias and on testing our results beyond standard metrics. This approach is illustrated through its application to two administrative regions of Mali.
Many communities in the Sahel rely solely on groundwater. We develop a machine learning...
