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Geocarto International Volume 36, 2021 - Issue 2
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Research Article

Geographical random forests: a spatial extension of the random forest algorithm to address spatial heterogeneity in remote sensing and population modelling

Stefanos Georganosa Department of Geosciences, Environment & Society, Université Libre De Bruxelles (ULB), Bruxelles, BelgiumCorrespondence[email protected]
ORCID Iconhttps://orcid.org/0000-0002-0001-2058View further author information
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Tais Grippaa Department of Geosciences, Environment & Society, Université Libre De Bruxelles (ULB), Bruxelles, BelgiumORCID Iconhttps://orcid.org/0000-0002-9837-1832View further author information
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Assane Niang Gadiagab Institute of Life, Earth and Environment, University of Namur, Namur, BelgiumView further author information
,
Catherine Linardb Institute of Life, Earth and Environment, University of Namur, Namur, BelgiumView further author information
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Moritz Lennerta Department of Geosciences, Environment & Society, Université Libre De Bruxelles (ULB), Bruxelles, BelgiumORCID Iconhttps://orcid.org/0000-0002-2870-4515View further author information
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Sabine Vanhuyssea Department of Geosciences, Environment & Society, Université Libre De Bruxelles (ULB), Bruxelles, BelgiumView further author information
,
Nicholus Mbogaa Department of Geosciences, Environment & Society, Université Libre De Bruxelles (ULB), Bruxelles, BelgiumView further author information
,
Eléonore Wolffa Department of Geosciences, Environment & Society, Université Libre De Bruxelles (ULB), Bruxelles, BelgiumView further author information
&
Stamatis Kalogirouc Department of Geography, Harokopio University, Kallithea, GreeceView further author information
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Pages 121-136 | Received 20 Dec 2018, Accepted 08 Mar 2019, Published online: 10 Jun 2019

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