Spatial Cross-validation
Spatial Cross-Validation is a model evaluation procedure belonging to the class of cross-validation techniques, distinguished by its explicit accommodation of spatial autocorrelation through spatially structured data partitioning to provide unbiased assessment of spatial prediction models.
87
Publications
6.3K
Citations
307
Authors
189
Institutions
Publications per year
2017–2026
69
87
Tomislav Hengl, Madlene Nussbaum, Marvin N. Wright et al. · PeerJ · 2018 · 1.1K citations · Full text
Computing, Geography, Geoinformatics +17
Spatial cross-validation is not the right way to evaluate map accuracy
Alexandre M.J.‐C. Wadoux, G.B.M. Heuvelink, Sytze de Bruin et al. · Ecological Modelling · 2021 · 261 citations
Computing, Geography, Geoinformatics +12
1–5 of 87
307
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Leibniz Institute for Prevention Research and Epidemiology - BIPS, Germany
4 publications · 1.2K citations
4
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4
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1–5 of 307
189
Wageningen University & Research
Wageningen, The Netherlands
8 h-index
19 publications
2.5K citations

Bern University of Applied Sciences
Bern, Switzerland
5 h-index
5 publications
1.2K citations

Centre National de la Recherche Scientifique
Paris, France
4 h-index
12 publications
1K citations
Leibniz Institute for Prevention Research and Epidemiology - BIPS
Bremen, Germany
4 h-index
4 publications
1.2K citations
University of Münster
Münster, Germany
4 h-index
9 publications
389 citations
52°North Spatial Information Research
Münster, Germany
3 h-index
3 publications
1.2K citations

University of British Columbia
Vancouver, Canada
3 h-index
5 publications
184 citations
Humboldt-Universität zu Berlin
Berlin, Germany
3 h-index
4 publications
273 citations
1–8 of 189
9 publications · 369 citations
8
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3 publications · 1.2K citations
3
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3 publications · 255 citations
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JAG · 2 publications · 225 citations
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2 publications · 85 citations
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1–5