Model-based Spatial Sampling
Model-Based Spatial Sampling is a spatial sampling paradigm that relies on an explicit statistical or mathematical model of the underlying spatial process to guide the selection and inference of sample locations, distinguishing it from design-based approaches by incorporating assumed spatial dependence structures.
32
Publications
2.3K
Citations
109
Authors
69
Institutions
Publications per year
2017–2026
8
Parents
32
Using Niche‐Based Models to Improve the Sampling of Rare Species
Antoine Guisan, Olivier Broennimann, Robin Engler et al. · Conservation Biology · 2006 · 518 citations
Prospective sampling based on model ensembles improves the detection of rare species
Gwenaëlle Le Lay, Robin Engler, Erika Franc et al. · Ecography · 2010 · 97 citations
1–5 of 32
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NOAA National Marine Fisheries Service Alaska Fisheries Science Center, United States
2 publications · 100 citations
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2
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1–5 of 109
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Wageningen University & Research
Wageningen, The Netherlands
3 h-index
4 publications
130 citations

University of St Andrews
St Andrews, United Kingdom
2 h-index
5 publications
759 citations
Environmental Protection Agency
Washington, United States
2 h-index
6 publications
346 citations
Institut Polytechnique de Bordeaux
Bordeaux, France
1 h-index
3 publications
105 citations

Australian National University
Canberra, Australia
1 h-index
2 publications
72 citations
Cox & Company (United States)
Plainview, United States
1 h-index
1 publications
25 citations
University of Cape Coast
Cape Coast, Ghana
1 h-index
1 publications
32 citations
Université d'Abomey-Calavi
Cotonou, Benin
1 h-index
1 publications
32 citations
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JABES · 2 publications · 360 citations
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2 publications · 34 citations
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2 publications · 420 citations
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2 publications · 69 citations
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1 publications · 15 citations
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