Spatial cross-validation is not the right way to evaluate map accuracy
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DOI: 10.1016/j.ecolmodel.2021.109692
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- Diana Koldasbayeva & Polina Tregubova & Mikhail Gasanov & Alexey Zaytsev & Anna Petrovskaia & Evgeny Burnaev, 2024. "Challenges in data-driven geospatial modeling for environmental research and practice," Nature Communications, Nature, vol. 15(1), pages 1-16, December.
- Hanna Meyer & Edzer Pebesma, 2022. "Machine learning-based global maps of ecological variables and the challenge of assessing them," Nature Communications, Nature, vol. 13(1), pages 1-4, December.
- Daniel S. Maynard & Lalasia Bialic-Murphy & Constantin M. Zohner & Colin Averill & Johan Hoogen & Haozhi Ma & Lidong Mo & Gabriel Reuben Smith & Alicia T. R. Acosta & Isabelle Aubin & Erika Berenguer , 2022. "Global relationships in tree functional traits," Nature Communications, Nature, vol. 13(1), pages 1-12, December.
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Keywords
Map quality; Model performance; Above-ground biomass; Sampling theory; Design-based; Model-based; Random forest; Design-unbiased;All these keywords.
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