500m gridded surfaces for changes in climate suitability for coffee production in Risaralda, Colombia
We used 500m gridded historical and future climate surfaces for Risaralda, Colombia and coffee presences and absences to train species distribution models (suitability). Five methods were used: Generalized Boosting Model (GBM) (Friedman, 2001), Random Forest (RF) (Breiman, 2001), Maxent (Phillips et al., 2006), Generalized Linear Model (GLM) and Generalized Additive Model (GAM) (Guisan et al., 2002).
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Main Authors: | Vallejo Arango, Eliana, Navarro Racines, Carlos Eduardo, Ramírez Villegas, Julián, Aguilar-Ariza, Andrés, Delerce, Sylvain Jean |
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Format: | Dataset biblioteca |
Language: | English |
Published: |
2017-12-15
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Subjects: | suitability, coffee, machine learning, climate change, agriculture, |
Online Access: | https://hdl.handle.net/10568/89764 https://doi.org/10.7910/DVN/FEEHQX |
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