500m gridded surfaces for changes in climate suitability for coffee production in Risaralda, Colombia

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dc.creatorVallejo Arango, Eliana
dc.creatorNavarro Racines, Carlos Eduardo
dc.creatorRamírez Villegas, Julián Armando
dc.creatorAguilar-Ariza, Andrés
dc.creatorDelerce, Sylvain Jean
dc.date2017-12-15
dc.date2017-12-15T18:54:48Z
dc.date2017-12-15T18:54:48Z
dc.date.accessioned2026-06-27T14:34:14Z
dc.descriptionWe 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).
dc.identifierhttps://hdl.handle.net/10568/89764
dc.identifier.urihttp://hdl.handle.net/123456789/81998
dc.languageen
dc.rightsOpen Access
dc.sourceVallejo-Arango, Eliana ; Navarro-Racines, Carlos E.; Ramirez-Villegas, Julian; Aguilar-Ariza, Andres; Delerce, Sylvain Jean, 2017, "500m gridded surfaces for changes in climate suitability for coffee production in Risaralda, Colombia", doi:10.7910/DVN/FEEHQX, Harvard Dataverse, V1
dc.subjectsuitability
dc.subjectcoffee
dc.subjectmachine learning
dc.subjectclimate change
dc.subjectagriculture
dc.title500m gridded surfaces for changes in climate suitability for coffee production in Risaralda, Colombia
dc.typeDataset

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Centro Internacional de Agricultura Tropical (CIAT)