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).

Enregistré dans:
Détails bibliographiques
Auteurs principaux: Vallejo Arango, Eliana, Navarro Racines, Carlos Eduardo, Ramírez Villegas, Julián, Aguilar-Ariza, Andrés, Delerce, Sylvain Jean
Format: Dataset biblioteca
Langue:English
Publié: 2017-12-15
Sujets:suitability, coffee, machine learning, climate change, agriculture,
Accès en ligne:https://hdl.handle.net/10568/89764
https://doi.org/10.7910/DVN/FEEHQX
Tags: Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!