Predicting habitat suitability with machine learning models: The potential area of Pinus sylvestris L. in the Iberian Peninsula

Ecological Modelling

Volumn 197, Issue 3-4, 2006, Pages 383-393

  Garzón, Marta Benito ^a   Blazek, Radim ^b   Neteler, Markus ^b   Dios, Rut Sánchez de ^a   Ollero, Helios Sainz ^a   Furlanello, Cesare ^b  

^a UNIVERSIDAD AUTÓNOMA DE MADRID   (Spain)

^b ITC IRST   (Italy)

Author keywords

AUC; Classification and regression trees; Habitat suitability; Iberian Peninsula; Kappa; Machine learning; Neural networks; Pinus sylvestris L.; Random forest

Indexed keywords

ALGORITHMS; FORESTRY; GEOGRAPHIC INFORMATION SYSTEMS; MATHEMATICAL MODELS; NEURAL NETWORKS;

AUC; CLASSIFICATION AND REGRESSION TREES; HABITAT SUITABILITY; IBERIAN PENINSULA; KAPPA; PINUS SYLVESTRIS L.; RANDOM FORESTS;

LEARNING SYSTEMS;

ALGORITHM; CLIMATE MODELING; FOREST COVER; GIS; HABITAT SELECTION; TOPOGRAPHY;

ALGORITHMS; FORESTRY; GIS; MATHEMATICAL MODELS; NEURAL NETWORKS;

EURASIA; EUROPE; IBERIAN PENINSULA; SOUTHERN EUROPE;

PINUS SYLVESTRIS;

EID: 33746317317     PISSN: 03043800     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.ecolmodel.2006.03.015     Document Type: Article

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