The multispectral separability of Costa Rican rainforest types with support vector machines and Random Forest decision trees

Steven E. SesnieDepartment of Forest Resources, PO Box 441133, University of Idaho, Moscow, ID, 83844-1133, USA;Centro Agronómico Tropical de Investigación y Enseñanza (CATIE), Turriabla7170, Costa RicaCorrespondence[email protected]

Bryan FineganCentro Agronómico Tropical de Investigación y Enseñanza (CATIE), Turriabla7170, Costa Rica

Paul E. GesslerDepartment of Forest Resources, PO Box 441133, University of Idaho, Moscow, ID, 83844-1133, USA;Geospatial Laboratory for Environmental Dynamics, University of Idaho, Moscow, ID, 83844, USA

Sirpa ThesslerFinnish Forest Research Institute (Metla), Unioninkatu 40 A, 00170Helsinki, Finland

Zayra Ramos BendanaCentro Agronómico Tropical de Investigación y Enseñanza (CATIE), Turriabla7170, Costa Rica

Alistair M. S. SmithDepartment of Forest Resources, PO Box 441133, University of Idaho, Moscow, ID, 83844-1133, USA;Geospatial Laboratory for Environmental Dynamics, University of Idaho, Moscow, ID, 83844, USA

The multispectral separability of Costa Rican rainforest types with support vector machines and Random Forest decision trees

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The multispectral separability of Costa Rican rainforest types with support vector machines and Random Forest decision trees

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