Journal of Geographic Information System
Vol.7 No.2(2015), Paper ID 55798, 9
pages
DOI:10.4236/jgis.2015.72017
Predicting Cork Oak Suitability in Maâmora Forest Using Random Forest Algorithm
Said Lahssini, Hicham Lahlaoi, Hicham Mharzi Alaoui, El Aid Hlal, Martino Bagaram, Quentin Ponette
National School of Forestry Engineering, Salé, Morocco
Geosciences Laboratory, Faculty of Sciences Ain Chock, Hassan II University, Casablanca, Morocco
Institut of Agronomy and Veterinary Hassan II, Rabat, Morocco
National School of Forestry Engineering, Salé, Morocco
National School of Forestry Engineering, Salé, Morocco
Catholic University of Louvain, Louvain la Neuve, Belgium
Copyright © 2015 Said Lahssini, Hicham Lahlaoi, Hicham Mharzi Alaoui, El Aid Hlal, Martino Bagaram, Quentin Ponette et al. This is
an open access article distributed under the Creative Commons Attribution
License, which permits unrestricted use, distribution, and reproduction in any
medium, provided the original work is properly cited.
How to Cite this Article
Lahssini, S. , Lahlaoi, H. , Alaoui, H. , Hlal, E. , Bagaram, M. and Ponette, Q. (2015) Predicting Cork Oak Suitability in Maâmora Forest Using Random Forest Algorithm.
Journal of Geographic Information System,
7, 202-210. doi:
10.4236/jgis.2015.72017.