A Random Forest-Cellular Automata Modeling Approach to Predict Future Forest Cover Change in Middle Atlas Morocco, Under Anthropic, Biotic and Abiotic Parameters

This study aims to predict forest species cover changes in the Sidi M’Guild Forest (Mid Atlas, Morocco). Used approach combines remote sensing and GIS and is based on training Cellular Automata and Random Forest (RF) regression model for predicting species cover transition. Five covariates that prec...

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Detalles Bibliográficos
Autores principales: Legdou, Anass, Chafik, Hassan, Amine, Aouatif, Lahssini, Said, Berrada, Mohamed
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2020
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7340914/
http://dx.doi.org/10.1007/978-3-030-51935-3_10

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7340914/
http://dx.doi.org/10.1007/978-3-030-51935-3_10

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