Predicting the deforestation probability using the binary logistic regression, random forest, ensemble rotational forest, REPTree: A case study at the Gumani River Basin, India

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Title
Predicting the deforestation probability using the binary logistic regression, random forest, ensemble rotational forest, REPTree: A case study at the Gumani River Basin, India
Authors
Keywords
Forest canopy density, Deforestation, Machine learning algorithms, Probabilistic model, Ensemble model
Journal
SCIENCE OF THE TOTAL ENVIRONMENT
Volume 730, Issue -, Pages 139197
Publisher
Elsevier BV
Online
2020-05-05
DOI
10.1016/j.scitotenv.2020.139197

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