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

Volume: 730, Pages: 139197 - 139197
Published: Aug 1, 2020
Abstract
Rapid population growth and its corresponding effects like the expansion of human settlement, increasing agricultural land, and industry lead to the loss of forest area in most parts of the world especially in such highly populated nations like India. Forest canopy density (FCD) is a useful measure to assess the forest cover change in its own as numerous works of forest change have been done using only FCD with the help of remote sensing and...
Paper Details
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
Published Date
Aug 1, 2020
Volume
730
Pages
139197 - 139197
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