Gully erosion susceptibility mapping (GESM) using machine learning methods optimized by the multi‑collinearity analysis and K-fold cross-validation

Gully erosion susceptibility mapping (GESM) using machine learning methods optimized by the multi‑collinearity analysis and K-fold cross-validation

Gully erosion is a severe form of soil erosion that results in a wide range of environmental problems such as, dams’ sedimentation, destruction of transportation and energy transmission lines, decreasing and losing farmland productivity, and land degradation. The main objective of this study is to a...

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Bibliographic Details
Main Authors: Omid Ghorbanzadeh, Hejar Shahabi, Fahimeh Mirchooli, Khalil Valizadeh Kamran, Samsung Lim, Jagannath Aryal, Ben Jarihani, Thomas Blaschke
Format: Article
Language:English
Published: Taylor & Francis Group 2020-01-01
Series:Geomatics, Natural Hazards & Risk
Subjects:
soil erosion
spatial modeling
artificial neural networks (ann)
random forest (rf)
Online Access:http://dx.doi.org/10.1080/19475705.2020.1810138

Internet

http://dx.doi.org/10.1080/19475705.2020.1810138

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