New Ensemble Models for Shallow Landslide Susceptibility Modeling in a Semi-Arid Watershed

New Ensemble Models for Shallow Landslide Susceptibility Modeling in a Semi-Arid Watershed

We prepared a landslide susceptibility map for the Sarkhoon watershed, Chaharmahal-w-bakhtiari, Iran, using novel ensemble artificial intelligence approaches. A classifier of support vector machine (SVM) was employed as a base classifier, and four Meta/ensemble classifiers, including Adaboost (AB),...

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Bibliographic Details
Main Authors: Dieu Tien Bui, Ataollah Shirzadi, Himan Shahabi, Marten Geertsema, Ebrahim Omidvar, John J. Clague, Binh Thai Pham, Jie Dou, Dawood Talebpour Asl, Baharin Bin Ahmad, Saro Lee
Format: Article
Language:English
Published: MDPI AG 2019-08-01
Series:Forests
Subjects:
shallow landslide
machine learning
goodness-of-fit
factor selection
GIS
Iran
Online Access:https://www.mdpi.com/1999-4907/10/9/743

Internet

https://www.mdpi.com/1999-4907/10/9/743

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