Machine learning methods for landslide susceptibility studies: A comparative overview of algorithm performance

2020/06/03 by Abdelaziz Merghadi, Ali P. Yunus, Jie Dou +7 · 2 citations
Environmental Science · #Fire effects on ecosystems #Flood Risk Assessment and Management #Landslides and related hazards

paper · doi:10.1016/j.earscirev.2020.103225

openalex publication_date 2020/06/03 · crossref created 2020/06/03 · crossref issued 2020/08/01 · crossref published 2020/08/01 · crossref published-print 2020/08/01 · openalex created_date 2025/10/10 · crossref deposited 2025/11/02 · crossref indexed 2026/07/30 · openalex updated_date 2026/08/02

Citations

• A Decision-Theoretic Generalization of On-Line Learning and an Application to Boosting
• Collinearity: a review of methods to deal with it and a simulation study evaluating their performance
• The Lack of A Priori Distinctions Between Learning Algorithms
• Landslide hazard evaluation: a review of current techniques and their application in a multi-scale study, Central Italy
• The Measurement of Observer Agreement for Categorical Data

Cited by

• On the importance of both climate and vegetation evolution when predicting long-term wildfire susceptibility
• Landslide susceptibility of Rwanda (Central Africa)