A review of landslide conditioning factors in tropical forests

A variety of natural and human-induced factors can trigger landslides. A combination of these factors, with several key factor characteristics, may increase the risk of landslides. This paper aims to review comprehensive conditioning factors that contribute to landslide occurrence. Landslide occurre...

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Bibliographic Details
Main Authors: Kamarudin, Norizah, Abdul Whab @ Abdul Wahab, Zulfa, Jasni, Ahmad Syakir, Mohd Razali, Sheriza, Jamaluddin, Jamhuri, Abu Bakar, Siti Nurhiday, Abdul Hamid, Hazandy, Saverinus, Bate, Law, Tze Ding, Parman, Rhyma Purnamasayangsukasih
Format: Article
Language:English
Published: Universiti Putra Malaysia, Universiti Pertanian Malaysia Press 2024
Online Access:http://psasir.upm.edu.my/id/eprint/119294/
http://psasir.upm.edu.my/id/eprint/119294/1/119294.pdf
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Summary:A variety of natural and human-induced factors can trigger landslides. A combination of these factors, with several key factor characteristics, may increase the risk of landslides. This paper aims to review comprehensive conditioning factors that contribute to landslide occurrence. Landslide occurrence varied with the conditioning factors and has been documented in response to the need to understand and mitigate the risks associated with these natural events. 26 conditioning factors have been identified on landslide occurrence from 16 articles reviewed using systematic literature review with PRISMA guidelines. All 16 articles study landslides: Malaysia (66% of the article), Indonesia (13% of the article), Vietnam, Philippines and Brazil (7% of the article for each country) mostly applied the conditioning factors for landslides susceptibility map modelling. The discussion of this work focuses on the conditioning factor of landslides in tropical forests. This study is crucial in improving risk assessment and developing effective mitigation and management strategies. In addition, the information from this study can be used in future studies to develop and validate models that simulate landslide processes under different conditions and are essential for predicting potential landslide events and their impacts.