Assessment on Recent Landslide Susceptibility Mapping Methods: A Review

Landslide is a destructive natural hazard that causes severe property loss and loss of lives. Numerous researchers have developed landslide susceptibility maps in order to forecast its occurrence, particularly in hill-site development. Various quantitative approaches are used in landslide susceptibi...

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Bibliographic Details
Published in:IOP conference series. Earth and environmental science 2022-01, Vol.971 (1), p.12032
Main Authors: Manan, W A A, Rashid, A S A, Abdul Rahman, M Z A, Khanan, M F A
Format: Article
Language:English
Subjects:
Data mining
Landslides
Machine learning
Slope stability
Stability analysis
Support vector machines
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Summary:Landslide is a destructive natural hazard that causes severe property loss and loss of lives. Numerous researchers have developed landslide susceptibility maps in order to forecast its occurrence, particularly in hill-site development. Various quantitative approaches are used in landslide susceptibility map production, which can be classified into three categories; statistical data mining, machine learning and deterministic approach. In this paper, we choose two regular models in each category, which are Weight of Evidence (WoE) and Frequency Ratio (FR), Artificial Neutral Networks (ANN) and Support Vector Machines (SVM), Shallow Landsliding Stability Model (SHALSTAB) and YonSei-Slope (YS-Slope). Discussion and assessment on these models are based on relevant literature.
ISSN:1755-1307
1755-1315
DOI:10.1088/1755-1315/971/1/012032