A Systematic review of machine learning based landslide susceptibility mapping

  • Semachew Molla Kassa Department of Civil Engineering, College of Engineering and Technology, Wachemo University, Ethiopia
Keywords: Landslide, Landslide susceptibility mapping, Machine learning

Abstract

The landslide problem is one type of geohazard which damages both economic and human life loss. This problem needs awareness and creating zonation’s to prevent its effect. This study reviews in locations Brazil, India, China, Italy, Turkey, Denmark, Vietnam, Iran, Bhutan, Pakistan, Peru, and Ecuador. These countries are facing landslide problems because their topography is more hilly terrain types. During the studies, different criteria are set to review articles published in the last 5 years from 2018 to June 9, 2023. The research is more focused on a machine learning model to map landslide problems in these selected areas. A field survey is used to validate this landslide susceptible mapping results. Future researchers utilizing machine learning methods to map the area's susceptibility to landslides will benefit from this research. Deep learning and ensembled machine learning will give good results for more datasets.

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Published
2024-06-19
How to Cite
Kassa, S. (2024). A Systematic review of machine learning based landslide susceptibility mapping. Journal of Road and Traffic Engineering, 70(2), 23-30. https://doi.org/10.31075/PIS.70.02.03