Landslide susceptibility modeling using a hybrid bivariate statistical and expert consultation approach in Canada Hill, Sarawak, Malaysia

Daniel, Marelyn Telun and Ng, Tham Fatt and Abdul Kadir, Mohd. Farid and Pereira, Joy Jacqueline (2021) Landslide susceptibility modeling using a hybrid bivariate statistical and expert consultation approach in Canada Hill, Sarawak, Malaysia. Frontiers in Earth Science, 9. ISSN 2296-6463, DOI https://doi.org/10.3389/feart.2021.616225.

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Abstract

Landslide susceptibility assessment was conducted in Canada Hill, Sarawak, Malaysia through a combined bivariate statistics and expert consultation approach using geographical information system, which captures landslide-conditioning parameters specific to the study area; to ensure its usefulness in practice. Over the past four decades, many landslide parameters and increasingly sophisticated statistical methods have been used in landslide research. However, the findings have had very limited use in practice as the actual ground conditions are not well represented. The weakness is due to poor quality of data in landslide inventories and inadequate understanding of landslide-conditioning parameters. In this study, bivariate statistical method was used in conjunction with an iterative process of expert consultation. Thirteen original landslide-conditioning parameters were narrowed down to six, with the addition of a unique parameter, planar failure potential, which was selected based on expert input. The parameter captures planar failure landslides, which has the highest impact in the study area, causing loss of lives and property destruction. The inaugural landslide susceptibility map for the study area has five classes; very low, low, moderate, high and very high susceptibility. All major planar failures and most smaller circular failures fall within the very high susceptibility class, with a success rate of 75.8%. The approach used in this study has improved the quality of the landslide inventory and delineated key conditioning parameters. The resultant map captures local conditions, which is useful for landslide management.

Item Type: Article
Funders: Newton-Ungku Omar Fund (59348-455144), UM project (IF002-2017), UKM project (XX-2017-002)
Uncontrolled Keywords: Bivariate statistics; Expert consultation; Landslide-conditioning parameter; Landslide susceptibility; Geographic information system; Malaysia
Subjects: Q Science > QE Geology
Divisions: Faculty of Science > Department of Geology
Depositing User: Ms. Juhaida Abd Rahim
Date Deposited: 15 Mar 2022 08:16
Last Modified: 15 Mar 2022 08:16
URI: http://eprints.um.edu.my/id/eprint/26535

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