Landslide susceptibility assessment in Sabah, Malaysia: A bivariate frequency ratio approach
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Abstract
A statistical bivariate model, frequency ratio, was used to assess the susceptibility of Pekan Nabalu to Kundasang area to landslides, using a geographic information system as a tool because the number of reported landslide cases rises annually. A total of 564 landslides (0.27 km2) were detected from field observations, Google Earth satellite imagery, and IFSAR imagery, creating a landslide inventory map (dependent factor). To determine landslide susceptibility, eight landslide causative factor maps (independent factor) were considered: slope angle, slope aspect, slope curvature, drainage proximity, lineament proximity, lithology, land use, and soil series. The integration of these dependent and independent factors resulted in a regional-scale spatial landslide susceptibility analysis (LSA) map with five susceptibility classes. Approximately 11.39% (12.99 km2), 25.56% (29.14 km2), 29.67% (33.82 km2), 23.6% (26.9 km2), and 9.78% (11.15 km2) are classified as very low, low, moderate, high, and very high susceptibility classes, respectively. Using the area under the curve validation method, the prediction and success rates were 82.63% and 82.6%, respectively. The LSA map is considered reliable because 239 landslides (0.14 km2) were classified as high to very high susceptibility classes. Therefore, this study provides valuable insights for stakeholders, researchers, and professionals, facilitating the proposal of suitable mitigation measures and the development of robust landslide management plans.
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