Abstract

Malaysia is one of the countries in the world experiencing landslides yearly due to natural events and human activities. Penang Island is Malaysia’s second most developed state and the largest by population. It is prone to landslides with devastating environmental impacts. Hence, the need to characterize its near-surface soil-rock conditions. This study uses remotely sensed data via frequency ratio (FR) techniques to identify landslide-prone areas based on different categories of landslide causative factors. To further understand the conditions and hydrodynamics of the soil-rock profiles causing landslides, electrical resistivity tomography and seismic refraction tomography were carried out at a landslide-suspected section in the study area. Also, the satellite-derived Bouguer gravity anomaly modeling was performed to map the varied gravity anomalies associated with landslide-triggering factors in lithologic units. The multi-geophysical models offer strongly correlated results with the causative remote sensed maps and the landslide susceptibility index (LSI) map. The likelihood of landslides occurring in the area, as suggested by the area under curve modeling of LSI data, yielded a high predicted success rate of 83.47%. Hence, prospective landslides were identified at the hilly and elevated sections, while the less susceptible sections were identified on flat reliefs. Landslides may also be triggered, for instance, at steep sections with varied contractive soil bodies and shallow structures. Most importantly, leveraging the LSI map would help the necessary agencies to forestall and mitigate future landslide occurrences in the area.

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