GIS-Based Landslide Susceptibility Mapping Using Weighted Overlay Method in East Suwawa Timur District, Bone Bolango Regency

Merlin; Sri  Maryati; Masruroh

doi:10.63922/ijevss.v5i03.4755

Merlin Merlin Geography Education Program, Faculty of Mathematics and Natural Sciences, Gorontalo State University, Gorontalo, Indonesia
Sri Maryati Merlin Geography Education Program, Faculty of Mathematics and Natural Sciences, Gorontalo State University, Gorontalo, Indonesia
Masruroh Merlin Geography Education Program, Faculty of Mathematics and Natural Sciences, Gorontalo State University, Gorontalo, Indonesia

DOI: https://doi.org/10.63922/ijevss.v5i03.4755

Keywords: GIS; Landslide Susceptibility; Weighted Overlay; Spatial Analysis; Disaster Mitigation

Abstract

Landslides are among the most frequent hydrometeorological disasters in Indonesia, particularly in hilly regions characterized by high rainfall intensity and unstable land conditions. East Suwawa District, Bone Bolango Regency, is characterized by mountainous terrain, intensive land-use activities, and recurring landslide events, making landslide susceptibility assessment essential for disaster mitigation and spatial planning. Previous studies have predominantly focused on landslide susceptibility mapping at broader regional scales, while detailed spatial analysis at the district level remains limited. Therefore, this study aims to map landslide susceptibility in East Suwawa District using a Geographic Information System (GIS)-based Weighted Overlay Method. The analysis incorporated five parameters, namely rainfall, slope, land use, soil type, and geological conditions. Spatial data were weighted according to their influence on landslide occurrence and subsequently integrated through overlay analysis to generate a landslide susceptibility map. The results reveal four susceptibility classes: low (0.13%), moderate (43.53%), high (55.75%), and very high (0.58%). High susceptibility areas dominate the district, particularly in the hilly regions of Tulabolo, Tulabolo Barat, and Tulabolo Timur villages. These findings provide important spatial information for disaster risk reduction, land-use planning, and sustainable regional development in landslide-prone areas.

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