TY  - EJOU
AU  - Gacu, Jerome 
AU  - Cawaling, Dencel Edrian 
AU  - Fiestada, Edel Queen 
AU  - Maybanting, Diablell 
AU  - Bensurto, Jamica 
AU  - Falogme, John Kevin 
AU  - Fontamillas, Jea Janelle 
AU  - Gadon, Janellene Edd 
AU  - Fernandez, Samaica 
AU  - Sagario, Maryjay 

TI  - A Multi-Criteria GIS Approach to Landslide Risk Assessment: Application of FAHP in San Andres, Romblon, Philippines
T2  - Revue Internationale de Géomatique

PY  - 2026
VL  - 35
IS  - 1
SN  - 2116-7060

AB  - A landslide is the downslope movement of soil, rock, or debris driven by gravity, often triggered by natural or anthropogenic factors. The Philippines is highly susceptible to landslides due to its steep terrain, frequent typhoons, intense rainfall, and seismic activity, resulting in significant socioeconomic and environmental impacts. Despite increasing landslide occurrences in vulnerable coastal and mountainous municipalities in the Philippines, localized and integrated Geographic Information System (GIS)-based landslide risk assessments incorporating hazard, vulnerability, and exposure components remain limited in small island municipalities such as San Andres, Romblon. This study assesses landslide risk in the Municipality of San Andres, Romblon, using an integrated GIS and Fuzzy Analytic Hierarchy Process (FAHP) framework guided by the Sendai Framework for Disaster Risk Reduction to develop a comprehensive landslide risk assessment framework for localized disaster risk management and spatial planning. The study utilized the available multi-source geospatial, environmental, and socio-economic datasets spanning 2011–2024, including terrain, rainfall, land use, soil, and demographic information obtained from government agencies, remote sensing sources, and local community-based records. Risk was evaluated through three core components: hazard, vulnerability, and exposure. Hazard factors included soil type, landslide susceptibility, slope, elevation, and annual rainfall, while vulnerability incorporated socioeconomic and accessibility indicators. Exposure was represented by population, land use, household distribution, and proximity to evacuation facilities. Expert-based pairwise comparison was applied to derive parameter weights, with landslide susceptibility (34.98%) and distance to river (26.28%) identified as dominant hazard and vulnerability drivers, respectively, while land use/land cover (33.01%) and population density (32.93%) were the most influential exposure factors. The resulting landslide risk map revealed that 17.78% of the study area falls under very high risk, primarily concentrated in Marigondon Norte, Marigondon Sur, Victoria, and Matutuna. The findings provide a spatially explicit basis for targeted mitigation strategies, supporting local government units in implementing structural and non-structural interventions. This study demonstrates the effectiveness of GIS–FAHP integration in enhancing data-driven disaster risk reduction and resilience planning in landslide-prone regions.
KW  - Landslide; spatial analysis; disaster risk reduction; hazard; exposure; vulnerability; fuzzy logic; GIS

DO  - 10.32604/rig.2026.083180