Community-Driven Risk Assessment: Integrating Local Perceptions into Quantifiable Risk Weights Using Analytical Hierarchy Process (AHP)-Geographical Information System (GIS)

This study integrates the Analytical Hierarchy Process (AHP) and Geographic Information System (GIS) to assess community flood risk in Maidipur, Kurigram, Bangladesh an area frequently affected by monsoon flooding. By combining community-based hazard and vulnerability indicators and satellite-derived hydrological, meteorological, and geological data, the research develops a Community Risk Map to identify and categorize hazard-prone zones. Fourteen indicators were ranked and weighted using AHP to generate hazard and vulnerability indices, which were then spatially overlaid in GIS to produce a composite flood risk map. Network also applied to identify optimal evacuation routes and assembly points based on shortest time travel and distance, avoid risk zone. Traditionally, practitioners relied on community perception and a limited set of factors for risk mapping. This study advances that approach by aligning local knowledge with scientific analysis, achieving a high accuracy rate (96.88%) validated through field visits and community engagement… The findings offer evidence- based insights for flood preparedness, shelter placement, and community resilience planning under the Disaster Risk Management framework.