Enhancing Flood Resilience: A GIS-Based Analysis of Evacuation Centre Site Suitability Cheah Wei Chee, Nurul Ashikin Bte Mabahwi
Universiti Sains Malaysia
Abstract
Flooding is one of the most frequent and destructive natural hazards affecting Southeast Asia, particularly in low-lying urban areas such as Kuantan, Malaysia. The increasing intensity of flood events due to climate change and urban expansion underscores the urgent need for resilient infrastructure planning. This study aims to support disaster preparedness and enhance flood resilience by identifying optimal locations for evacuation centres using a GIS-based Multi-Criteria Evaluation (MCE) framework.
The methodology integrates remote sensing data, spatial analysis, and the Analytical Hierarchy Process (AHP) to assess land suitability. Key criteria include elevation, slope, proximity to disaster-prone areas, landslides, floods, river, and land use. Each layer was standardized, weighted based on literature review, and combined using a weighted overlay analysis in ArcGIS. The final suitability map classifies land into five categories: Extremely Suitable, Very Suitable, More Suitable, Moderately Suitable, and Less Suitable.
Results indicate that among the 127 evacuation centres evaluated, 31.50% were categorized as Less Suitable, 7.09% as Moderately Suitable, 19.69% as More Suitable, 26.77% as Very Suitable, and 14.96% as Extremely Suitable, and. These findings reveal a limited distribution of highly suitable areas, highlighting the importance of integrating geospatial hazard data with topographic constraints in planning decisions.
This research demonstrates the practical application of remote sensing and GIS in improving urban flood resilience and emergency response planning. It contributes to Sustainable Development Goals by supporting inclusive, safe, and disaster-resilient infrastructure (SDG 11) and promoting climate adaptation strategies (SDG 13). The study offers a transferable and scalable approach that can benefit disaster-prone regions across Asia, aligning with the broader goals of advancing remote sensing science for sustainable development.
