Abstract Identifying and determining the temporary shelter areas to be used after an earthquake is essential for natural disaster management and planning. This study aims to develop an innovative decision support model that considers spatial, geological, and socio-economic factors to determine the most suitable locations for post-disaster temporary shelter areas in earthquake-prone areas selected as a case study. The model and framework are aligned with the Sendai Framework for Disaster Risk Reduction (2015–2030), which emphasizes disaster preparedness, risk governance, and resilience building. Within disaster management and planning, the analytical hierarchy process (AHP) method evaluated eleven geographical criteria that experts determined. Integrated Geographic Information Systems (GIS) and Multi-Criteria Decision Analysis (MCDM) determined temporary shelter areas. The reliability and robustness of the model were tested with sensitivity analysis. The study shows that the applied model effectively determines the suitability of temporary shelter areas after an earthquake. The MCDA and sensitivity analysis of the model highlight the impact of different geographical criteria on site selection, providing a systematic approach to disaster preparedness. The study also reveals that spatial decision support models have significant potential to enhance resilience and optimize disaster management strategies. By integrating decision-making with geospatial analysis, the model provides actionable insights for disaster planning and management. Furthermore, the model has been developed as a replicable tool for regional and international disaster response strategies. In addition, it has contributed to sustainable urban planning and increasing global resilience to seismic hazards.
Kızılkan et al. (Tue,) studied this question.