Optimal School Site Selection with a Risk-Reduction Approach: Integration of GIS and Multi-Criteria Decision-Making Methods

Abstract

The objective of this study was to develop a comprehensive model for safe school site selection against natural hazards by integrating GIS with multi-criteria decision-making techniques. This descriptive–analytical study applied an MCDA-based methodology. Data were collected using an ANP pairwise comparison questionnaire completed by 35 experts in architecture, urban planning, and disaster management. Data validity was examined using KMO and Bartlett’s tests, followed by EFA and CFA analyses. ANP was used to determine criterion weights, TOPSIS was employed to rank the urban blocks, and GIS was utilized to spatially integrate and map the final priorities. The KMO value of 0.64 and the significant Bartlett test (p<0.01) confirmed the adequacy of the data for factor analysis. Pearson correlation analysis indicated a non-significant linear relationship between the two main factors (p=0.34). EFA extracted a two-factor structure with acceptable loadings. TOPSIS results ranked Block A (0.7336) and Block D (0.7220) as top priorities, while Block B (0.2032) had the lowest priority. GIS-based spatial integration revealed meaningful clustering patterns of TOPSIS scores, indicating non-random spatial distribution of suitability levels. The findings underscore that school site selection must extend beyond technical considerations and incorporate spatial, demographic, and architectural criteria. The integration of GIS with MCDA methods provided a precise spatial prioritization framework and offered a practical model for designing resilient school environments capable of supporting both daily educational functions and emergency response needs.