Post-earthquake recovery: GIS-driven prioritization of urban transportation networks in Sari, Iran

Rapid restoration of transportation networks is crucial for effective post-earthquake response, yet persistent challenges hinder network optimization due to factors compromising functionality. This study introduces an innovative framework combining GIS and MCDA to evaluate and prioritize the reopening of urban transportation networks affected by earthquakes. Applied to Sari, Iran, the methodology identified 1 319 priority edges, reducing selections seven-fold. The resulting emergency network prioritizes accessibility and functionality, ensuring strategic transportation for post-disaster response. The key innovation lies in using impedance derived from network dataset analysis based on optimized criteria weights, enabling the automated generation of an emergency network focused on the most accessible and functional routes. This integrated analytical approach, distinct from conventional isolated analyses, empowers authorities to optimize resource allocation for recovery by incorporating spatial, statistical, and accessibility indicators. Importantly, the multi-criteria decision-making approach applied in this study is adaptable and flexible, allowing users in different case studies to develop their own hierarchies and weights to suit specific local contexts. As seismic risks escalate amid rapid urbanization in vulnerable regions, this study contributes to strengthening urban transportation network resilience and earthquake preparedness. The versatile toolkit equips decision-makers to identify critical routes and facilitate rapid system restoration, mitigating earthquake impacts. This research emphasizes the need to enhance understanding of transportation network dynamics after seismic events and improve resilience and preparedness on both large and practical scales. Further validation across diverse urban landscapes is recommended to ensure the generalizability and robustness of the proposed framework.