Urban resilience evaluates systems’ capacities to prepare for, adapt to, absorb, and recover from disruptions. Evaluation frameworks incorporate metrics like recovery speed, adaptive ability, and absorptive capacity. Assessing critical infrastructure interdependencies is challenging yet vital to limit failure propagation. While static assessments, multi-layer frameworks, and software like Hazus are used, limitations persist. Machine learning often focuses on infrastructure data for recovery monitoring. A common workflow entails acquiring and o...
