Design a system to assess how street networks withstand disruptions like floods or earthquakes, by simulating edge removals and measuring connectivity loss (e.g., via giant component size or detour lengths). Source network data from free repositories like OpenStreetMap, and incorporate vulnerability layers from elevation models. Use Python with OSMNX and NetworkX for robustness algorithms and spatial visualization. Test on case studies (e.g., coastal cities prone to flooding), evaluate recovery strategies like redundant paths, and provide policy recommendations for resilient infrastructure. This project combines network theory with disaster management.