Cities are complex systems with interconnected “lifeline networks” enabled by critical infrastructure, which can be severely damaged or destroyed in the aftermath of a natural disaster. Following Hurricanes Maria and Katrina and the Tōhoku earthquake and tsunami, for example, damage to critical systems resulted in cascading effects that severely impeded recovery and crippled regional economies. Geographic information system data gives the location of critical infrastructure (CI) and can be used to identify and mitigate damage, but in many cases the locations of key components are unmapped or unshared, particularly in developing countries.

Without pinpointing the physical location of key assets, it is not possible to identify where the regional risk from infrastructure disruption can lead to cascading damage that, in some cases, could significantly reverse progress in developing countries. This project builds on previous work to expand the ability to model the catastrophic impacts of infrastructure disruption by providing a foundation for CI exposure development in concert with remote-sensing Earth observations made via satellite. 

The project team will begin its work in India, and expand to developing countries globally, prioritizing based on end-user requirements. As with buildings, identifying lifeline networks is a data-fusion process requiring collection of existing datasets and use of segmentation and edge-detection algorithms. Data will be delivered openly and globally to developing countries and all those interested in risk, as well as integrated into commercial products for global risk identification and management.