Extreme events such as floods, landslides, wildfires, and pandemics pose a significant risk to transportation systems and public health. The state of North Carolina is particularly fragile to these events. Such events have led to road closures, travel delays, and other disruptions and resulted in substantial economic and labor cost, especially impacting freight movement due to necessary re-routing operations. Given the increasing frequency and severity of such events, there is an urgent need to understand their potential impact on the NC transportation infrastructure, particularly regarding the risks of road closures affecting freight routing.
To address these challenges, we developed a state-of-the-art geospatially explicit analytics platform, termed as “Geo-FRIT,” for the analytics of transportation risks and resilience. We collected and processed data as required in this framework, including extreme events, transportation assets, environmental, and socio-economic data. Then, transportation resilience of NC roadway system was estimated. The Geo-FRIT framework supports risk-based routing analysis and spatial simulation-based scenario analysis, providing integrated advanced freight routing modeling capabilities. We developed a web GIS dashboard for the management, analytics, and mapping of resilience-related data. This dashboard greatly facilitates the sharing and dissemination of spatially explicit transportation resilience results. Our findings include: 1) Efficient geoprocessing and integration of diverse data related to extreme events with transportation asset warrant the feasibility for transportation resilience analysis. 2) Specific approaches or models need to be developed for threat likelihood modeling of alternative types of extreme events, depending on data availability and the driving mechanisms of extreme events. 3) Automated handling of routing analysis and pre-/post- data processing are of great help for detour analysis as required by transportation risk estimation. 4) The Geo-FRIT framework holds great potential in the resilience analysis of alternative transportation networks and provides spatial decision support for stakeholders in terms of transportation planning or management in need of explicit consideration of resilience in response to various types of extreme events.
