With advancements in sensor and geospatial technologies, capturing spatiotemporal changes in and to the built environment under different conditions is no longer a challenge. Given the dynamic nature of human and natural systems, understanding the cause and effect of changes to and in the built environment still remains an area of active research. This ORNL research group develops novel datasets, models, algorithms and tools using spatial and aspatial static and dynamic datasets to analyze, visualize and forecast interactions between natural systems, social systems and the built environment resulting from climate-induced and anthropogenic extreme events. The group has multi-disciplinary expertise ranging from Geographic Information Science, spatiotemporal analytics, multi-scale modeling, econometrics modeling, logistics and network flow optimization, remote sensing, and geo-visualization. With funding from NGA, DHS, DoE and NASA, the group supports national and homeland security missions such as community and infrastructure resilience, risk and vulnerability assessment, environmental and energy justice issues, supply chain logistics and land use/cover change.
To foster research innovation, data creation, algorithm and information system development to forecast and provide situational awareness about risk and resilience of the built environment to extreme events as well as resulting from interactions with natural and social systems.
Be a recognized leader in modeling risk and resilience of the built environment and providing situational awareness information to achieve equitable, reliable and adaptable built environment to meet climate change impacts and national security needs.