We develop and apply cutting-edge methods for analyzing spatial and space-time data from GPS-enabled devices, satellites, drones, sensor networks, and administrative records. Our approaches are often dynamic, multiscalar, place-based, and context-aware. Application areas include modeling of vegetation change, human mobility, environmental hazards and exposures, climate change impacts, transportation processes, and health and wellbeing.
Faculty working in Space-Time Analytics
- Congratulations to PhD student Lirong Kou (advisor: Prof. Mei-Po Kwan) on winning the 2019 Robert Ferber Dissertation Award!