A team of students, collaborating with Professors Mike Bergin, David Carlson, and PhD Candidate Zach Calhoun developed a modeling approach to estimate heat stress in urban areas. Students will further develop a dataset consisting of high-resolution temperature and relative humidity observations in over 60 cities (https://www.heat.gov/pages/mapping-campaigns), satellite imagery and meteorological data. They then developed a deep learning-based approach to estimate heat stress in locations without observations. This research will provide us with an understanding of the extent to which existing datasets are sufficient to assess heat stress in urban areas.
Project Leads: Mike Bergin and David Carlson, CEE
Project Manager: Zach Calhoun
View the team’s final poster here
Watch the team discuss this project in the videos below:
