Professor Jason Cao and PhD candidate Tao Tao were invited to present at the webinar: Spatial planning of low-carbon cities with machine learning, organized by Climate Change AI, on June 18, 2021. 

Climate Change AI (CCAI) is an organization composed of volunteers from academia and industry who believe that tackling climate change requires concerted societal action, in which machine learning can play an impactful role. 

This webinar focused on using machine learning approaches to analyze the influences of urban form on energy use and greenhouse gas (GHG) emissions, and looking for urban planning strategies that can reduce carbon footprint of cities.

Cao and Tao presented two case studies that employed gradient-boosting decision trees to examine the nonlinear and threshold associations of urban form variables with driving distance in Oslo, Norway and CO2 emissions in Minneapolis, Minnesota. This modeling approach enabled them to bring new insights and challenge conventional wisdom in the field of land use and travel behavior research. Watch their presentation.