Research Seminar: A computational geography approach to understanding human-urban environment interactions

Seeking detailed spatial and temporal human activity patterns about how citizens interact with their surrounding urban environments is critical to understanding how cities work. This presentation aims to show how we can develop computational geography approaches with geospatial social media Big Data to model and uncover unique human-urban environment interaction patterns. By incorporating complex network theory and large-scale mobility data, spatial networks are constructed to represent people’s activities when interacting with the urban environments. This presentation illustrates two case studies: (1) The first study depicts intriguing urban geography based on the collective spatial interaction patterns. Its findings provide an explicit explanation of how spatial proximity affects the interaction intensity across space. (2) The second study characterizes people’s daily activity patterns in the urban environment. By modeling the transitions in people’s daily activities as geographic context-aware mobility networks, this study reveals distinct and recurrent activity patterns, known as activity motifs, that form the fundamental elements embedded in complex human-urban environment interactions. Finally, this presentation discusses potential challenges and opportunities in adopting computational geography as a core component for a wider range of social science applications.

Poster