Urban Geoinformatics

Our research acts as bridging studies connecting physical and social domains. Our main research interest is to model urban place functions with heterogeneous big geographical data such as citizen science data and remotely sensed imagery by applying different machine learning/GeoAI methods. In turn, we also explore how the spatial organization of the place functions shapes people’s daily behavior patterns.

Sample Publications
Zhao, F., Dai, Z.X., Zhang, W.Y., Shan, Y.T., Fu, C.* (2023). Epidemiological-Survey-based Multidimensional Modeling for Understanding Daily Mobility during the COVID-19 Pandemic Across Urban-Rural Gradient in the Chinese Mainland. Geo-spatial Information Science. 
https://doi.org/10.1080/10095020.2022.2156821

Bruehwiler, L., Fu, C.*, Huang, H.S., Longi, L., & Weibel, R. (2022) Modeling Individuals’ Car Accident Risk by Trajectory, Driving Events, and Geographical Context. Computers, Environment, and Urban Systems.
https://doi.org/10.1016/j.compenvurbsys.2022.101760

Group leader
Dr. Cheng Fu

Group members
Changyu Han( PhD candidate)
Jingyi Zhou (visiting PhD candidate)
Guojian Zou (visiting PhD candidate)

Belongs to the organizational unit
Geographic Information Systems