Our Mission

To advance GIScience through GeoAI research
GIScience is a broad field established surrounding geographic information systems (GIS). In his 1992 landmark paper in IJGIS, Michael Goodchild defines GIScience as “research on the generic issues that surround the use of GIS technology, impede its successful implementation, or emerge from an understanding of its potential capabilities.” One important goal of GIScience (among many other important ones) is to produce knowledge that can make GIS better, e.g., to equip them with new functionalities, to improve their existing spatial algorithms, to give them more friendly user interfaces, and to enhance their geovisualization capabilities. This is the goal pursued by the members of our GeoAI Lab, and we are working to advance GIScience through GeoAI research.

Why a focus on GeoAI?

There are many ways to advance GISicence. Why particularly do we choose to focus on GeoAI research? The short answer is this is something we are passionate about and good at. Artificial intelligence has provided novel solutions to many research problems and has the potential to improve a variety of GIS functions; yet, developing effective AI solutions for geographic problems may require geographically integrated datasets and/or spatially explicit models that are not readily available. We believe that a lot of interesting research can happen at the intersection of geography and AI, and we are setting out to examine such research questions. This is also something we are good at. The director of the GeoAI Lab has received extensive training on GIScience, AI, and computational methods. Some of our lab members already have solid backgrounds in computational methods and AI at the time of joining our lab. Some of our other lab members are highly motivated to learn GeoAI by taking courses and completing research projects. We are using our expertise in GIS and AI to tackle the most challenging problems in geography.

Our research products

As a research lab, our major products are knowledge in the form of peer-reviewed publications. In addition, we also share code and data produced through our research projects, which we believe are useful resources for supporting future research. For a list of projects and their source codes, please check the GitHub page of the GeoAI Lab. You can also find the code and data of some earlier projects on the GitHub page of the lab director.

For prospective students

We are always looking for new members who are self-motivated and passionate about GIScience! If you share our passion and would like to join us, please contact Yingjie Hu.