GIScience is a multidisciplinary field that involves the use of a spatial perspective and geographic information systems (GIS) to understand our world. Such a multidisciplinary characteristic can be seen in the nature of geographic information. In his 1992 landmark paper in IJGIS, Goodchild discussed the uniqueness of geographic information in the form of <x, y, z>, in which x, y refer to the coordinates of a location and z represents an attribute at that location. Since z can be any attribute, such as a disaster event, an environmental variable related to health, an endangered species, a crime incident, and so forth, GIScience is linked to many disciplines that have a concern on geographic location. This multidisciplinary characteristic with a shared spatial perspective makes GIScience an exciting field to work in. The mission of our GeoAI Lab is to advance GIScience by integrating spatial analysis and AI methods to understand the various natural and social phenomena in geographic space and to address the most challenging problems facing our society.
Why a focus on GeoAI?
There are many ways to advance GIScience. 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 methods that enable the extraction of accurate and detailed information from big geo data. By integrating spatial analysis, GIS, and AI, we can answer new scientific questions and test new hypotheses which were difficult or impossible to test before. Using spatial analysis and AI to investigate social and natural phenomena can also inspire research on spatially explicit models and novel GeoAI methods. We believe that a lot of intriguing 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 lab, Dr. Yingjie Hu, has extensive research experience in GIScience, AI, and computational methods. Some of our lab members already have a solid background in computational methods and AI when joining the lab. Some of our other lab members are highly motivated and eager to learn GeoAI by taking courses and completing research projects. We are using our expertise in GIS and AI to tackle a variety of research problems and to advance knowledge.
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 important 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.