Spatial Informatics Program Area

Spatial Informatics represents an overarching umbrella for studying theories, methods, and applications of spatial analysis/modeling; and spatial data handling, management, and visualization. Spatial informatics research and education are becoming increasingly important as data-intensive, large-scale, and/or multi-scale problems that involve the use and development of GIS (Geographic Information Systems) and spatial analysis/modeling are becoming ubiquitous in scientific discovery and decision-making in many fields. Examples of research themes include development of new theories, methods and software in GIScience (Geographic Information Science), policy and user issues of GIS, geospatial data accessibility, spatial decision support systems, geospatial problem solving environments, and novel applications of GIS such as in Business, Earth sciences, Environmental Science and Engineering, Epidemiology, Geography and Regional Science, Natural Resource Management, and Urban and Regional Planning.


Spatial Informatics faculty

Area Lead: Shaowen Wang (Geography)
Faculty: If you would like to affiliate with I3 and appear on this list, please contact Karin Readel.

College of Education
Education Policy, Organization and Leadership Eboni Zamani-Gallaher
College of Engineering
Civil and Environmental Engineering Praveen Kumar
Computer Science Kevin Chang
College of Fine and Applied Arts
Landscape Architecture Brian Deal
College of Law
Law Arden Rowell
College of Liberal Arts & Sciences (LAS)
Astronomy Robert Brunner
Atmospheric Sciences Atul Jain
Geography and Geographic Information Science Sara McLaffertyShaowen Wang, Mei-Po Kwan
Statistics Bo Li
College of Veterinary Medicine
Pathobiology Marilyn O’Hara Ruiz
School of Information Sciences
ISGS Yu-Feng Lin, Andrew Phillips

Recommended Spatial Informatics courses

Spatial Application Courses

PATH 560 Spatial Epidemiology
UP 519 Advanced Applications of GIS
UP 556 Regional Science Methods

Spatial Foundation Courses

GEOG 569 Spatial Ecosystem Modeling
CS 512 Data Mining
IS 542 Data, Stat and Info
STAT 525 Computational Statistics