GIScience is the scientific discipline that studies data structures and computational techniques to capture, represent, process, and analyze geographic information, which provides theoretical foundation for geographical information systems (GIS), the software tools, among others. Since the coining of the term “geographic information science” (shortened as GIScience) in 1990, it has advanced rapidly in a range of areas, offering exciting study and research opportunities for students interested in discovering, processing, and analyzing geospatial data with computational, analytical, and visualization methods. The focus areas include geocomputation and GIS programming, remote sensing of the earth, spatial and spatiotemporal data analytics and modeling, digital cartography, participatory GIS, and spatial decision support. Students can earn B.S. and M.S. degrees in GIScience.


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Applied GIS

Applied GIS focuses on methods and techniques of gaining insight and intelligence from spatio-temporal data in order to manage natural resources, man-made infrastructure, and support a variety of decision making processes.

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Cartography and Geovisualization

Cartography is a synthesis of science, techniques, and art for study map-making and map use. Geovisualization is the study of methods and tools for effective geospatial data visualization and data analytics.

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Data Science

Data science uses scientific methods, processes, algorithms and systems to extract knowledge and insights from diverse data, including structured and unstructured forms of “big data.”

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We apply computational theories, methods, tools, and technologies to understand complex spatiotemporal processes and solve geographical problems.

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Remote Sensing

Remote sensing involves collection and analysis of data about the earth’s surface and near surface with sensors on aircraft and satellites. Image processing and interpretation are key components of remote sensing, and valuable skills for geographers and earth/environmental scientists.

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Spatial Analysis and Modeling

Spatial Analysis and Modeling aim to process, analyze, visualize, model, and better understand spatial processes (often with a temporal dimension) that take place on the earth. It includes a set of closely related subareas: agent-based modeling, data analytics and geographic knowledge discovery, social network analysis, and spatial and spatiotemporal statistics/modeling/simulation.