Computer Science + Geography
Listed on the application as: Interdisciplinary Computing: Geographic Information Science
Use computing and location data to understand and improve the world
Geographic Information Science (GIS) focuses on the collection, analysis, and visualization of geospatial data: information connected to a specific place. As the amount and complexity of this data grow, the field increasingly depends on advanced computational methods.
This four-year interdisciplinary degree combines geographic and spatial thinking with computer science. Students learn to work with large geospatial datasets, build advanced spatial models, and design interactive mapping systems that help people understand complex challenges.
What is geographic information science?
Geographic information science examines how location-based data is collected, managed, analyzed, and communicated. It provides the foundation for technologies that use maps, satellite imagery, sensors, and other geospatial information to reveal patterns and guide decisions.
GIS is used in areas such as:
- Environmental monitoring
- Climate and sustainability planning
- Transportation and logistics
- Urban and regional planning
- Emergency response
- Public health
- Agriculture and natural resources
- Business and market analysis
- Infrastructure development
- Interactive maps and navigation systems
What will I study?
Students complete a shared foundation in computer science before advancing into geography courses and areas where computing and geospatial analysis intersect.
The curriculum develops knowledge and skills in:
- Programming and computational problem-solving
- Algorithms and data structures
- Geographic information systems
- Geospatial data collection and management
- Geospatial computing
- Remote sensing and satellite imagery
- Spatial analysis and modeling
- Cartography and geovisualization
- Data mining and machine learning
- Interactive mapping systems
- Ethical and responsible uses of location data
Advanced coursework and projects allow students to apply computational tools to real geographic questions and datasets.
Connect spatial and computational thinking
Geographic problems are not simply data problems. Understanding them also requires knowledge of place, scale, environment, human communities, and the relationships among them.
By combining spatial thinking with computational thinking, students learn not only how to build technical tools but also how to use them in ways that account for the people and places represented by the data.
This perspective prepares students to develop solutions that are both data-driven and socially meaningful.
What kinds of problems could I help solve?
Computer Science + Geography students can apply their skills to challenges such as:
- Monitoring environmental and climate change
- Managing water, land, energy, and other natural resources
- Designing more sustainable and equitable cities
- Improving transportation networks
- Mapping the effects of natural disasters
- Identifying geographic patterns in public health
- Analyzing satellite and sensor data
- Building more useful and accessible mapping tools
- Helping organizations make location-based decisions
Expand your studies with the AI and Machine Learning minor
Students may also be able to complement this degree with the University of Minnesota’s new Artificial Intelligence and Machine Learning minor beginning in 2027.
The seven-course minor explores areas such as machine learning, data mining, computer vision, robotics, and natural language processing. For Computer Science + Geography students, it offers an opportunity to develop additional expertise in using AI to analyze satellite images, recognize spatial patterns, model complex systems, and work with large geospatial datasets.
Eligibility and course-planning requirements apply. Students interested in the minor should work with an academic advisor to determine how it can fit with their degree.
Explore the Artificial Intelligence and Machine Learning minor.
Is Computer Science + Geography right for me?
This subplan may be a good fit if you are interested in questions such as:
- How can maps and data help us understand a changing planet?
- How do satellites, sensors, and mapping platforms collect information?
- How can computing improve transportation or city planning?
- How can we identify geographic patterns in large datasets?
- How can AI be used to analyze satellite imagery?
- How can location-based technology support more equitable decisions?
You do not need to choose between an interest in computing and an interest in the world around you. This program is designed for students who want to use both perspectives to solve problems.
What can I do with this degree?
Graduates will be prepared to pursue careers and advanced study in areas including:
- Geographic information science
- Geospatial software development
- Geospatial data science and analysis
- Remote sensing
- Cartography and data visualization
- Urban and transportation technology
- Environmental data analysis
- Location intelligence
- Spatial modeling
- Machine learning and artificial intelligence
- Natural resource management
- Emergency planning and response
Potential employers include technology companies, environmental organizations, government agencies, consulting firms, transportation and logistics companies, public utilities, research organizations, and businesses that rely on mapping or location-based data.
Explore the curriculum
Learn more about admission requirements, required courses, and the recommended four-year plan for Innterdisciplinary Computing: Geographic Information Science.
