Program Overview

Introduction to Geospatial Data Sciences

The Geospatial Data Sciences field of study at the University of Michigan School for Environment and Sustainability (SEAS) prepares environmental professionals and researchers to develop and use analytical and computer-intensive data-science methods to assess and steward the Earths landscapes and natural resources to achieve a sustainable society.

What is Geospatial Data Sciences?

Geospatial Data Sciences is an interdisciplinary field that combines training in digital geospatial, statistical, and modeling tools with application of those tools to a wide range of issues across other specializations at SEAS and beyond. Students learn to apply geospatial data science and modeling principles and tools across fields as diverse as geography and land use, social sciences including environmental justice, policy analysis, business, sustainable systems, terrestrial and aquatic ecosystem management, and coupled human-natural systems and environmental justice.

Why Geospatial Data Sciences?

The benefits of studying Geospatial Data Sciences include:

• Learning both the theory and the applications of advanced computational, analytical, and environmental data science techniques
• Combining training in digital geospatial, statistical, and modeling tools with application of those tools to a wide range of issues
• Developing a sophisticated understanding of satellite remote sensing, including physical principles, types of sensors, scene frequencies based on satellite orbits, methods of image analysis and classification, and applications of remote-sensing scenes and datasets to a wide range of environmental issues
• Planning, designing, and executing GIS projects for natural resource management and becoming proficient in the use of digital mapping software
• Planning and executing modeling analyses, both data-driven statistical modeling and complex dynamic-systems modeling

Curriculum

The curriculum covers four key areas: GIS, satellite remote sensing, statistics, and modeling. Coursework includes:

• GIS laboratories where students learn how to plan, design, and execute a GIS project for natural resource management
• Study of remote sensing, including physical principles, types of sensors, methods of image analysis and classification, and applications of remote sensing for the identification and solution of environmental problems
• Many students also combine their study of informatics with another field of study in SEAS

Career and Select Employers

Through the Geospatial Data Sciences field of study, students can prepare for a wide range of careers in academic research or professional environmental management. Natural resource agencies, NGOs, and nonprofits are increasingly looking for graduates with the training to analyze digital geospatial data. Geospatial Data Sciences graduates become remote sensing specialists, area foresters, refuge managers, environmental consultants, conservation and wildlife information specialists, restoration planners, and more.

Faculty

The faculty members for the Geospatial Data Sciences program include:

• Shannon Brines, Lecturer
• Neil Carter, Associate Professor
• Silvia Cordero-Sancho, Lecturer
• Bill Currie, Professor; Associate Dean for Research and Engagement
• Kim C. Diver, Lecturer III
• Ayumi Fujisaki-Manome, Associate Research Scientist
• Lauren E. Gillespie, Assistant Professor
• Dimitrios Gounaridis, Assistant Research Scientist; Lecturer
• Yi Hong, Assistant Research Scientist
• Meha Jain, Associate Professor
• Dani Jones, Associate Research Scientist
• Derek Van Berkel, Associate Professor
• Tiantian Yang, Associate Professor
• Kai Zhu, Associate Professor

Featured Course

One of the featured courses is Remote Sensing of Environment, which covers the theory, sensors, analysis methods, and uses of remote sensing data in environmental research and applications.

Action-based Learning + Impact

The program emphasizes action-based learning and impact, with students working on real-world projects and collaborating with faculty and professionals in the field.

Dual Degree Programs

The University of Michigan School for Environment and Sustainability offers dual degree programs that allow students to combine their Geospatial Data Sciences degree with another field of study, such as business, law, or public policy.

Sustainability Themes

The program is part of the University's broader sustainability initiative, which includes themes such as:

• Cities + Mobility + Built Environment
• Climate + Energy
• Conservation + Restoration
• Cross-cutting
• Food Systems
• Water

These themes provide a framework for students to explore and address complex environmental issues from multiple perspectives.