Geospatial Data Sciences - Environmental Informatics

The past few decades have seen an explosion in the amount, variety, and complexity of spatial environmental data that is now available to address a wide range of issues in environment and sustainability. Informatics and data analysis for environmental science and management have become increasingly valuable and professionals and researchers possessing these skills are in high demand.

WHAT IS 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 Earth’s landscapes and natural resources to achieve a sustainable society. 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?

• Learn both the theory and the applications of advanced computational, analytical, and environmental data science techniques so you can apply GIS and other tools in the environmental domain of your choice.
• Combine 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. 
• Develop 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.
• Plan, design, and execute GIS projects for natural resource management and become proficient in the use of digital mapping software.
• Plan and execute modeling analyses, both data-driven statistical modeling and complex dynamic-systems modeling.

CURRICULUM

As an Geospatial Data Sciences student, you will learn both the theory and the applications of advanced computational and analytical techniques. This environmental master's program is distinctive because it combines training in digital and computer tools with application of those tools to a wide range of issues across other fields of study at SEAS. The hallmark of our environmental data science program is that it is interdisciplinary, meaning you will work with other students pursuing studies as diverse as ecosystem science and management, environmental justice, and environmental policy and planning.

Coursework covers four key areas: GIS, satellite remote sensing, statistics, and modeling. In the study of remote sensing, combined lecture and laboratory venues acquaint you with physical principles, types of sensors, methods of image analysis and classification, and applications of remote sensing for the identification and solution of environmental problems. In GIS laboratories, you will learn how to plan, design, and execute a GIS project for natural resource management and become proficient in the use of mapping software. Many students also combine their study of informatics with another field of study in SEAS; our curriculum is designed not only to teach you to use these tools but also to apply them in an environmental domain of your choice.