A master’s degree in Civil Engineering with a focus on geospatial engineering allows students to build advanced expertise in collecting, analyzing, modeling, and communicating spatial data to support engineering and infrastructure decisions. Graduate study at Michigan Tech helps students move beyond undergraduate fundamentals to develop deeper technical skills in GIS, GNSS, LiDAR, remote sensing, photogrammetry, and spatial analysis.
This degree is a strong next step for students who want to specialize in geospatial technologies, strengthen their technical problem-solving skills, and prepare for advanced roles in infrastructure, environmental systems, mapping, and data-driven engineering.
What Makes Graduate Study Different?
Graduate-level study emphasizes deeper technical analysis, more advanced geospatial workflows, and greater independence in solving open-ended engineering challenges. In this program, students build on their undergraduate background to work with modern geospatial datasets and tools, apply spatial modeling to real-world problems, and support more informed decision-making across infrastructure and environmental systems.
Earn $10,000 More Annuallywhen compared to undergraduate degree holders.
1 year experiencetowards your Professional Engineering License.
Advanced Skills You’ll Build
- Gain hands-on experience with advanced GIS, GNSS, LiDAR, and remote sensing tools and workflows.
- Learn the principles of modern photogrammetry and selected computer vision techniques.
- Solve real-world geospatial problems in infrastructure, environmental systems, and water resources.
- Turn location-based data into smarter engineering decisions through spatial analysis and modeling.
- Explore mapping, visualization, and spatial modeling approaches for today’s most complex challenges.
- Develop confidence in communicating technical geospatial information to a range of audiences.
- Prepare for careers supporting sustainable and resilient infrastructure through data-driven analysis
How a Master's Degree Can Support Your Career
Technical Specialization
Develop deeper expertise in geospatial technologies, spatial data analysis, and mapping for engineering applications.
Career Advancement
Develop deeper expertise in geospatial technologies, spatial data analysis, and mapping for engineering applications.
Applied Problem-Solving
Strengthen your ability to turn complex spatial data into practical insights for design, planning, and decision-making.
A Strong Option for Current Michigan Tech Students
For Michigan Tech undergraduates, pursuing the MSCE in Geospatial Engineering can be an efficient way to build on your existing technical foundation while gaining additional specialization in modern geospatial tools, workflows, and applications.
- Deepen your expertise in spatial data collection, analysis, and visualization.
- Strengthen your preparation for careers in mapping, infrastructure, environmental systems, and applied geospatial problem-solving.
- Build advanced skills in emerging technologies such as LiDAR, remote sensing, and photogrammetry.
- Continue developing technical knowledge that can help distinguish you in a competitive and evolving job market.
Sample Course Plan
This sample course plan is a sample, and adjustments may be required due to curriculum changes. Students should work with their advisor to develop their individual plan. A full list of graduate course descriptions is available.
Assumed Student Background
The sample course plan shown below was designed assuming that a student has an undergraduate degree in engineering, surveying, geography, or natural sciences
Requirements: 30 credits minimum (12 maximum credits at 3000-4000 level; 18 credits at 5000 level
Sample Coursework List
| Course | Credits | Semester |
|---|---|---|
| SU 5140 – Photogrammetry & UAV Mapping | 4 | Fall |
| SU 5022 – Geodetic Positioning | 3 | Fall |
| SU 5060 – Geodesy | 3 | Spring |
| SU 5541 – Close-range Photogrammetry | 3 | Spring |
| SU 5640 – Introduction to Remote Sensing | 3 | Spring |
| FW 5550 – Geographic Information Science and Spatial Analysis |
4 | Fall |
| FW 5540– Remote Sensing of the Environment | 3 | Fall |
| FW 5541- Remote Sensing of the Environment Lab | 1 | Fall |
| Systems Elective | 3 | |
| Graduate Elective | 3 |
Systems Elective
| Course | Credits | Semester |
|---|---|---|
| CEE 5710 – Modeling and Simulation Applications | 3 | Fall |
| CEE 5730 – Probabilistic Analysis and Reliability | 3 | Fall |
| CEE 5740 – Introduction to System Identification | 3 | Spring |
| CEE 5760 – Optimization Methods | 3 | Spring |
Sample Graduate Electives
| Course | Credits | Semester |
|---|---|---|
| MA 5701 – Statistical Method | 3 | Fall/Spring/Sum |
| MA 5627– Numerical Linear Algebra | 3 | Spring |
| MA 5631– Advanced Numerical Linear Algebra | 3 | Fall |
| MA 5741– Multivariate Statistical Methods | 3 | Spring |
| CS 5841 – Machine Learning | 3 | Spring |
| EE 5522 – Digital Image Processing | 3 | Fall/Spr |
| FW 5553 – Python Programming for ArcMap GIS | 3 | Fall |
Disclaimer
This course plan is meant to serve as a sample for a student interested in pursuing a coursework-only MSCE degree with a focus on water resources engineering. This plan may not be appropriate for all students, nor is it necessary for a student to follow this schedule to earn a coursework-only degree. Student-specific goals and prior education must be considered and consultation with faculty members is required. Consult with instructors before enrolling in courses that are outside of the Department to ensure that the course will be consistent with your goals and background since sometimes other courses may provide more value to the student. All MSCE degree requirements and rules set forth by the Department and the Graduate School must be met in order for a student to finish the program.