Student Success
Curious about the achievements of our students and alumni? Learn more about their impact and where they work after graduation.
Master of Geospatial Information Science and Technology (MGIST)
Since 2010, our professional master’s degree program has been training students to tackle geospatial problems and leverage new technologies.
What partnerships have MGIST students formed?
Before graduation, each professional master’s student works directly with a community partner on a capstone project to solve a real-world challenge through experiential learning. Over 120 partners have worked with our students, from local public works departments and small startups to national nonprofits, federal agencies and international companies.
Where do our MGIST alumni work?
Graduates find employment in a range of fields, from environmental services to government administration.
Examples of MGIST alumni employers
- Esri
- Duke Energy
- City of Charlotte
- US Army
- NC Department of Transportation
- NC Department of Environmental Quality
- Timmons Group
- Geo Owl
- National Geospatial Intelligence Agency
- National Park Service
- and many more…
300+
MGIST alumni
120+
MGIST capstone partners
95%
of students report securing a new job or a promotion or salary increase at their current job upon graduation
Ph.D. in Geospatial Analytics
Since 2018, our unique doctoral program has supported students pushing the boundaries of geospatial data science and addressing grand challenges through original research. Ph.D. students have won prestigious fellowships and grants to support their work and published their findings in respected peer-reviewed journals, garnering media attention.
National fellowships, scholarships and grants received by Ph.D. students
- American Geophysical Union (AGU) Thriving Earth Exchange Fellowship
- Environmental Protection Agency (EPA) Pathways Program
- Future Investigators in NASA Earth and Space Science and Technology (FINESST)
- Geological Society of America Graduate Student Research Grant
- Great Lakes Summer Fellows Program (in partnership with the NOAA Great Lakes Environmental Research Laboratory)
- Joint Fire Science Program Graduate Research Innovation Grant
- National Institute of Environmental Health Sciences K.C. Donnelly Externship Award
- Nature Conservancy NatureNet Fellowship
- NSF Graduate Research Fellowships Program (GRFP)
- Pacific Northwest National Laboratory Distinguished Graduate Research Program
- Rachel Carson Council Fellowship
- Stu Shea USGIF Endowed Scholarship
- Women in GIS Graduate Scholarship
- Yale Environmental Fellows Program
First-author publications by Ph.D. students (not exhaustive)
- Allen, L.R., et al. (2024). Objective identification of pressure wave events from networks of 1 Hz, high-precision sensors. Atmospheric Measurement Techniques. https://doi.org/10.5194/amt-17-113-2024
- Coffer, M.M., et al. (2021). Assessing cyanobacterial frequency and abundance at surface waters near drinking water intakes across the United States. Water Research. https://doi.org/10.1016/j.watres.2021.117377
- Coffer, M.M., et al. (2020). Performance across WorldView-2 and RapidEye for reproducible seagrass mapping. Remote Sensing of Environment. https://doi.org/10.1016/j.rse.2020.112036
- Coffer, M.M., et al. (2020). Quantifying national and regional cyanobacterial occurrence in US lakes using satellite remote sensing. Ecological Indicators. https://doi.org/10.1016/j.ecolind.2019.105976
- Collins, E.L., et al. (2024). Global patterns in river water storage dependent on residence time. Nature Geoscience.
https://doi.org/10.1038/s41561-024-01421-5 - Collins, E.L., et al. (2022). Predicting flood damage probability across the conterminous United States. Environmental Research Letters. https://iopscience.iop.org/article/10.1088/1748-9326/ac4f0f
- Composto, R.W., et al. (2024). Quantifying urban flood extent using satellite imagery and machine learning. Natural Hazards. https://doi.org/10.1007/s11069-024-06817-5
- Das, R., et al. (2024). Assessment of discontinuity-controlled rock slope instability for debris slide initiation: a GIS-based kinematical analysis in the Great Smoky Mountains National Park, TN, USA. Environmental Earth Sciences. https://doi.org/10.1007/s12665-024-11578-2
- Das, R., et al. (2024). Machine learning-based assessment of regional-scale variation of landslide susceptibility in central Vietnam. PLoS One. https://doi.org/10.1371/journal.pone.0308494
- Das, R., Wegmann, K.W. (2022). Evaluation of machine learning-based algorithms for landslide detection across satellite sensors for the 2019 Cycline Idai event, Chimanimani District, Zimbabwe. Landslides. https://doil.org/10.1007/s10346-022-01912-9.pdf
- Gaines, M.D., et al. (2024). Projecting surface water area under different climate and development scenarios. Earth’s Future. https://doi.org/10.1029/2024EF004625
- Gaines, M.D., Tulbure, M.G., Perin, V. (2022). Effects of climate and anthropogenic drivers on surface water area in the Southeastern United States. Water Resources Research. https://doi.org/10.1029/2021WR031484
- Gao, X., et al. (2023). Observations of satellite land surface phenology indicate that maximum leaf greenness is more associated with global vegetation productivity than growing season length. Global Biogeochemical Cycles. https://doi.org/10.1029/2022GB007462
- Gao, X., Gray, J.M., Reich, B.J. (2021). Long-term, medium spatial resolution annual land surface phenology with a Bayesian hierarchical model. Remote Sensing of Environment. https://doi.org/10.1016/j.rse.2021.112484
- Gao, X., et al. (2021). Longer greenup periods associated with greater wood volume growth in managed pine stands. Agricultural and Forest Meteorology. https://doi.org/10.1016/j.agrformet.2020.108237
- Haedrich, C., et al. (2023). Integrating GRASS GIS and Jupyter Notebooks to facilitate advanced geospatial modeling education. Transactions in GIS. https://doi.org/10.1111/tgis.13031
- Ifediora, B., Cutts, B.B. (2023). Open and shut: Identifying activity patterns by volunteer organizations active in disaster using space-time permutation scan statistics. International Journal of Mass Emergencies & Disasters. https://doi.org/10.1177/02807270231171629
- Inglis, N.C., Vukomanovic, J. (2020). Climate change disproportionately affects visual quality of cultural ecosystem services in a mountain region. Ecosystem Services. https://doi.org/10.1016/j.ecoser.2020.101190
- Inglis, N.C., Vukomanovic, J. (2020). Visualizing when, where, and how fires happen in U.S. parks and protected areas. ISPRS Intl Journal of Geo-Information. https://doi.org/10.3390/ijgi9050333
- Jones, K., et al. (2024). Mapping wildfire jurisdictional complexity reveals opportunities for regional co-management.
Global Environmental Change. https://doi.org/10.1016/j.gloenvcha.2024.102804 - Jones, K., Vukomanovic, J. (2023). Mapping South Florida daily fire risk for decision support using fuel type, water levels, and burn history. Fire.
https://doi.org/10.3390/fire6060236 - Karimi, K., et al. (2023). Contrasting annual and summer phosphorus export using a hybrid Baysean watershed model. Water Resources Research. https://doi.org/10.1029/2022WR033088
- Lawrimore, M.A., et al. (2024). Creating spatially complete zoning maps using machine learning. Computers, Environment and Urban Systems. https://doi.org/10.1016/j.compenvurbsys.2024.102157
- Mathieu, M.E., Gray, J., Richmond-Bryant-J. (2023). Spatial associations of long-term exposure to diesel particulate matter with season and annual mortality due to COVID-19 in the contiguous United States. BMC Public Health. https://doi.org/10.1186/s12889-023-15064-5
- Matli, V.R.R., et al. (2020). Fusion-based hypoxia estimates: Combining geostatistical and mechanistic models of dissolved oxygen variability. Environmental Science and Technology. https://doi.org/10.1021/acs.est.0c03655
- McQuillan, K., Hwang, T., Martin, K. (2023). Extended growing seasons and decreases in hydrologic connectivity indicate increasing water stress in humid, temperate forests. Agricultural and Forest Meteorology.
https://doi.org/10.1016/j.agrformet.2023.109525 - McQuillan, K., Tulbure, M.G., Martin, K.L. (2022). Forest water use is increasingly decoupled from water availability even during severe drought. Landscape Ecology. https://doi.org/10.1007/s10980-022-01425-9
- Millar, G.C, et al. (2021). Space-time analytics of human physiology for urban planning. Computers, Environment and Urban Systems. https://doi.org/10.1016/j.compenvurbsys.2020.101554
- Montgomery, K., et al. (2020). Measures of canopy structure from low-cost UAS for monitoring crop nutrient status. Drones. https://doi.org/10.3390/drones4030036
- Perin, V., et al. (2022). A multi-sensor satellite imagery approach to monitor on-farm reservoirs. Remote Sensing of Environment. https://doi.org/10.1016/j.rse.2021.112796
- Perin, V., et al. (2021). Monitoring small water bodies using high spatial and temporal resolution analysis ready datasets. Remote Sensing. https://doi.org/10.3390/rs13245176
- Reckling, S.K., et al. (2024). Equity in wastewater monitoring: Differences in the demographics and social vulnerability of sewered and unsewered populations across North Carolina. PLoS ONE. https://doi.org/10.1371/journal.pone.0311516
- Ricci, S.W., Bohenstiehl, D.R. (2022). Monitoring visitation at North Carolina artificial reef sites using high spatiotemporal resolution PlanetScope imagery. Regional Studies in Marine Science. https://doi.org/10.1016/j.rsma.2022.102511
- Saffer, A., et al. (2025). Quantifying uncertainty forecasts of when and where invasions happen. Biological Invasions. https://doi.org/10.1007/s10530-025-03573-w
- Saffer, A., et al. (2024). Reconstructing historic and modern potato late blight outbreaks using text analytics. Scientific Reports. https://doi.org/10.1038/s41598-024-52870-2
- Saffer, A., et al. (2024). GIATAR: a Spatio-temporal Dataset of Global Invasive and Alien Species and their Traits. Scientific Data. https://doi.org/10.1038/s41597-024-03824-w
- Sanchez, F., et al. (2023). Spatiotemporal relative risk distribution of porcine reproductive and respiratory syndrome virus in the United States. Frontiers in Veterinary Science. https://doi.org/10.3389/fvets.2023.1158306
- Tiwari, V., et al. (2024). Rice yield estimation framework using time-series satellite data & machine learning. PLoS One. https://doi.org/10.1371/journal.pone.0309982
- Tiwari, V., et al. (2024). Automated in-season rice crop mapping using Sentinel time-series data and Google Earth Engine: A case study in climate-risk prone Bangladesh. Journal of Environmental Management. https://doi.org/10.1016/j.jenvman.2023.119615
- Tomkins, L.M., et al. (2022). Image muting of mixed precipitation to improve identification of regions of heavy snow in radar data. Atmospheric Measurement Techniques. https://doi.org/10.5194/amt-15-5515-2022
- White, C.T., et al. (2023). An open-source platform for geospatial participatory modeling in the cloud. Environmental Modelling & Software. https://doi.org/10.1016/j.envsoft.2023.105767
- White, C.T., et al. (2022). Rapid-DEM: Rapid topographic updates through satellite change detection and UAS data fusion. Remote Sensing. https://doi.org/10.3390/rs14071718
- White, C.T., et al. (2021). Spatially explicit fuzzy cognitive mapping for participatory modeling of stormwater management. Land. https://doi.org/10.3390/land10111114
- Worm, T., et al. (2024). Border interceptions reveal variable bridgehead use in the global dispersal of insects. Global Ecology and Biogeography. https://doi.org/10.1111/geb.13924
Ph.D. student dissertations
- Blind Spots in Citizen Science Data: Implications of Volunteer Biases in eBird Data (Deja Perkins, 2025)
- Advancing Climate-Resilient Agriculture and Disaster Management: Applications of Remote Sensing and Machine Learning in Data-Scarce Bangladesh (Varun Tiwari, 2025)
- Spatial Predictive Modeling of Particulate Matter Related to Health Effects (Martine Mathieu, 2024)
- Reducing Global Pest Forecast Uncertainty with Text Mined Media Records (Ariel Saffer, 2024)
- Observed Mesoscale Surface Air Pressure Waves and In-cloud Characteristics in the Context of Winter Storm Structures
(Luke Allen, 2024) - Leveraging Remote Sensing and Machine Learning for Advanced Landslide Analysis: From Detection to Prediction to Monitoring across Diverse Geo-environments (Raja Das, 2024)
- Using Earth Observation Data of Different Spatial Resolutions to Quantify the Influence of Anthropogenic and Climate Drivers on Surface Water Dynamics (Mollie Gaines, 2024)
- Spatiotemporal Analysis of Innovation Using an Automated Publication Screening (Nicholas Grokhowksy, 2024)
- Multi-Scale Modeling for Wildland Fire Decision Support (Kate Jones, 2024)
- Synthesis of Radar-Observed Characteristics, Storm Structures, and Surface Snowfall Rates in 10+ Years of Northeast US Winter Storms (Laura Tomkins, 2024)
- Assessing Spatio-Temporal Variability in Watershed Nutrient Loadings Using Statistical-Mechanistic Modeling
(Kimia Karimi, 2023) - Does Chilling Explain the Divergent Response of Spring Phenology to Urban Heat Islands? (Xiaojie Gao, 2023)
- Advancing Real-time Deforestation Monitoring via Multi-source Remote Sensing Data, Landscape Processes, and End-User Contributions (Ian McGregor, 2023)
- Computationally Efficient Approaches to Modeling Flood Risk and River Discharge at Scale (Elyssa Collins, 2023)
- Linking Forests and Freshwater Across the Southern Appalachian Forest Landscape
(Katie McQuillan, 2023) - Disaster Nonprofit Relief and Housing Recovery Using GIS Techniques (Byron Ifediora, 2023)
- Facilitating Civic Engagement in Rapidly Urbanizing Regions through Geospatial Participatory Modeling (Corey White, 2023)
- Estimating and Forecasting the Spatio-temporal Hypoxia Dynamics in Northern Gulf of Mexico (Venkata Rohith Reddy Matli, 2022)
- Estimating and Modeling Structural Characteristics of Trees within Aerial LiDAR Data (Vishnu Mahesh Vivek Nanda, 2022)
- Quantifying On-farm Reservoir Dynamics: An Earth Observation and Hydrological Modeling Approach (Vinicius Perin, 2022)
- Mapping Forest Host Species Distributions And Understanding Their Effects On Forecasts Of Disease Spread
(Nicholas Kruskamp, 2021) - Analytical Approaches for Plant Pest Management Across the Biosecurity Continuum (Kellyn Montgomery, 2021)
- Temporally Dynamic Viewscapes for Modeling the Past and Future of Visual Landscape Amenities (Nicole Inglis, 2021)
- Eyes in the Sky Lend Support for Water Quality Monitoring across Inland and Coastal Environments (Megan Coffer, 2021)
Media outlets covering Ph.D. student research
- Association of Flood Plain Mappers
- Aspen Daily News
- CBS 9 (Greenville, NC)
- CBS 17 (Raleigh, NC)
- CNN
- Colorado Public Radio
- CTV News
- Futurity
- H2O Radio
- Law 360
- National Institute of Environmental Health Sciences
- Mirage News
- Nature World News
- NBC 9 (Denver, CO)
- OBX Today
- Phys.org
- PiPa News
- Science Daily
- Verve Times
- Scientific American
- Tech Explorist
- The News & Observer
- WUNC Public Radio (Chapel Hill, NC)
Where do our Ph.D. alumni work?
Our doctoral program prepares students for a range of careers in industry, academia, government agencies, and nonprofit research organizations.
Examples of Ph.D. alumni employers
- Arthur J. Gallagher & Co.
- Cary Institute of Ecosystem Studies
- Clark University
- Emory University
- Environmental Protection Agency (EPA)
- Fresno State University
- Harvard University
- Karen Clark & Company
- NASA Goddard Space Flight Center
- National Environmental Satellite, Data, and Information Service (NESDIS)
- National Oceanic and Atmospheric Administration (NOAA)
- NextEra Analytics
- Planet Labs
- RTI International
- SAS
- Spectrum Enterprise
- Stockholm University
- Syngenta
- Texas Water Development Board
- UNC Chapel Hill
- University of Nevada Reno
- USDA Animal and Plant Health Inspection Service (APHIS)
- USGS National Climate Adaptation Science Center
- Virginia Tech
- Washington and Lee University
$143K+
Average annual salary of a Ph.D. holder in data science, according to Glassdoor
100%
Employment rate after graduation
100%
of Ph.D. alumni say they would choose the program again