Graduate Degree Programs
M.S., M.P.S. or Ph.D. Geospatial Information Science and Engineering
Geospatial Information Science and Engineering is designed for specialized study in spatial information acquisition, analysis, modeling and applications.
This includes theoretical and applied projects in sensing systems and the location, measurement, analysis and description of ground features and earth resources. It also includes use of geographic information systems (GIS) to incorporate spatial data into a wide range of environmental and engineering problems.
Program prerequisite or co-requisite courses beyond the departmental requirement include at least one year of physics and one engineering science course in surveying, numerical methods, or computer science.
Program mastery courses include at least one course (3+ credit hours) in each of these areas of competence: 1) remote sensing; 2) geographic information Ssystems; 3) spatial analysis and programming; 4) statistics.
Students in the MPS program will take additional coursework in at least one of these areas, MS students will take additional coursework in at least two areas, and Ph.D. students will take additional coursework in at least three of these areas.
In addition to competence areas listed above, there is flexibility for students interested in supplementary areas. For example, students in the past have expanded their knowledge in geography, ecology, forestry, systems analysis, electrical/computer engineering and mathematics. Courses from these competence areas are identified in consultation with the Major Professor and Steering Committee.
- Giorgos E. Mountrakis; email@example.com
geographic information systems, remote sensing, spatiotemporal analysis, land cover land use change, climate change, biogeography, coupled human and natural systems
- Lindi J. Quackenbush; firstname.lastname@example.org
geospatial information systems, spatial measurements, remote sensing and image processing, particularly focused on spatial techniques for both urban and forest classification, spatial analysis
- Bahram Salehi; email@example.com
Polarimetric and Interferometric SAR, Optical Remote Sensing including Nanosatellite data, UAV and Photogrammetry, Image Processing and Machine Learning of RS data. Environmental Remote Sensing (Wetland and Water bodies, Forest, Permafrost, Agriculture and other Land Cover types, Sea Ice, Oil Spill on sea and land