Programs and Courses Geospatial Information Science and Engineering (GIScE)
Graduate Programs of Study
The GIScE program offered by the Department of Environmental Resources Engineering provides M.S. and Ph.D. degrees. For more information visit our department’s study areas within the ESF Catalog (scroll down to find the GIScE program). Here are some general guidelines for coursework depending on the program you enter:
- M.S. candidates
- Departmental policy: at least 24 credits of graduate courses and at least 6 credits of thesis
- At least 9 credits of courses within the department
- At least 3 credits of courses from outside the department
- Ph.D. candidates
- Departmental policy: at least 30 credits of graduate courses and a maximum of 30 credits for dissertation
- At least 12 credits of courses within the department
- At least 6 credits of courses from outside the department
Pre- or Co-Requisite Courses
Pre- or co-requisite courses include calculus, physics, probability and statistics, and programming. These courses are typically taken prior to enrolling in the graduate program, but there are cases when some are taken concurrently with your graduate degree. However, introductory courses in these areas do not typically count towards graduate credit.
GIScE Courses taught by the ERE Department
- ERE 553: Intro to Spatial Information (1cr)
- ERE 555: Radar Remote Sensing (3cr)
- ERE 556: Unmanned Aerial Vehicle Photogrammetry (3cr)
- ERE 565: Principles of Remote Sensing (4cr)
- ERE 621: Spatial Analysis (3cr)
- ERE 622: Digital Image Analysis (3cr)
Additional Geospatial Courses
Mathematics and Statistics Courses
- APM 595: Probability and Statistics (3cr)
- APM 620: Experimental Design and ANOVA* (3cr)
- APM 625: Sampling Methods* (3cr)
- APM 630: Regression Analysis* (3cr)
- APM 635: Multivariate Statistical Methods* (3cr)
- APM 645: Nonparametric Statistics and Categorical Analysis* (3cr)
- APM 671 Map Accuracy Assessment (1cr)
Additional Computing Courses
- IST 459: Introduction to Database Management Systems** (3cr)
- CIS 798: Data Mining** (3cr)
(*) denotes ESF courses offered outside the ERE department
(**) denotes courses available at Syracuse University
Depending on interest, students may select mathematical and computing courses. The above list is only a guide, students will work with their advisor to create an individualized program of study.
For additional information on publications, research and teaching activities please visit the corresponding faculty webpage (Dr. Mountrakis, Dr. Quackenbush, Dr. Salehi.)