Geospatial Information Science and Engineering (GIScE)

Course Requirements
Geospatial Information Science and Engineering (GIScE)
Environmental Resources Engineering (M.S. & Ph.D.)

SUNY ESF Catalog describes the prerequisite and co-requisite courses as well as the mastery courses for the Geospatial Information Science and Engineering graduate programs:

Program prerequisite or co-requisite courses include at least one year of physics and calculus, one course in statistics, 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 the four Geospatial Information Science and Engineering areas (illustrative courses are listed in parenthesis):

  • Remote sensing (e.g., Principles of Remote Sensing, Remote Sensing of the Environment)
  • Geographic information systems (e.g., Introduction to Spatial Information, GIS for Engineers, GIS-Based Modeling, Introduction to Global Positioning Systems)
  • Spatial analysis and programming (e.g., Spatial Analysis, Digital Image Analysis, Numerical and Computing Methods, Systems Engineering, Design and Analysis of Algorithm, Introduction to Artificial Neural Networks, Introduction to Database Management Systems, Data Mining, Artificial Intelligence)
  • Statistics (e.g., Statistical Analysis, Multivariate Statistical Methods, Nonparametric Statistics, Analysis of Variance, Regression Analysis, Map Accuracy Assessment, Sampling Methods)

Ph.D. students will take an additional course in at least two of these areas (6+ credit hours total). These areas of competence form the basis for your graduate coursework and are supplemented by studies in systems analysis, environmental sciences and management, and geography. Departmental and other seminars are also required. Of the total graduate coursework, at least 15 credit hours must be completed in engineering and applied science courses. Research credits complete the degree requirements.


GIScE Courses

Additional Environmental Courses

  • Ecological Engineering in the Tropics (3cr)
  • Ecological Engineering for Waste Management (3cr)
  • Engineering Hydrology & Hydraulics (3cr)
  • Open Channel Hydraulics (3cr)
  • Water Pollution Engineering (3cr)
  • Systems Ecology* (4cr)
  • Landscape Ecology* (4cr)

Additional Mathematical Courses

  • Statistical Analysis* (3cr)
  • Intro to Sampling Techniques* (3cr)
  • Multivariate Statistical Methods* (3cr)
  • Nonparametric Stats* (3cr)
  • Analysis of Variance* (3cr)
  • Regression Analysis* (3cr)

Additional Computing Courses

  • Design and Analysis of Algorithms** (3cr)
  • Introduction to Artificial Neural Networks** (3cr)
  • Introduction to Database Management Systems** (3cr)
  • Data Mining** (3cr)
  • Principles of Programming I** (3cr)

(*) denotes ESF courses offered outside the ERE department
(**) denotes courses available at neighboring Syracuse University

Depending on interest, students may select environmental, mathematical and/or computing courses. The above list is only a guide, students will work with their advisor to create an individualized program of study. A complete list with additional ESF courses is available for the Fall and Spring semesters.

For additional information on publications, research and teaching activities please visit the corresponding faculty webpage (Dr. Mountrakis, Dr. Quackenbush).


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