Twin Cities campus
 
Twin Cities Campus

Geographic Information Science M.G.I.S.

Geography, Environment, Society
College of Liberal Arts
Link to a list of faculty for this program.
Contact Information
Department of Geography, 414 Social Sciences Building, 267 19th Avenue South, Minneapolis, MN 55455 (612-624-1498; fax: 612-624-1044)
Email: mgis@umn.edu
  • Program Type: Master's
  • Requirements for this program are current for Spring 2020
  • Length of program in credits: 35
  • This program does not require summer semesters for timely completion.
  • Degree: Master of Geographic Information Science
Along with the program-specific requirements listed below, please read the General Information section of this website for requirements that apply to all major fields.
The professional master of geographic information science (MGIS), administered by the Department of Geography, provides graduate-level work in the theory, applications, and technology of geographic information science (GIS). Courses for the program are divided into three broad categories. Core courses provide the conceptual and theoretical underpinnings for a comprehensive, well-rounded knowledge of GIS, including an introductory seminar for entering students (GIS 8501). A set of technology courses focuses on specific software and techniques of GIS. Elective courses provide additional breadth to the program by allowing students to take courses related to their area of interest.
Program Delivery
  • via classroom (the majority of instruction is face-to-face)
Prerequisites for Admission
Special Application Requirements:
Applicants must submit an application form; a M.G.I.S. supplemental application form; transcripts; a clearly written personal statement of career interests and goals; and three letters of recommendation from persons familiar with their academic and/or employment background. The GRE is not required. All materials must be submitted by January 30 for fall semester entrance and by September 1 for spring semester entrance.
International applicants must submit score(s) from one of the following tests:
  • TOEFL
    • Internet Based - Total Score: 100
    • Internet Based - Writing Score: 24
    • Internet Based - Reading Score: 22
  • IELTS
    • Total Score: 7.5
  • MELAB
    • Final score: 84
The preferred English language test is Test of English as Foreign Language.
Key to test abbreviations (TOEFL, IELTS, MELAB).
For an online application or for more information about graduate education admissions, see the General Information section of this website.
Program Requirements
Plan C: Plan C requires 29 major credits and 6 credits outside the major. There is no final exam.
This program may be completed with a minor.
Use of 4xxx courses toward program requirements is permitted under certain conditions with adviser approval.
A minimum GPA of 3.00 is required for students to remain in good standing.
At least 2 semesters must be completed before filing a Degree Program Form.
Students must complete a professional portfolio, and a set of concluding experiences including a public presentation, an exit survey, and a final meeting with an advisor.
Required Courses
GEOG 5561 - Principles of Geographic Information Science (4.0 cr)
or FNRM 5131 - Geographical Information Systems (GIS) for Natural Resources (4.0 cr)
GIS 8501 - GIS Project Management and Professional Development (3.0 cr)
GIS 5571 - ArcGIS I (3.0 cr)
GIS 5572 - ArcGIS II (3.0 cr)
Advanced GIS Focus Courses
5xxx-level Requirement
Take 3 credits from the following:
GEOG 5562 - GIS Development Practicum (3.0 cr)
GEOG 5563 - Advanced Geographic Information Science (3.0 cr)
ESPM 5295 - GIS in Environmental Science and Management (4.0 cr)
FNRM 5462 - Advanced Remote Sensing and Geospatial Analysis (3.0 cr)
GIS 5577 - Spatial Database Design and Administration (3.0 cr)
GIS 5574 - Web GIS and Services (3.0 cr)
GIS 5578 - GIS Programming (3.0 cr)
CSCI 5715 - From GPS and Virtual Globes to Spatial Computing (3.0 cr)
GEOG 5543 - Advanced Geocomputing (3.0 cr)
GEOG 5588 - Advanced Geovisualization (3.0 cr)
8xxx-Level Requirement
Take 3 credits from the following:
GEOG 8290 - Seminar in GIS and Cartography (3.0 cr)
GEOG 8291 - Seminar in GIS, Technology, and Society (3.0 cr)
GEOG 8292 - Seminar in GIS: Spatial Analysis and Modeling (3.0 cr)
GIS 8990 - Research Problems in GIS (1.0-6.0 cr)
FNRM 8205 - Research Problems: Spatial Data Analysis (1.0-5.0 cr)
CSCI 8715 - Spatial Data Science Research (3.0 cr)
GEOG 8293 - CyberGIS (3.0 cr)
GEOG 8294 - Spatiotemporal Modeling and Simulation (3.0 cr)
Electives
Take remaining credits from the following list to meet the 35-credit minimum. At least 6 elective credits must be other than those with GEOG or GIS course designators.
Take 16 or more credit(s) from the following:
· GEOG 5361 - Geography and Real Estate (4.0 cr)
· GEOG 5511 - Principles of Cartography (4.0 cr)
· GEOG 5531 - Numerical Spatial Analysis (4.0 cr)
· GEOG 5562 - GIS Development Practicum (3.0 cr)
· GEOG 5563 - Advanced Geographic Information Science (3.0 cr)
· GEOG 5564 - Urban Geographic Information Science and Analysis (3.0 cr)
· GEOG 8290 - Seminar in GIS and Cartography (3.0 cr)
· GEOG 8291 - Seminar in GIS, Technology, and Society (3.0 cr)
· GEOG 8292 - Seminar in GIS: Spatial Analysis and Modeling (3.0 cr)
· GIS 5530 - GIS Internship (1.0-3.0 cr)
· GIS 5555 - Basic Spatial Analysis (3.0 cr)
· GIS 5573 - Introduction to Digital Mapping: ArcGIS Basics (2.0 cr)
· GIS 5574 - Web GIS and Services (3.0 cr)
· GIS 5577 - Spatial Database Design and Administration (3.0 cr)
· GIS 5578 - GIS Programming (3.0 cr)
· GIS 5590 - Special Topics in GIS (3.0 cr)
· GIS 8990 - Research Problems in GIS (1.0-6.0 cr)
· CSCI 4041 - Algorithms and Data Structures (4.0 cr)
· CSCI 4131 - Internet Programming (3.0 cr)
· CSCI 4707 - Practice of Database Systems (3.0 cr)
· CSCI 5715 - From GPS and Virtual Globes to Spatial Computing (3.0 cr)
· CSCI 8715 - Spatial Data Science Research (3.0 cr)
· ESPM 5031 - Applied Global Positioning Systems for Geographic Information Systems (3.0 cr)
· ESPM 5295 - GIS in Environmental Science and Management (4.0 cr)
· FNRM 5114 - Hydrology and Watershed Management (3.0 cr)
· FNRM 5228 - Advanced Topics in Assessment and Modeling of Forests (3.0 cr)
· FNRM 5262 - Remote Sensing and Geospatial Analysis of Natural Resources and Environment (3.0 cr)
· FNRM 5462 - Advanced Remote Sensing and Geospatial Analysis (3.0 cr)
· FNRM 8205 - Research Problems: Spatial Data Analysis (1.0-5.0 cr)
· PA 5231 - Transit Planning and Management (3.0 cr)
· VMED 5181 - Spatial Analysis in Infectious Disease Epidemiology (3.0 cr)
· ANTH 5980 - Topics in Anthropology (3.0 cr)
· GEOG 5541 - Principles of Geocomputing (3.0 cr)
· GEOG 5543 - Advanced Geocomputing (3.0 cr)
· GEOG 5588 - Advanced Geovisualization (3.0 cr)
· GEOG 8293 - CyberGIS (3.0 cr)
· GEOG 8294 - Spatiotemporal Modeling and Simulation (3.0 cr)
· GIS 5576 - Spatial Digital Humanities (3.0 cr)
· CSCI 5521 - Introduction to Machine Learning (3.0 cr)
· CSCI 5523 - Introduction to Data Mining (3.0 cr)
· CSCI 5561 - Computer Vision (3.0 cr)
· FNRM 5216 - Geodesy, Coordinate, and Surveying Calculations for GIS Professionals (1.0 cr)
· FNRM 5362 - Drones: Data, Analysis, and Operations (3.0 cr)
· GDES 5341 - Interaction Design (3.0 cr)
· GDES 5342 - Advanced Web Design (3.0 cr)
· GDES 5371 - Data Visualization Studio (3.0 cr)
· IDSC 4431 - Advanced Database Design (2.0 cr)
· IDSC 6040 - Information Technology Management (2.0 cr)
· IDSC 6423 - Enterprise Systems (2.0 cr)
· INET 4061 - Data Science I: Fundamentals (4.0 cr)
· INET 4707 - Introduction to Databases (4.0 cr)
· INET 4710 - Data Science II: Big Data Analytics (4.0 cr)
· MOT 5001 - Technological Business Fundamentals (2.0 cr)
· MOT 5002 - Creating Technological Innovation (2.0 cr)
· MSBA 6310 - Programming for Data Science (3.0 cr)
· MSBA 6320 - Data Management, Databases, and Data Warehousing (3.0 cr)
· MSBA 6330 - Big Data Analytics (3.0 cr)
· MSBA 6410 - Exploratory Data Analytics and Visualization (3.0 cr)
 
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GEOG 5561 - Principles of Geographic Information Science
Credits: 4.0 [max 4.0]
Course Equivalencies: 02490
Typically offered: Every Fall & Spring
Introduction to the study of geographic information systems (GIS) for geography and non-geography students. Topics include GIS application domains, data models and sources, analysis methods and output techniques. Lectures, reading, and hands-on experience with GIS software. prereq: grad
FNRM 5131 - Geographical Information Systems (GIS) for Natural Resources
Credits: 4.0 [max 4.0]
Course Equivalencies: 00369
Grading Basis: A-F or Aud
Typically offered: Every Fall
Geographic information systems (GIS), focusing on spatial data development and analysis in the science and management of natural resources. Basic data structures, sources, collection, and quality; geodesy and map projections; spatial and tabular data analyses; digital elevation data and terrain analyses; cartographic modeling and layout. Lab exercises provide practical experiences complementing theory covered in lecture. prereq: Grad student or instr consent
GIS 8501 - GIS Project Management and Professional Development
Credits: 3.0 [max 3.0]
Grading Basis: A-F only
Typically offered: Every Fall
Project management/professional development. Portfolio creation, career exploration, degree program planning. GIS project management through lectures, class exercises, guest speakers. prereq: MGIS student or instr consent
GIS 5571 - ArcGIS I
Credits: 3.0 [max 3.0]
Typically offered: Every Fall
First of a two-course series focusing on ArcGIS Desktop. Overview of ArcGIS system and its use for spatial data processing. Data capture, editing, geometric transformations, map projections, topology, Python scripting, and map production. prereq: [GEOG 5561 or equiv, status in MGIS program, familiarity with computer operating systems] or instr consent
GIS 5572 - ArcGIS II
Credits: 3.0 [max 3.0]
Typically offered: Every Spring
Continues GIS 5571. Raster analysis, dynamic segmentation, geometric networks, geocoding, Python scripting, and data interoperability. Substantial projects include map and poster design and production. prereq: [5571, [GEOG 5561 or equiv], in MGIS program] or instr consent
GEOG 5562 - GIS Development Practicum
Credits: 3.0 [max 3.0]
Prerequisites: GIS 5571 or #
Typically offered: Periodic Fall
Algorithms/data structures for digital cartographic data, topological relationships, surface modeling, and interpolation. Map projections, geometric transformations, numerical generalization, raster/vector processing. Hands-on experience with software packages. prereq: GIS 5571 or instr consent
GEOG 5563 - Advanced Geographic Information Science
Credits: 3.0 [max 3.0]
Typically offered: Every Fall & Spring
Advanced study of geographic information systems (GIS). Topics include spatial data models, topology, data encoding, data quality, database management, spatial analysis tools and visualization techniques. Hands-on experience using an advanced vector GIS package. prereq: B or better in 3561 or 5561 or instr consent
ESPM 5295 - GIS in Environmental Science and Management
Credits: 4.0 [max 4.0]
Grading Basis: A-F or Aud
Typically offered: Every Fall
Application of geographic information science and technologies (GIS) in complex environmental problems. Students gain experience in spatial data collection, database development, and spatial analysis, including GNSS and field attribute collection, image interpretation, and existing data fusion, raster/vector data integration and analysis, information extraction from LiDAR data, DEM conditioning and hydrologic analysis, neighborhood analysis, bulk processing and automation, and scripting. Problems vary depending on topics, often with extra-University partners. *Please note that students should have completed a semester-long, introductory lab/lecture GIS course at the graduate or undergraduate level before enrolling in this course, e.g., FNRM 5131. We do not require any given course because students come from varied universities and backgrounds. That said, we assume a knowledge commensurate with a comprehensive introductory course. Students seeking a first course are directed to FNRM 5131. If you have questions regarding your capabilities, please contact the instructor prior to enrolling.
FNRM 5462 - Advanced Remote Sensing and Geospatial Analysis
Credits: 3.0 [max 6.0]
Course Equivalencies: 02660 - FNRM 3462/FNRM 5462
Typically offered: Every Spring
This course builds on the introductory remote sensing class, FNRM 3262/5262. It provides a detailed treatment of advanced remote sensing and geospatial theory and methods including Object-Based Image Analysis (OBIA), lidar processing and derivatives, advanced classification algorithms (including Random Forest, Neural Networks, Support Vector Machines), biophysics of remote sensing, measurements and sensors, data transforms, data fusion, multi-temporal analysis, and empirical modeling. In-class and independent lab activities will be used to apply the course topics to real-world problems. Prior coursework in Geographic Information Systems, remote sensing, and statistics is necessary. Prereq: grad student or instr consent
GIS 5577 - Spatial Database Design and Administration
Credits: 3.0 [max 1.0]
Typically offered: Every Spring
Spatial database design, development planning/management, maintenance, security, access/distribution, and documentation. prereq: instr consent
GIS 5574 - Web GIS and Services
Credits: 3.0 [max 3.0]
Typically offered: Every Fall
Plan, design, develop, publish web-based GIS solution. Build websites, prepare data for web. Commercial software, Open Source software, volunteer geographic information, open GIS standards/developing web GIS application. Hands-on experience with variety of web GIS technologies/software. prereq: [GEOG 5561 or equiv, in MGIS program] or instr consent
GIS 5578 - GIS Programming
Credits: 3.0 [max 3.0]
Prerequisites: #
Typically offered: Every Spring
Programming techniques using Python and other languages specifically relating to GIS technologies. prereq: instr consent
CSCI 5715 - From GPS and Virtual Globes to Spatial Computing
Credits: 3.0 [max 3.0]
Typically offered: Spring Even Year
Mathematical concepts, geo-information, representations, algorithms, data-structures/access methods, analysis, architectures, interfaces, reasoning, time. prereq: Familiarity with Java, C++, or Python
GEOG 5543 - Advanced Geocomputing
Credits: 3.0 [max 3.0]
Typically offered: Every Fall
The availability of computing infrastructures such as high-performance and cloud computing, highspeed networks, and rich data has led to a new scientific paradigm using computational approaches, termed computational science. Geocomputation is the "application of a computational science paradigm to study a wide range of problems in geographical and earth systems (the geo) contexts" (Openshaw, 2014). This course will delve into advanced topics in geocomputation as well as related areas ranging from geographic information and spatial big data to cyberinfrastructure and parallel computation. Students will engage in hands-on exercises learning principles and best practices in geocomputing while using cutting-edge computational infrastructures.
GEOG 5588 - Advanced Geovisualization
Credits: 3.0 [max 3.0]
Typically offered: Every Fall
The generation and use of geographic information has become an integral part of our daily life, science, and technology. This has led to increasing interest in the design and development of interactive maps and dynamic geographic visualizations in 2D, 3D, and Web environments. The Advanced Geovisualization course intends to equip students with the knowledge and advanced technical skills needed to design and implement effective maps and create dynamic and interactive visualizations using geospatial data sets.
GEOG 8290 - Seminar in GIS and Cartography
Credits: 3.0 [max 3.0]
Typically offered: Periodic Fall & Spring
Selected concepts/methods. Topics, which vary yearly, include spatial analysis methods in GIS; advanced visualization methods; data quality and error propagation in GIS; generalization methods in GIS and cartography; role of time in GIS; interactive/animated cartography; incorporation of uncertainty. prereq: instr consent
GEOG 8291 - Seminar in GIS, Technology, and Society
Credits: 3.0 [max 3.0]
Typically offered: Periodic Fall & Spring
Relationships between practice of GIS and political, economic, legal, institutional structures of society. Effects of GIS on society. Nontraditional spaces in GIS. GIS and local decision making. Privacy issues. prereq: instr consent
GEOG 8292 - Seminar in GIS: Spatial Analysis and Modeling
Credits: 3.0 [max 3.0]
Typically offered: Spring Even Year
Overview of Geographic Information Systems (GIS) and spatial analysis/modeling of human/environmental systems. Spatial statistics, modeling spatiotemporal processes, simulation techniques, visualization, complex systems/complexity. Guidance in thesis/dissertation research. prereq: 3511 [or equiv statistics course], [3561 or 5561 or equiv intro GIS course] or instr consent
GIS 8990 - Research Problems in GIS
Credits: 1.0 -6.0 [max 6.0]
Grading Basis: A-F only
Typically offered: Every Fall, Spring & Summer
Project of sufficient scope/complexity to document student's ability to apply spatial analysis and visualization techniques to real-world problems. Supervised by faculty member. prereq: MGIS student, instr consent
FNRM 8205 - Research Problems: Spatial Data Analysis
Credits: 1.0 -5.0 [max 10.0]
Typically offered: Every Fall, Spring & Summer
Independent research under faculty guidance. prereq: instr consent
CSCI 8715 - Spatial Data Science Research
Credits: 3.0 [max 3.0]
Typically offered: Periodic Fall & Spring
Motivation, models of spatial information, querying spatial data, processing strategies for spatial queries, multi-dimensional storage/access methods, spatial graph datasets, spatial data mining, trends (e.g., spatio-temporal databases, mobile objects, raster databases), research literature, how to pursue research. prereq: 4707 or 5707 or 5715 or GIS 5571 or GIS 5573
GEOG 8293 - CyberGIS
Credits: 3.0 [max 3.0]
Typically offered: Every Spring
Just as physical infrastructure provides services such as electricity, plumbing, and road networks to communities across the world, cyberinfrastructure has emerged to provide computational services and capabilities to scientific communities. Cyberinfrastructure integrates high-performance computing, digital sensors, virtual organizations, and software tools and services to facilitate computationally-intensive and collaborative scientific research. CyberGIS, broadly defined as cyberinfrastructure-based geographic information systems, integrates cyberinfrastructure, geographic information systems (GIS), and spatial analysis to enable collaborative geographic problem solving. This course will delve into advanced topics within the context of cyberGIS and related technologies. Particular emphasis will be placed on raster data processing including a broad introduction to raster data, cartographic modeling, and raster data manipulation. We will situate raster data processing in the broader context of geographic information science and cyberGIS focusing on the how synthesizing computational thinking and spatial thinking influence methodological approaches. Students will be expected to draw on their own experiences and backgrounds to enhance discussions, labs, and research projects. Students will gain hands-on experience developing methods to analyze and manipulate raster data.
GEOG 8294 - Spatiotemporal Modeling and Simulation
Credits: 3.0 [max 3.0]
Typically offered: Periodic Spring
Many geographic, societal, and environmental phenomena as well as biological and ecological systems involve dynamic processes that are changing in space and time. Examples include hurricanes, animal migrations, spread of diseases, human mobility and population dynamics. Movement is a key to understanding the underlying mechanisms of these dynamic processes. Today, the availability of an unprecedented amount of movement observations at ne spatial and temporal granularities has resulted in substantial advances in GISciences approaches for the analysis, modeling, and simulation of movement and its patterns. Spatiotemporal models and simulation techniques are often used to analyze and better understand the patterns of spatiotemporal processes, and to assess their behavioral responses in varying environmental conditions. This seminar introduces students to the concepts of spatiotemporal processes and patterns. We review existing methods for modeling and simulation of spatiotemporal phenomena, especially movement. Students will develop computational skills to model a phenomena of their choice and create simulations.
GEOG 5361 - Geography and Real Estate
Credits: 4.0 [max 4.0]
Typically offered: Every Spring
Origins and evolution of land ownership in the United States.
GEOG 5511 - Principles of Cartography
Credits: 4.0 [max 4.0]
Course Equivalencies: 02579 - Geog 3511/Geog 5511
Typically offered: Every Spring
Topics on data sources for mapping. History of thematic cartography (focused on 19th-century European activity). Multivariate classification/symbolization. Models for cartographic generalization, spatial interpolation, and surface representation. Animated/multimedia cartography.
GEOG 5531 - Numerical Spatial Analysis
Credits: 4.0 [max 4.0]
Course Equivalencies: Geog 3531/5531
Typically offered: Every Fall
Applied/theoretical aspects of geographical quantitative methods for spatial analysis. Emphasizes analysis of geographical data for spatial problem solving in human/physical areas.
GEOG 5562 - GIS Development Practicum
Credits: 3.0 [max 3.0]
Prerequisites: GIS 5571 or #
Typically offered: Periodic Fall
Algorithms/data structures for digital cartographic data, topological relationships, surface modeling, and interpolation. Map projections, geometric transformations, numerical generalization, raster/vector processing. Hands-on experience with software packages. prereq: GIS 5571 or instr consent
GEOG 5563 - Advanced Geographic Information Science
Credits: 3.0 [max 3.0]
Typically offered: Every Fall & Spring
Advanced study of geographic information systems (GIS). Topics include spatial data models, topology, data encoding, data quality, database management, spatial analysis tools and visualization techniques. Hands-on experience using an advanced vector GIS package. prereq: B or better in 3561 or 5561 or instr consent
GEOG 5564 - Urban Geographic Information Science and Analysis
Credits: 3.0 [max 3.0]
Typically offered: Periodic Fall
Core concepts in urban geographic information science including sources for urban geographical and attribute data (including census data), urban data structures (focusing on the TIGER data structure), urban spatial analyses (including location-allocation models), geodemographic analysis, network analysis, and the display of urban data. prereq: 3561 or 5561
GEOG 8290 - Seminar in GIS and Cartography
Credits: 3.0 [max 3.0]
Typically offered: Periodic Fall & Spring
Selected concepts/methods. Topics, which vary yearly, include spatial analysis methods in GIS; advanced visualization methods; data quality and error propagation in GIS; generalization methods in GIS and cartography; role of time in GIS; interactive/animated cartography; incorporation of uncertainty. prereq: instr consent
GEOG 8291 - Seminar in GIS, Technology, and Society
Credits: 3.0 [max 3.0]
Typically offered: Periodic Fall & Spring
Relationships between practice of GIS and political, economic, legal, institutional structures of society. Effects of GIS on society. Nontraditional spaces in GIS. GIS and local decision making. Privacy issues. prereq: instr consent
GEOG 8292 - Seminar in GIS: Spatial Analysis and Modeling
Credits: 3.0 [max 3.0]
Typically offered: Spring Even Year
Overview of Geographic Information Systems (GIS) and spatial analysis/modeling of human/environmental systems. Spatial statistics, modeling spatiotemporal processes, simulation techniques, visualization, complex systems/complexity. Guidance in thesis/dissertation research. prereq: 3511 [or equiv statistics course], [3561 or 5561 or equiv intro GIS course] or instr consent
GIS 5530 - GIS Internship
Credits: 1.0 -3.0 [max 6.0]
Grading Basis: S-N only
Typically offered: Every Fall & Spring
Practical hands-on experience using GIS to solve problems in a real-world work environment. prereq: instr consent, strong GIS/mapping skills
GIS 5555 - Basic Spatial Analysis
Credits: 3.0 [max 3.0]
Typically offered: Every Fall
How to use spatial data to answer questions on a wide array of social, natural, and information science issues. Exploratory data analysis/visualization. Spatial autocorrelation analysis/regression. prereq: [STAT 3001 or equiv, MGIS student] or instr consent
GIS 5573 - Introduction to Digital Mapping: ArcGIS Basics
Credits: 2.0 [max 2.0]
Course Equivalencies: 02285
Prerequisites: [GEOG 5561 or equiv, in MGIS program] or #
Grading Basis: A-F only
Typically offered: Every Fall
Desktop mapping functions using ArcGIS software. Application of systems to display/analysis of geographical data. prereq: [GEOG 5561 or equiv, in MGIS program] or instr consent
GIS 5574 - Web GIS and Services
Credits: 3.0 [max 3.0]
Typically offered: Every Fall
Plan, design, develop, publish web-based GIS solution. Build websites, prepare data for web. Commercial software, Open Source software, volunteer geographic information, open GIS standards/developing web GIS application. Hands-on experience with variety of web GIS technologies/software. prereq: [GEOG 5561 or equiv, in MGIS program] or instr consent
GIS 5577 - Spatial Database Design and Administration
Credits: 3.0 [max 1.0]
Typically offered: Every Spring
Spatial database design, development planning/management, maintenance, security, access/distribution, and documentation. prereq: instr consent
GIS 5578 - GIS Programming
Credits: 3.0 [max 3.0]
Prerequisites: #
Typically offered: Every Spring
Programming techniques using Python and other languages specifically relating to GIS technologies. prereq: instr consent
GIS 5590 - Special Topics in GIS
Credits: 3.0 [max 6.0]
Grading Basis: A-F or Aud
Typically offered: Every Fall, Spring & Summer
Topics vary according to curricular needs, technological developments in field.
GIS 8990 - Research Problems in GIS
Credits: 1.0 -6.0 [max 6.0]
Grading Basis: A-F only
Typically offered: Every Fall, Spring & Summer
Project of sufficient scope/complexity to document student's ability to apply spatial analysis and visualization techniques to real-world problems. Supervised by faculty member. prereq: MGIS student, instr consent
CSCI 4041 - Algorithms and Data Structures
Credits: 4.0 [max 4.0]
Course Equivalencies: 02015
Typically offered: Every Fall & Spring
Rigorous analysis of algorithms/implementation. Algorithm analysis, sorting algorithms, binary trees, heaps, priority queues, heapsort, balanced binary search trees, AVL trees, hash tables and hashing, graphs, graph traversal, single source shortest path, minimum cost spanning trees. prereq: [(1913 or 1933) and 2011] or instr consent; cannot be taken for grad CSci cr
CSCI 4131 - Internet Programming
Credits: 3.0 [max 3.0]
Course Equivalencies: CSci 4131/5131
Typically offered: Every Fall & Spring
Issues in internet programming. Internet history, architecture/protocols, network programming, Web architecture. Client-server architectures and protocols. Client-side programming, server-side programming, dynamic HTML, Java programming, object-oriented architecture/design, distributed object computing, Web applications. prereq: 4061, 4211 recommended, cannot be taken for grad CSci cr
CSCI 4707 - Practice of Database Systems
Credits: 3.0 [max 3.0]
Course Equivalencies: CSci 4707/5707/INET 4707
Typically offered: Every Fall & Spring
Concepts, conceptual data models, case studies, common data manipulation languages, logical data models, database design, facilities for database security/integrity, applications. prereq: 4041 or instr consent
CSCI 5715 - From GPS and Virtual Globes to Spatial Computing
Credits: 3.0 [max 3.0]
Typically offered: Spring Even Year
Mathematical concepts, geo-information, representations, algorithms, data-structures/access methods, analysis, architectures, interfaces, reasoning, time. prereq: Familiarity with Java, C++, or Python
CSCI 8715 - Spatial Data Science Research
Credits: 3.0 [max 3.0]
Typically offered: Periodic Fall & Spring
Motivation, models of spatial information, querying spatial data, processing strategies for spatial queries, multi-dimensional storage/access methods, spatial graph datasets, spatial data mining, trends (e.g., spatio-temporal databases, mobile objects, raster databases), research literature, how to pursue research. prereq: 4707 or 5707 or 5715 or GIS 5571 or GIS 5573
ESPM 5031 - Applied Global Positioning Systems for Geographic Information Systems
Credits: 3.0 [max 3.0]
Course Equivalencies: ENR 3031/5031
Grading Basis: A-F or Aud
Typically offered: Every Spring
GPS principles, operations, techniques to improve accuracy. Datum, projections, and coordinate systems. Differential correction, accuracy assessments discussed/applied in lab exercises. Code/carrier phase GPS used in exercises. GPS handheld units, PDA based ArcPad/GPS equipment. Transferring field data to/from desktop systems, integrating GPS data with GIS. prereq: Grad student or instr consent
ESPM 5295 - GIS in Environmental Science and Management
Credits: 4.0 [max 4.0]
Grading Basis: A-F or Aud
Typically offered: Every Fall
Application of geographic information science and technologies (GIS) in complex environmental problems. Students gain experience in spatial data collection, database development, and spatial analysis, including GNSS and field attribute collection, image interpretation, and existing data fusion, raster/vector data integration and analysis, information extraction from LiDAR data, DEM conditioning and hydrologic analysis, neighborhood analysis, bulk processing and automation, and scripting. Problems vary depending on topics, often with extra-University partners. *Please note that students should have completed a semester-long, introductory lab/lecture GIS course at the graduate or undergraduate level before enrolling in this course, e.g., FNRM 5131. We do not require any given course because students come from varied universities and backgrounds. That said, we assume a knowledge commensurate with a comprehensive introductory course. Students seeking a first course are directed to FNRM 5131. If you have questions regarding your capabilities, please contact the instructor prior to enrolling.
FNRM 5114 - Hydrology and Watershed Management
Credits: 3.0 [max 3.0]
Course Equivalencies: 02342
Typically offered: Every Fall
Hydrologic cycle and water processes in upland/riparian systems. Applications of hydrological concepts to evaluate impacts of forest and land management activities on water yield, streamflow, groundwater erosion, sedimentation, and water quality. Concepts, principles, and applications of riparian/watershed management. Regional/national/global examples. Forest ecosystems.
FNRM 5228 - Advanced Topics in Assessment and Modeling of Forests
Credits: 3.0 [max 3.0]
Grading Basis: A-F or Aud
Typically offered: Fall Even Year
Application of recently developed mathematics, computer science, and statistics methodologies to natural resource functioning, management, and use problems. Specific topics, software, and methodologies vary. prereq: 3218, Math 1272, Stat 5021
FNRM 5262 - Remote Sensing and Geospatial Analysis of Natural Resources and Environment
Credits: 3.0 [max 3.0]
Course Equivalencies: 00372 - FNRM 3262/FNRM 5262
Typically offered: Every Fall
Introductory principles and techniques of remote sensing and geospatial analysis applied to mapping and monitoring land and water resources from local to global scales. Examples of applications include: Land cover mapping and change detection, forest and natural resource inventory, water quality monitoring, and global change analysis. The lab provides hands-on experience working with satellite, aircraft, and drone imagery, and image processing methods and software. Prior coursework in Geographic Information Systems and introductory Statistics is recommended. prereq: Grad student or instr consent
FNRM 5462 - Advanced Remote Sensing and Geospatial Analysis
Credits: 3.0 [max 6.0]
Course Equivalencies: 02660 - FNRM 3462/FNRM 5462
Typically offered: Every Spring
This course builds on the introductory remote sensing class, FNRM 3262/5262. It provides a detailed treatment of advanced remote sensing and geospatial theory and methods including Object-Based Image Analysis (OBIA), lidar processing and derivatives, advanced classification algorithms (including Random Forest, Neural Networks, Support Vector Machines), biophysics of remote sensing, measurements and sensors, data transforms, data fusion, multi-temporal analysis, and empirical modeling. In-class and independent lab activities will be used to apply the course topics to real-world problems. Prior coursework in Geographic Information Systems, remote sensing, and statistics is necessary. Prereq: grad student or instr consent
FNRM 8205 - Research Problems: Spatial Data Analysis
Credits: 1.0 -5.0 [max 10.0]
Typically offered: Every Fall, Spring & Summer
Independent research under faculty guidance. prereq: instr consent
PA 5231 - Transit Planning and Management
Credits: 3.0 [max 3.0]
Course Equivalencies: 02587 - CEGE 5213/PA 5231
Typically offered: Every Fall
Principles/techniques related to implementing transit systems. Historical perspective, characteristics of travel demand, demand management. Evaluating/benchmarking system performance. Transit-oriented development. Analyzing alternative transit modes. System design/finance. Case studies, field projects. prereq: Grad student or instr consent
VMED 5181 - Spatial Analysis in Infectious Disease Epidemiology
Credits: 3.0 [max 3.0]
Grading Basis: OPT No Aud
Typically offered: Every Spring
Spatial distribution of disease events. Exposures/outcomes. Factors that determine where diseases occur. Analyzing spatial disease data in public health, geography, epidemiology. Focuses on human/animal health related examples. prereq: Intro to epidemiology, statistics,
ANTH 5980 - Topics in Anthropology
Credits: 3.0 [max 6.0]
Typically offered: Every Fall & Spring
Topics specified in Class Schedule.
GEOG 5541 - Principles of Geocomputing
Credits: 3.0 [max 3.0]
Course Equivalencies: 02617 - Geog 3541/Geog 5541
Grading Basis: A-F or Aud
Typically offered: Every Spring
The availability of computing infrastructures such as high-performance and cloud computing, high-speed networks, and rich data has led to a new scientific paradigm using computational science. Geocomputation is the "application of a computational science paradigm to study a wide range of problems in geographical and earth systems (the geo) contexts" (Openshaw, 2014). This course will introduce students to geocomputation as well as related areas including big spatial data, and cyberinfrastructure. Students will engage in hands-on-exercises learning principles and best-practices in geocomputing. The ability to program is an essential skill for GIScientists. Learning to program takes time and a lost of practice, and in this course students will learn how to develop programs in the Python programming language to solve geospatial problems.
GEOG 5543 - Advanced Geocomputing
Credits: 3.0 [max 3.0]
Typically offered: Every Fall
The availability of computing infrastructures such as high-performance and cloud computing, highspeed networks, and rich data has led to a new scientific paradigm using computational approaches, termed computational science. Geocomputation is the "application of a computational science paradigm to study a wide range of problems in geographical and earth systems (the geo) contexts" (Openshaw, 2014). This course will delve into advanced topics in geocomputation as well as related areas ranging from geographic information and spatial big data to cyberinfrastructure and parallel computation. Students will engage in hands-on exercises learning principles and best practices in geocomputing while using cutting-edge computational infrastructures.
GEOG 5588 - Advanced Geovisualization
Credits: 3.0 [max 3.0]
Typically offered: Every Fall
The generation and use of geographic information has become an integral part of our daily life, science, and technology. This has led to increasing interest in the design and development of interactive maps and dynamic geographic visualizations in 2D, 3D, and Web environments. The Advanced Geovisualization course intends to equip students with the knowledge and advanced technical skills needed to design and implement effective maps and create dynamic and interactive visualizations using geospatial data sets.
GEOG 8293 - CyberGIS
Credits: 3.0 [max 3.0]
Typically offered: Every Spring
Just as physical infrastructure provides services such as electricity, plumbing, and road networks to communities across the world, cyberinfrastructure has emerged to provide computational services and capabilities to scientific communities. Cyberinfrastructure integrates high-performance computing, digital sensors, virtual organizations, and software tools and services to facilitate computationally-intensive and collaborative scientific research. CyberGIS, broadly defined as cyberinfrastructure-based geographic information systems, integrates cyberinfrastructure, geographic information systems (GIS), and spatial analysis to enable collaborative geographic problem solving. This course will delve into advanced topics within the context of cyberGIS and related technologies. Particular emphasis will be placed on raster data processing including a broad introduction to raster data, cartographic modeling, and raster data manipulation. We will situate raster data processing in the broader context of geographic information science and cyberGIS focusing on the how synthesizing computational thinking and spatial thinking influence methodological approaches. Students will be expected to draw on their own experiences and backgrounds to enhance discussions, labs, and research projects. Students will gain hands-on experience developing methods to analyze and manipulate raster data.
GEOG 8294 - Spatiotemporal Modeling and Simulation
Credits: 3.0 [max 3.0]
Typically offered: Periodic Spring
Many geographic, societal, and environmental phenomena as well as biological and ecological systems involve dynamic processes that are changing in space and time. Examples include hurricanes, animal migrations, spread of diseases, human mobility and population dynamics. Movement is a key to understanding the underlying mechanisms of these dynamic processes. Today, the availability of an unprecedented amount of movement observations at ne spatial and temporal granularities has resulted in substantial advances in GISciences approaches for the analysis, modeling, and simulation of movement and its patterns. Spatiotemporal models and simulation techniques are often used to analyze and better understand the patterns of spatiotemporal processes, and to assess their behavioral responses in varying environmental conditions. This seminar introduces students to the concepts of spatiotemporal processes and patterns. We review existing methods for modeling and simulation of spatiotemporal phenomena, especially movement. Students will develop computational skills to model a phenomena of their choice and create simulations.
GIS 5576 - Spatial Digital Humanities
Credits: 3.0 [max 3.0]
Typically offered: Every Spring
Introduction to Spatial Digital Humanities GIS 5576 is a basic overview of desktop GIS (both Esri and open source), as well as an introduction to a number of other mapping techniques (such as Esri Maps for Office, ArcGIS Online, web mapping basics, georeferencing historical maps, etc) in addition to digital scholarship techniques. Course objectives include: understanding the basics of mapping and geospatial information using GIS; documenting and managing spatial data using coherent/standardized methods; understanding several spatial analysis methods that are relevant to student research area; and applying spatial research methods into student research.
CSCI 5521 - Introduction to Machine Learning
Credits: 3.0 [max 3.0]
Typically offered: Periodic Fall
Problems of pattern recognition, feature selection, measurement techniques. Statistical decision theory, nonstatistical techniques. Automatic feature selection/data clustering. Syntactic pattern recognition. Mathematical pattern recognition/artificial intelligence. prereq: [[2031 or 2033], STAT 3021] or instr consent
CSCI 5523 - Introduction to Data Mining
Credits: 3.0 [max 3.0]
Typically offered: Periodic Fall & Spring
Data pre-processing techniques, data types, similarity measures, data visualization/exploration. Predictive models (e.g., decision trees, SVM, Bayes, K-nearest neighbors, bagging, boosting). Model evaluation techniques, Clustering (hierarchical, partitional, density-based), association analysis, anomaly detection. Case studies from areas such as earth science, the Web, network intrusion, and genomics. Hands-on projects. prereq: 4041 or equiv or instr consent
CSCI 5561 - Computer Vision
Credits: 3.0 [max 3.0]
Typically offered: Every Spring
Issues in perspective transformations, edge detection, image filtering, image segmentation, and feature tracking. Complex problems in shape recovery, stereo, active vision, autonomous navigation, shadows, and physics-based vision. Applications. prereq: 5511 or instr consent
FNRM 5216 - Geodesy, Coordinate, and Surveying Calculations for GIS Professionals
Credits: 1.0 [max 1.0]
Grading Basis: OPT No Aud
Typically offered: Every Fall
Where exactly are we? How do we define and refine geographic locations on a lumpy, spinning, unstable planet? On course completion students will understand concepts and practices that are at the very foundation of GIS: geodesy and geographic projections. They will have a working knowledge of geodetic datums and datum evolution, be able to make common geodetic and coordinate geometry calculations, and solve common problems that arise during datum and coordinate system conversions while engaged in the practice of GIS.
FNRM 5362 - Drones: Data, Analysis, and Operations
Credits: 3.0 [max 6.0]
Course Equivalencies: 02659 - FNRM 3362/FNRM 5362
Typically offered: Every Spring
This course explores principles and techniques of Unmanned Aircraft Systems (UAS, also "drones"), applied to natural resource and environmental issues. The course provides hands-on experience with UAS vehicles, sensors, imagery, and software. Course topics include: UAS flight characteristics, regulations/safety, mission planning, flight operations, data collection, image analysis, and applications. Examples of UAS applications to be explored include: forest and natural resource inventory, wetland monitoring, and land cover mapping. Prior coursework in Geographic Information Systems is recommended. Prereq: grad student or instr consent
GDES 5341 - Interaction Design
Credits: 3.0 [max 3.0]
Course Equivalencies: 01108
Grading Basis: A-F or Aud
Typically offered: Every Fall & Spring
Design of interactive multimedia projects. Interactive presentations and electronic publishing. Software includes hypermedia, scripting, digital output. prereq: [[2334 or 2342], design minor] or graphic design major or grad student or instr consent
GDES 5342 - Advanced Web Design
Credits: 3.0 [max 3.0]
Grading Basis: A-F or Aud
Typically offered: Every Spring
Internet-based design. Static web pages, embedded media, cascading style sheets. Design and usability of interface between humans and technology. Evaluation of visual elements that control and organize dealings with computers to direct work. Students develop designs, do usability testing. prereq: [[2334 or 2342], design minor] or graphic design major or grad student or instr consent
GDES 5371 - Data Visualization Studio
Credits: 3.0 [max 3.0]
Course Equivalencies: 02385
Grading Basis: A-F only
Typically offered: Every Fall
Visual articulation of data. Expansive research, meticulous gathering of data, analysis. Develop cohesive graphical narratives/build solid foundation in craft of presenting data.
IDSC 4431 - Advanced Database Design
Credits: 2.0 [max 2.0]
Grading Basis: A-F only
Typically offered: Every Spring
Reviews ER/relational modeling and normalization, then focuses on fact modeling (ORM) to produce advanced richer business data models. "Flipped" class, fully online, including all lectures & final exam. Weekly in-class review session is recorded and online for questions, discussion, and results of assignments & quizzes. prereq: 3103 or CSCI 4707 or CSCI 5707 or instr consent
IDSC 6040 - Information Technology Management
Credits: 2.0 [max 2.0]
Course Equivalencies: 00760 - IDSc 6040/MBA 6240
Grading Basis: A-F only
Typically offered: Every Fall, Spring & Summer
Management of information systems, information technology (IT) in global organization. Strategic uses of IT. Alignment of IT, organizational strategy, internet/Web technologies, e-commerce customer services. Integration of e-business applications, interorganizational systems, systems implementation. Management of information as resource. Lecture, case analysis, classroom discussion. Prereq MBA student.
IDSC 6423 - Enterprise Systems
Credits: 2.0 [max 2.0]
Grading Basis: A-F only
Typically offered: Every Fall & Spring
Requirements of architectures of information systems that help integrate business processes and optimize performance across diverse organizations/divisions. Capabilities of information systems in enterprise integration and supply chain management. Linkages necessary between information systems and business processes.
INET 4061 - Data Science I: Fundamentals
Credits: 4.0 [max 4.0]
Grading Basis: A-F or Aud
Typically offered: Every Fall & Spring
Introduction to data science. Design strategies for business analytics: statistics for machine learning, core data mining models, data pipeline, visualization. Hands-on labs with data mining, statistics, and in-memory analytics software. prereq: Basic statistics and programming skills, laptop
INET 4707 - Introduction to Databases
Credits: 4.0 [max 4.0]
Course Equivalencies: CSci 4707/5707/INET 4707
Grading Basis: A-F or Aud
Typically offered: Every Fall
Concepts, data models. Case studies, data manipulation languages, logical data models, database design, facilities for database security/integrity, applications. Prereq: CSci 4061, at least 45 cr completed; CSci majors contact CSci Dept before registering.
INET 4710 - Data Science II: Big Data Analytics
Credits: 4.0 [max 4.0]
Grading Basis: A-F or Aud
Typically offered: Every Spring
Scales machine learning models and data analysis to a Big Data platform. Map Reduce and Spark frameworks are introduced as approaches to parallel algorithm development. Hands-on labs. Prerequisites: Basic programming knowledge (Java, Python, R). Linear algebra strongly recommended, especially matrix operations (e.g., MATH 2243, Linear Algebra and Differential Equations)
MOT 5001 - Technological Business Fundamentals
Credits: 2.0 [max 2.0]
Grading Basis: A-F only
Typically offered: Every Fall
Basics of operations, strategy, decision-making in technology-driven business. Market opportunity assessment, finance/financial decision-making, organizational roles. Work in teams to analyze aspects of business opportunity. prereq: Degree seeking or non-degree graduate students
MOT 5002 - Creating Technological Innovation
Credits: 2.0 [max 2.0]
Grading Basis: A-F or Aud
Typically offered: Every Spring
Course provides students with techniques to create new ideas, and lead an organization to bring them successfully to market. It will include examples of the dynamics of technological industries, and technology strategies. Topics include effective practices to generate ideas, processes to move them to market, and intellectual property. Students will work in teams to develop a strategy to commercialize a new technology. prereq: Degree seeking or non-degree graduate students.
MSBA 6310 - Programming for Data Science
Credits: 3.0 [max 3.0]
Grading Basis: A-F only
Typically offered: Every Fall
According to recent industry surveys, Python is one of the most popular tools used by organizations data analysis. We will explore the emerging popularity of Python for tasks such as general purpose computing, data analysis, website scraping, and data visualization. You will first learn the basics of the Python language. Participants will then learn how to apply functionality from powerful and popular data science-focused libraries. In addition, we will learn advanced programming techniques such as lambda functions and closures. We will spend most of our class time completing practical hands-on exercises.
MSBA 6320 - Data Management, Databases, and Data Warehousing
Credits: 3.0 [max 3.0]
Grading Basis: A-F only
Typically offered: Every Fall
Fundamentals of database modeling/design, normalization. Extract, transform, load. Data cubes/setting up data warehouse. Data pre-processing, quality, integration/stewardship issues. Advances in database/storage technologies.
MSBA 6330 - Big Data Analytics
Credits: 3.0 [max 3.0]
Grading Basis: A-F only
Typically offered: Every Fall
Big data infrastructure and ecosystem, ingesting and managing big data, analytics with big data; Hadoop, MapReduce, Sqoop, Pig, Hive, Spark, SQL for Big Data, Machine Learning for Big Data, Real-time Streaming for Big Data; cloud computing and other recent developments in big data.
MSBA 6410 - Exploratory Data Analytics and Visualization
Credits: 3.0 [max 3.0]
Grading Basis: A-F only
Typically offered: Every Fall
Fundamentals of data exploration. Detecting relationships and patterns in data. Cluster analysis. Hierarchical and partition-based clustering techniques. Rule induction from data. Advances in multidimensional data visualization.