Geographic Information Systems (GIS)

GIS - Geographic Information Systems Courses

GIS 205 Spatial Thinking with GIS 3.

Spatial thinking and how it relates to the basic foundations of geospatial science and geographic information systems (GIS) are introduced. Students will learn to tell stories through maps using geographic information and geospatial data and analysis by applying spatial reasoning through a series of interactive assignments and discussions. Students will learn to define spatial problems and design solutions across a variety of disciplines, setting the stage for additional technical coursework in GIS and Geospatial Science.

GIS 280 Introduction to GIS 3.

This course provides an overview of the operations and functions of geographic information systems [GIS]. Students develop a fundamental understanding of geographic information management and analysis methods. Emphasis is placed on the nature of geographic information, working with spatial data, and elementary geospatial analysis and modeling techniques. Students learn effective operation of GIS software and gain exposure to GIS tools that support these emphasis areas. Extensive independent learning and computer experiences include online laboratory sessions, alongside optional online or in-person weekly help sessions.

GIS 295 Special Topics in Geospatial Information Science 1-4.

Special Topics in Geospatial Information Science at the 200 level for offering courses on an experimental basis.

GIS 501 Geospatial Professionalism 2.

Students will examine a variety of topics critical to successful navigation of the geospatial profession, with an emphasis on map communication and presentation, interpreting geospatial research, the ethical, legal, and social implications (ELSI) of using spatial data, metadata concepts, and linking results to policy actions. Students will engage in several writing, presentation, and interpretation exercises.

GIS 510 Fundamentals of Geospatial Information Science and Technology 3.
P: GIS 280 or Senior Standing or Graduate Standing.

This course provides an advanced overview of how geographic information systems [GIS] facilitate data analysis and communication to address common geographic problems. Students improve spatial reasoning and problem definition expertise while emphasizing geographic data models and structures, data manipulation and storage, customization through programming, and the integration of geospatial analysis and modeling into project-based problem solving applicable to a variety of disciplines. Skilled application of both desktop and cloud-based GIS software supports these areas. Extensive independent learning and computer experiences include virtual laboratory sessions, alongside optional online or in-person weekly help sessions to facilitate student learning.

GIS 512 Introduction to Environmental Remote Sensing 3.

Principles and hands-on techniques for processing and analyzing remotely sensed data for natural resource applications. Topics include review of the electromagnetic spectrum, pre-processing (georectification, enhancements and transformations), processing (visual interpretation, indices, supervised and unsupervised classification) and post-processing (masking, change analysis and accuracy assessment) of digital image data. This course will provide students with fundamental concepts and skills needed to pursue further studies in digital processing of remotely sensed data.

GIS 515 Cartographic Design 2.
Prerequisite: GIS 510.

Principles of cartographic design and how to apply them to produce high-quality geographic information system (GIS) based maps. Successful students will acquire an understanding of map design and experience applying it with GIS software. Students produce project maps in both print and web media.

GIS 520 Spatial Problem Solving 3.
Prerequisite: GIS 510 or PA 541 or SSC 440.

Focus on spatial problem solving from a geographic information perspective. Students learn to solve spatial problems through advanced analysis using geospatial technologies, learn to integrate and analyze spatial data in various formats, and explore methods for displaying geographic data analysis results to guide decision making. All course materials are delivered through the Internet, with optional weekly on-campus and synchronous online help sessions.

GIS 521 Surface Water Hydrology with GIS 3.
Prerequisite: GIS 510 or PA 541 or SSC 440.

The application of geographic information systems (GIS) to surface water modeling including stream and watershed delineations, regulatory wetlands jurisdiction determinations, and flood mapping. In addition students will develop spatial computation methods to support hydrological analysis in land use planning, landscape management, and engineering assessments.

GIS 530 Spatial Data Foundations 3.
Prerequisite: GIS 510 or PA 541 or SSC 440.

This course focuses on geospatial information systems from a mathematical and information science perspective. We discuss theoretical frameworks for conceptualizing geographic data, including levels of measurement, data control, and the vector data and raster data paradigms. Then we discuss the geometric underpinnings of geospatial systems: representing data with geographic elements, spatial referencing systems, and projection. Next, we explore map-related topology and computational geometry concepts. Finally, we survey the algorithms for core spatial manipulations, such as interpolation and polygon operations.

GIS 535 Web and Mobile GIS Protocols 3.

This course examines the design, development and deployment of web and mobile geospatial applications using internet and web-based protocols. Throughout the course, students will develop and deploy web and mobile GIS maps and applications relevant to their career using on-premises hosted infrastructure. Course participants will be required to complete assignments with data relevant to their interests. Additionally, students will search for and examine scientific and popular literature to understand how the course concepts are being employed and to foster ideas and discussion.

GIS 540 Geospatial Programming Fundamentals 3.
Prerequisite: GIS 510 or PA 541 or SSC 440.

This course provides fundamental skills for geospatial programming. Topics include calling geographic processing tools, batch processing, performing file i/o in an external computing language and building, graphical user interfaces and displays. To support these tasks, students learn basic programming concepts, such as pseudocode, flow-control, code re-use, and debugging. In the final project, students streamline GIS work-flow and customize GIS user interfaces. Familiarity with GIS software is required, but no prior programming experience is expected.

GIS 550 Geospatial Data Structures and Web Services 3.
Prerequisite: GIS 540.

This course examines the spatial database models and structures used in geospatial information science and technology as well as the design and implementation of web and related mobile computing geospatial tools and systems. Students develop, evaluate, and deploy multiple spatial data models and web services that include connections to external data sources and systems.

GIS 582 Geospatial Modeling 3.

The course provides foundations in methods for GIS-based surface analysis and modeling. The topics include proximity analysis with cost surfaces and least cost paths, multivariate spatial interpolation and 3D surface visualization. Special focus is on terrain modeling, geomorphometry, solar irradiation, visibility, and watershed analysis. Students are also introduced to the basic concepts of landscape process modeling with GIS and to the principles of open source GIS. Introductory level knowledge of GIS or surveying/ geomatics principles is required.

GIS 590 Geospatial Information Science Master's Project 3.
Prerequisite: GIS 550.

This is the culmination course for The Master of Geospatial Information Science and Technology degree. This course provides students with the opportunity to demonstrate their accumulated degree skills and expertise by developing and communicating the solution to a complex geospatial problem through a Master's Capstone project. The project will include interoperable spatial and non-spatial data, web services, customized user interfaces and workflows completed in collaboration with a community partner. The student will design and manage a major project and professionally communicate their analysis and results to a public audience.

GIS 595 Special Topics in Geospatial Information Science 1-6.

Special Topics in Geospatial Information Science.

GIS 601 Seminar in Geospatial Information Science 1.

Seminar in Geospatial Information Science.

GIS 609 Geospatial Forum 1.

The Geospatial Forum brings together researchers, educators, practitioners, and students of the geospatial sciences in an exciting, weekly series of lively presentations and facilitated discussions centered upon frontiers in geospatial analytics and geospatial solutions to complex challenges. Live discussions are recorded and made available online for students.

GIS 610 Special Topics in Geospatial Information Science 1-6.

Special Topics in Geospatial Information Science.

GIS 630 Independent Study 1-3.

Advanced topics not otherwise included in curriculum for advanced graduate students on a tutorial basis. Determination of credits and content by participating faculty in consultation with Director of Graduate Programs. Departmental consent required.

GIS 660 MGIST Professional Portfolio 1.
Restriction: Graduate Student in the MGIST Program.

This course will focus on creating an effective digital portfolio, including content selection, description and reflection, and web site organization and design. The digital portfolio will present personal MGIST program accomplishments to demonstrate individual competences through knowledge, skills, and abilities of a geospatial science professional. Intended for students in their last semester in the MGIST Program.

GIS 710 Geospatial Analytics for Grand Challenges 3.

Examination of sustainable solutions to grand societal challenges using geospatial analytics. Emphasis is placed on the roles that location, spatial interaction, and multi-scale processes play in scientific discovery and communication. Discussion of seminal and leading-edge approaches to problem-solving is motivated by grand challenges such as controlling the spread of emerging infectious disease, providing access to clean water, and creating smart and connected cities. Students also engage in several written and oral presentation activities focused on data science communication skills and professionalization.

GIS 711 Geospatial Data Management 3.

Data management principles and technologies for efficient implementation of geospatial applications. This course introduces students to: spatial and temporal data types, data models, geometry models, spatial predicates, spatial access methods, and spatial query processing. In addition, students will be exposed to modern data management systems for geospatial application development and data integration principles. Prior GIS programming knowledge and knowledge of database management systems and SQL is preferred.

GIS 712 Environmental Earth Observation and Remote Sensing 3.

Focus is on passive electro-optical (microwaves, infrared and visible) remote sensing and will cover the physics of remote sensing, light interactions with Earth surface materials, limitations, advantages and disadvantages of passive remote sensing techniques, estimation of bio/geo-physical parameters from remote sensing data, and sensor performance and mission design for applications including hydrology, cryosphere, atmosphere-ocean dynamics, ecosystems and carbon cycle, and land use land cover change. Students should have introductory knowledge of GIS and remote sensing.

GIS 713 Geospatial Data Mining 3.

This course equips students with the theoretical background and practical computational skills required to use data mining methodologies, including clustering, PCA, spatial autocorrelation, neural networks, classification and regression trees, and high performance, open source geocomputation. The course is designed around, and pays particular attention to, approaches for data with spatial components. Students are expected to have a working knowledge of basic geographic principles, statistical principles, GIS, and remote sensing. Some experience with R programming would also be beneficial.

GIS 790 Special Topics in Geospatial Analytics 1-6.

Special Topics in Geospatial Analytics.

GIS 810 Special topics in Geospatial Analytics 1-6.

Special topics in Geospatial Analytics.

GIS 885 Doctoral Supervised Teaching 1-3.

Teaching experience under the mentorship of faculty who assist the student in planning for the teaching assignment, observe and provide feedback to the student during the teaching assignment, and evaluate the student upon completion of the assignment.

GIS 895 Doctoral Dissertation Research 1-9.

Dissertation Research.