Geospatial Information Science and Technology

Units: 1

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.

Offered in Fall and Spring

Units: 3

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.

Offered in Fall and Spring

Units: 3

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.

Offered in Fall and Spring

Units: 4

This course equips students with essential skills for geospatial programming. Topics include computer programming to call geospatial processing tools, batch process, performing file reading/writing, and generating displays. To support these tasks, students learn basic programming concepts, such as pseudocode, flow-control, code reuse, and debugging. In the final project, students streamline GIS workflows and customize GIS user interfaces. Familiarity with GIS software is required, but no prior programming experience is expected.

Offered in Fall and Spring

Units: 3

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.

Offered in Fall and Spring

Units: 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.

Offered in Fall and Spring

Units: 3

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.

Offered in Fall and Spring

Units: 1

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.

Offered in Fall and Spring

Units: 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.

Offered in Spring Only

TERM: Offered in Fall and Spring

Units: 2

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.

Offered in Spring Only

Units: 3

Introduction to the methods and applications of geographic spatial modeling technology in landscape architecture and environmental planning.

Offered in Fall Only

Units: 3

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.

Offered in Fall and Spring

Units: 3

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.

Offered in Fall and Spring

Units: 2

This course provides the background and foundation necessary for geospatial analysis, with emphasis on spatial statistics. Introduction to data handling techniques, conceptual and practical geospatial data analysis and GIS in research will be provided. Problems raised by the use of geospatial data will be introduced to provide an awareness of issues, their consequences, and potential solutions. The focus of this course is application and interpretation of analytical methods, rather than derivation of techniques. Students will also explore the interoperability between open source analytical platforms [such as R] and GIS platforms, in addition to other open source software. Students should expect weekly assignments, lectures, and hands-on training using GIS and statistical software. Prior knowledge in basics of GIS is recommended. Topics include descriptive and inferential statistical methods for geospatial data.

Offered in Spring Only

Units: 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.

Offered in Fall Only

Units: 3

The course provides an overview of UAS mapping technology and its rules and regulations. The principles of UAS data collection are explained along with optional hands-on practice with in flight planning and execution. The main focus is on processing imagery collected from UAS using structure from motion techniques and deriving orthophoto mosaics and ultra-high resolution digital elevation models of land surface, vegetation and structures. More advanced topics include multi-temporal 3D data analysis, fusion with lidar data and 3D visualization.

Offered in Fall Only

Units: 1 - 6

Special Topics in Geospatial Information Science

Offered in Fall and Spring

Units: 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.

Offered in Fall and Spring

Units: 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

Offered in Fall Spring Summer

Units: 3

This course is designed to help students with an engineering or scientific undergraduate degree understand the world of business. The class will cover key business functions including finance, marketing, operations, strategy, organizational behavior. Students will undertake a semester-long group project to design and plan for a new company or new product within an existing company. Restricted to students with an engineering, scientific, or other technical background.

Offered in Fall and Spring

Units: 3

Life cycle view of organizing and managing technical projects, including project selection, planning, and execution. Methods for managing and controlling project costs, schedules, and scope. Techniques for assessing project risk. Use of popular project management software tools. Application of project management tools and methods to product development, software, and process reengineering projects.

Offered in Spring and Summer

Units: 1 - 6

Presentation of material not normally available in regular courses offerings or offering of new courses on a trial basis.

Offered in Fall Spring Summer

Units: 3

Economic, political, cultural dimensions of globalization. Role of information and communication technologies, networks, institutions, and practices in human social organization.

Offered in Summer

YEAR: Offered Alternate Odd Years

Units: 3

Blends theory and research to understand and analyze interpersonal communication practices and issues within organizations, including managing impressions and conversations, engaging in active listening, managing conflict, influencing others, and communicating in teams. Focus on developing and maintaining effective interpersonal at work and improving student's communication competence.

Offered in Summer

Units: 3

Meteorological remote sensing data sets used in operational forecast and research applications. Sensor physical principles. Emphasis is on understanding the strengths and weaknesses of the different types of observational data so that the student can judge adequacy of purpose for their applications.

Offered in Fall Only

Units: 3

Overview of remote sensing including history, evolution, vocabulary, and physical principles, i.e., electromagnetic radiation and its interaction with matter. Distant and proximate remote sensing techniques [aerial photography, satellite imaging, radar, lidar, etc.], hardware, and platforms and their application in the characterization and management of soils and crops. Development of strategies for incorporating remote sensing into soil and agronomic research, and of practical skills for processing, analysis, display, and discussion of remote sensing data with applications in soil science and agriculture.

YEAR: Offered Alternate Even Years

Units: 3

Geographic information systems [GIS], global positioning system [GPS], and remote sensing to manage spatially variable soils, vegetation, other natural resources. Develop: function understanding of GIS principles, working knowledge of ArcGIS, problem-solving/critical-thinking necessary to use GIS to characterize and manage soils, agriculture, natural resources. Introduction to GIS; Maps/Cartography; Vectore/Raster Data Models; Georeferencing/Coordinate Systems; Spatial Data Sources; GPS/GPS skillls/ Remote Sensing; Statistics/Interpolation; Precision Agriculture; Computer Aided Design and GIS; Creating Analyzing 3-D Surfaces. Credit not given for both SSC 440 and SSC 540.

Offered in Fall Only

Units: 3

Overview of technology available for implementation of a comprehensive precision agriculture program. Topics include computers, GPS, sensors, mechanized soil sampling, variable rate control system, yield monitors, and postharvest processing controls. Applications of precision agriculture in crop planning, tillage, planting, chemical applications, harvesting and postharvest processing. Credit may not be received for BAE 435 and BAE 535.

Offered in Spring Only

YEAR: Offered Alternate Even Years

Units: 1

Exploration of geographic information systems [GIS] and its applications in precision agriculture. Topics will include file structure and formatting, interfacing with precision agriculture equipment, georeferencing maps, merging and clipping farm data, data field calculations, designing management zones, variable rate prescriptions, and basic data analysis.

Offered in Spring Only

Units: 3

First of a two-semester sequence in probability and statistics taught at a calculus-based level. Probability: discrete and continuous distributions, expected values, transformations of random variables, sampling distributions. Credit not given for both ST 701 and ST 501. Note: this course will be offered in person [Fall] and online [Summer].

Offered in Fall and Summer

Units: 3

Basic concepts of statistical models and use of samples; variation, statistical measures, distributions, tests of significance, analysis of variance and elementary experimental design, regression and correlation, chi-square.

Offered in Fall Spring Summer

Units: 3

This course introduces important ideas about collecting high quality data and summarizing that data appropriately both numerically and graphically. We explore the use of probability distributions to model data and find probabilities. Estimation of parameters and properties of estimators are discussed. Construction and interpretation of commonly used confidence intervals and hypothesis tests are investigated. Students will gain considerable experience working with data. Software is used throughout the course with the expectation of students being able to produce their own analyses.

Offered in Fall and Spring

Units: 3

Introduction to statistical models and methods for analyzing various types of spatially referenced data. The focus is on applications with real data and their analysis with statistical programs such as R and SAS. Students are required to write, modify, and run computer code in order to complete homework assignments and final projects.

Offered in Spring Only

Units: 3

An introduction to programming and data management using SAS, the industry standard for statistical practice. Detailed discussion of the program data vector and data handling techniques that are required to apply statistical methods. Topics are based on the current content of the Base SAS Certification Exam and typically include: importing, validating, and exporting of data files; manipulating, subsetting, and grouping data; merging and appending data sets; basic detail and summary reporting; and code debugging. Additional topics with practical applications are also introduced, such as graphics and advanced reporting. Statistical methods for analyzing data are not covered in this course. Regular access to a computer for homework and class exercises is required. Previous exposure to SAS is not expected.

Offered in Fall Spring Summer