Professional Geographic Information Systems Technology
Graduate Certificate
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The University of Arizona GIST program integrates GIS science and cutting-edge geospatial technology with management skills for use in government, corporate, non-profit, and academic settings. The UA currently offers two graduate options in GIST: the Master of Science in GIST (MS-GIST), which is available in-person or online, and the Professional GIST (P-GIST) graduate certificate, a fully online program. This comprehensive program is designed to meet the educational needs both of working professionals seeking to advance their careers and of recent graduates seeking employment in the high-growth geospatial industries.
*Residents of some U.S. Territories may not be eligible. Please see our Eligibility & State Authorization page for more information.
To earn this certificate, students may complete any 9 credits of graduate level GIST courses with the approval of an advisor. Courses to fulfill this requirement include:
This course will introduce the fundamental concepts of geographic information systems technology (GIST). It will emphasize equally GISystems and GIScience. Geographic information systems are a powerful set of tools for storing, retrieving, transforming and displaying spatial data from the real world for a particular set of purposes. In contrast, geographic information science is concerned with both the research on GIS and with GIS. As Longley et al. (2001, vii) note, “GIS is fundamentally an applications-led technology, yet science underpins successful applications.” This course will combine an overview of the general principles of GIScience and how this relates to the nature and analytical use of spatial information within GIS software and technology. Students will apply the principles and science of GIST through a series of practical labs using ESRI’s ArcGIS software.
This course provides an introduction to the scientific principles and practices of remote sensing. Topics that will be covered in this course include issues of spatial resolutions, the electromagnetic spectrum, remotely sensed sensors, spectral characteristics, digital and digitalization issues, multispectral and LiDAR image processing and enhancement, and land-use and land-cover classifications (LULC) and change detection. The course also emphasizes integration issues and analysis techniques that arise when merging remotely sensed data with geographic information systems (GIS).
The goal of this course is to gain an introductory understanding of geographic programming and data automation techniques using ModelBuilder and the Python language. Students will become familiar with the ModelBuilder tools inside ArcGIS for Desktop to automate redundant tasks using ModelBuilder and learn how to build a script using Python to customize functionality and task with GIS.
The goal of this course is to gain an understanding of web mapping using applications like ArcGIS for Server, ArcGIS Online (AGOL), WebAppBuilder (WAB), web-enabled geoprocessing, Story Maps, AppStudio, and the Javascript API.
This course introduces students to the theory of geovisualization (GV) and presents a range of case study applications. GV is intended to support spatio-temporal decision making across a range of domains, from urban planning to environmental management and climate analysis. Students integrate their theoretical learning into the assigned Lab protocol to design, deliver and test a range of GV products. A range of softwares are used including the ArcGIS suite; Google Map; Google Earth; and Build Out 3D modeling environment.
Combining aspects of Remote Sensing and GIS, this course will teach you everything you need to know to confidently plan for, acquire, process, and interpret drone data as well as produce re-source maps (e.g., aerial photography maps) and become a licensed UAS pilot.
Methods of gathering and analyzing data for the solution of geographical, urban, and regional planning problems, with emphasis on quantitative and statistical techniques used in spatial analysis and cartography, on the one hand, and program planning, on the other.
This course introduces fundamentals of database design, development, and analysis for Geographic Information Systems. Emphasis is on geospatial data and suitable database designs, and on database administration for GIS Enterprise. Topics include requirements engineering for geo-databases, database design using the Entity-Relationship model, object-relational database implementation, database normalization, database optimization, data handling, security risk management, and IT auditing. Database technologies will be demonstrated with two Spatial Database Management Systems: PostgreSQL/PostGIS and ArcGIS Server/Enterprise. Database programming will make use of Python, SQL, and Procedural SQL in PostGIS. A business case is developed as part of coursework, to train the student in the database lifecycle that supports organizational operations, planning, and data management in GIS.
This course examines the principles and practices associated with raster data development and analysis, particularly the development of real world surfaces and statistical analysis based on these surfaces. The course is presented in a lecture/laboratory format. The lecture portion will deal with conceptual issues necessary for the use of raster approaches within a GIS framework. The laboratory portion will provide practical experience with rasters in an ArcGIS environment.
This course focuses on providing students with an introduction vector based spatial analysis and their application in GIS software. Students will learn about how to analyze distribution, direction, orientation, clustering, spatial relationships and processes, and how to render analytic outcomes into cartographic form. This course provides foundational knowledge of global positioning systems, data collection, geodatabase development, and georeferencing.
A GIST-based problem solving approach within the context of a student-directed project. Specific GIS skills covered include project planning, spatial data sources and acquisition, data compilation, coding, analysis, representation, and presentation of results. The course can be repeated for credit, as the topics will vary; each course will examine a different urban or environmental issue in the natural and social sciences using geographic information systems technology.
This course provides students a brief introduction about Open Source software for both desktop and internet GIS applications. Main objective of the course is to expose students to alternative open source tools for practicing GIS besides licensed and conventional GIS software. Students will go through hands on learning about applications hosting, data development, processing, and sharing using open source tools and technologies such as GITHub, Quantum GIS (QGIS), Python, GeoServer and PostGIS. Students will apply technology in lab assignments using real-world data.
