PGIST - Courses

PGIST Courses

Course Descriptions
GIST 501A: Geographic Information Science (3 units)

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.

GIST 501B: Remote Sensing Science (3 units)

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). 

GIST 602A: Raster Spatial Analysis (3 units)

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.

GIST 602B: Vector Spatial Analysis (3 units)

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.

GIST 603A: Geographic Information Systems Programming and Automation (3 units)

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.

GIST 603B: WebGIS (3 units)

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.

GIST 604A: Cartography (3 units)

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. 

GIST 604B: Open Source GIS (3 units)

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.