Spring

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.

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 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.

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 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 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. (Prerequisites: GIST 417)