GEOG2100 Introduction to GIS:
Overview of GIS, including background, development, trends, and prospects in this technological field; software package and hands-on exercises used to examine basic geographic concepts and spatial data characteristics associated with automated mapping, projections, scales, geocoding, coordinate referencing, and data structures for computerized land-based data bases.
GEOG3010 Geographic Information Analysis:
Reviews many basic statistical methods and applies them to various spatial datasets. In addition, several spatial statistical methods are applied to spatial datasets. This course is an in-depth study of the interface between GIS, spatial data, and statistical analysis.
GEOG3100/GEOG4110 Geospatial Data:
This graduate-level course is designed to provide graduate students from a broad range of disciplines with the skills to carry out applied research tasks and projects requiring the integration of geographic information system technologies and geospatial data. Students are introduced to a collection of techniques and data sources with a focus on acquiring and integrating data. Legal, ethical, and institutional problems related to data acquisition for geospatial information systems are also discussed.
GEOG3130 GIS Programming with Python:
This advanced course explores the more technical aspects of GIS functions and data structures. Students have hands-on access to both raster (grid-cell) and vector-based software packages in the form of lab exercises that culminate in a small student-designed GIS project.
GEOG3140 GIS Database Design:
Designing databases to provide a foundation for GIS functions and applications, including investigating techniques used for designing databases in non-spatial environments and learning the applicability to GIS problems. Building on concepts and techniques introduced in the first half to extend traditional techniques and methodologies to model the requirements of spatial problems. Students learn to translate the conceptual spatial model into a physical implementation specific to GIS products.
GEOG3160 Web GIS
GEOG3170 / GEOG4170 Geospatial Analysis Project
This course provides an opportunity for students to apply geospatial data analysis to real-world applications. Students will work as a team to develop a project that requires GIS analysis and/or application development, design a project workflow and management plan, and implement a solution. Students will demonstrate competence in GIS techniques, geospatial data analysis, and project management at a professional level. The graduate section of the course may substitute for GEOG 3150 - GIS Project Management.
Selected Course Materials
- Labs (From GEOG2100 Intro to GIS):
Examine general election results: In this lab, students are expected to analyze election results in 2008 using operations such as attribute queries, spatial queries, join, summarize and other basic attribute operations. Students also formulate queries to examine the relationship between election results and other demographic data.
Identify Fossil X using raster operations: In this lab, students are expected to perform raster operations (e.g., reclassify, map algebra) and raster conversions to identify raster cells meeting a set of predefined conditions to identify the locations of Fossil X.
- Exercises (From GEOG3140 GIS Database Design):
Basic concepts in ER modeling: This exercise helps students understand various complex concepts in Entity-Relationship modeling as a fundamental modeling method for database design.
Build a geodatabase in ArcGIS: This exercise provides a review for basic geodatabase concepts and their implementations in ArcGIS.
- Assignments (From GEOG3130 GIS Programming with Python):
Evaluate GIS data quality: Data quality is important in ensuring successful data analysis. In this assignment, students are expected to create a Python script to examine the data quality of raster/vector data according to the data quality evaluation guidelines.
Tracking hurricanes: GIS data may not be provided in standard formats for analysis purposes. In this assignment, students are expected to develop a Python based tool to build hurricane trajectories as polylines from hurricane tracks.