Introduction to Geographic Information Science

An introduction to fundamental techniques for geospatial data science and geoscience using a modern GIS toolkit that includes ArcGIS Online and the programming language R. This site is for Chris Prener’s sections only.

Course Description

This class introduces both the theoretical and technical skills that constitute the nascent field of geospatial data science. Techniques introduced include map production and cartography, spatial data cleaning and management, and the manipulation of both tabular and spatial data. The course incorporates a wide variety of social, economic, health, urban, meteorological, and environmental data. These data are mapped at a variety of extents, from the City of St. Louis to the St. Louis Metropolian region, Missouri, and the entire United States.

To map these data, we balance an introduction to the industry-standard proprietary ecosystem, ArcGIS, with cutting-edge techniques for working with spatial data in the programming language R. Data science tools, including Markdown, Git, and GitHub are also introduced.

COVID-19 Pandemic: For the Spring 2021 semester, this course has been modified to accommodate remote learning. Please read about the modifications here.

Course Objectives

This course has five intertwined objectives. After completing the course, students will be able to:

  1. Geographic information science: Describe the concepts that form the foundation of GISc work.
  2. Data management: Perform basic data cleaning and geoprocessing tasks using R.
  3. Data visualization: Create and present visualizations of spatial data using R and ArcGIS Online.
  4. Analysis development: Apply techniques that make GISc work more reproducible, accurate, and collaborative using GitHub, R, Markdown, and other tools.
  5. Research synthesis: Plan and implement a spatial data analysis project that utilizes the techniques described throughout the course.


slides, notes, assignment submission

policies, schedule

slots available Wednesdays, 9am to 10am

course repositories

related articles, news, and media

data science in R