I served as instructor of record for the graduate class HES 505: Introduction to Spatial Data in R in the fall of 2024. This course was designed and previously taught by Dr. Matt Williamson. I taught the course with some modifications – notably, the addition of coding activities to most class sessions. The course syllabus, content, and activities (examples) can be found on the course website.

Course Description

Spatial data are ubiquitous and form the basis for many of our inquiries into social, ecological, and evolutionary processes. As such, developing the skills necessary for incorporating spatial data into reproducible statistical workflows is critical. In this course, we will introduce the core components of manipulating spatial data within the R statistical environment including managing vector and raster data, projections, extraction of data values, interpolation, and plotting. Students will also learn to prototype and benchmark different workflows to aid in applying the appropriate tools to their research questions.

Course Objectives

Students completing this course should be able to:

• Articulate the opportunities and challenges posed by geographic analysis.
• Select the appropriate R packages and functions for manipulating different types of spatial data
• Design statistical analyses that integrate geospatial and tabular data
• Construct appropriate data visualizations for conveying geospatial data
• Develop reproducible workflows for manipulating, visualizing, and analyzing spatial data.