Intro to Spatial Data in R

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:

• Develop reproducible workflows for manipulating, visualizing, and analyzing spatial data.
• Understand the unique components of spatial data and how those components fit in R’s data structures.
• Articulate the different formats of spatial data and identify which R packages are suited to each type.
• Describe why space matters for many social and ecological questions
• Implement a variety of descriptive and statistical spatial analyses.
• Leverage functional programming to automate and expedite spatial data operations.