Mapping with R

This workshop provides an introduction to making maps and working with spatial data in R. It is designed for anyone who has locations they'd like to put on a map — study sites, sample points, addresses, boundaries, or any table of coordinates — and wants to produce a clear, publication-quality map. We will cover the core ideas that make spatial data approachable, including what a coordinate reference system (CRS) is and why it matters, and how spatial data pairs geographic location with the ordinary attributes you already know how to work with. We will bring in a dataset (regardless of whether it starts as a spreadsheet of coordinates or a GIS file), explore it, ask a basic spatial question, and build a finished map complete with color, labels, and map elements such as a scale bar and north arrow. We will primarily use the sf and ggplot2 packages. This workshop incorporates hands-on work, and there will be plenty of time for questions. Some familiarity with R is helpful but not required. No spatial or GIS experience is required; we'll cover the mapping concepts you need along the way.

You will not need to install any software in advance. This session will take place in the Lenovo Esports and Gaming Lab (LEGL) at Hunt Library, on workstations that have R, RStudio, and Positron pre-installed. You are welcome to follow along on your own laptop, but note that we won't be able to install software or troubleshoot personal machines during the session — reach out through go.ncsu.edu/getdatahelp if you'd like setup help beforehand. As workshops have large waitlists, if you find you are no longer able to attend, we ask that you cancel your registration as early as possible; to do so, you would sign in to REPORTER, select "View Details" under the workshop title, and select "Cancel Registration." If you have any questions, please get in touch with the course instructor at lib-datascienceservices@ncsu.edu

Learning Objectives

By the end of this workshop, you will be able to:

• Explain what makes data "spatial," including the role of the coordinate reference system (CRS) and how spatial data combines geographic location with ordinary attributes
• Read spatial data into R from common sources, such as a spreadsheet of coordinates or a GIS file
• Inspect and explore a spatial dataset
• Use a basic spatial operation to relate features to one another by location
• Create a publication-quality map in R, applying color, labels, and standard map elements such as a scale bar and north arrow
• Export a map for use in a poster, presentation, or publication, and know where to find further help and resources from the Libraries