Overview
Geospatial data are an important component of data visualization and analysis in the social sciences, humanities, and elsewhere. The R programming language is a great platform for exploring these data and integrating them into your research.
R Geospatial Data, Part I: Getting started with spatial data objects
Part one of this three-part workshop series will introduce basic methods and packages for working with geospatial data in R. Participants will learn how to import and export spatial data and store them as spatial objects. We will explore and compare several methods for mapping the data including the base plot function and the ggmap and tmap libraries. We will review coordinate reference systems and methods for reading, defining and transforming these. Note, this workshop focuses on vector spatial data.
R Geospatial Data, Part 2: Geoprocessing and analysis
Part two of this three-part workshop series will dive deeper into data driven mapping in R, using color palettes and data classification to communicate information with maps. We will also introduce basic methods for processing spatial data, which are the building blocks of common spatial analysis workflows. Note, this workshop focuses on vector spatial data.
Knowledge Requirements: Basic knowledge of geospatial data is expected. R experience equivalent to the D-Lab R Fundamentals workshop series is required to follow along with the tutorial. Knowledge of ggplot helpful.
Technology Requirements: Bring a laptop with R, RStudio and the following R packages installed: sp, rgdal, rgeos, ggplot2, ggmap, leaflet, RColorBrewer, classInt, and tmap.
