Geospatial Data & Visualization
Our geospatial module is meant only as an introduction to geospatial data, an already-rich area in R that is in mid-Renaissance right now, just as tabular data was in the past few years since the introduction of
dplyr and the rest of
GeoSpatial Textbook: Geocomputation with R (Lovelace, Nowosad, Muenchow)
Basic Visualization tools
Also read over the following vignettes:
DataCamp now has a more modern course from Zev Ross, Spatial Analysis in R with
rasterthat more closely aligns with the tools we will be using in this module (matching the Geocomputation reading above).
Charlotte Wickham’s DataCamp course, Working with Geospatial Data doesn’t cover the new/emerging spatial suite we will focus on, but still very relevant. Chapter 3, introducing the
rasterside of things, is (for the moment) the same one we will use. However, the
sfpackage replaces the vector manipulation and mapping functions of
sp, though many concepts carry over. Least relevant are the older plotting strategies covered there, such as
ggmap, where we will rely on newer
I highly recommend browsing the excellent vignettes of the
sfpackage. Vignettes are provided with most well-developed R packages and often provide the best and most up-to-date introduction to the package.
Follow the r-spatial blog & website for the latest news from the r-spatial community. (Speaking of which, you can also follow the Tidyverse website/blog for updates from there.) Most of the package developers involved in these projects are also active in the
#rstatscorner of Twitter.