# Links

The following are resources that we have found useful in teaching spatial analysis and methods using R. You may find these helpful as a reference. Free resources are denoted with an asterisk.

## Spatial Data Analysis in R

**Spatial R Task View***: Provides an overview of the R ecosystem for spatial data analysis**Applied Spatial Data Analysis with R (2nd Edition)**, Roger Bivand, Edzer Pebesma and Virgilio Gomez-Rubio (2013): More advanced, in-depth coverage of spatial statistical packages in R (assumes quite a bit of R expertise)**Geocomputation in R***: Recent online textbook about manipulating, mapping, and modeling geographic data**Introduction to visualizing spatial data in R***, Robin Lovelace, James Cheshire, Rachel Oldroyd and others (2015) : A good introductory overview of GIS operations in R**An Introduction to Spatial Data Analysis and Visualization in R***, Guy Lansley and James Cheshire (2016): A more extensive introduction to mapping, spatial data manipulation and visualization in R**An Introduction to R for Spatial Analysis and Mapping**, Chris Brunsdon and Lex Comber (2015): a more in-depth intermediate overview of GIS operations and some spatial analysis in R with lots of illustrations

## General R Learning

**R for Data Science***, Garrett Grolemund and Hadley Wickham (2017): A collection of data science “skills” using R, with an emphasis on “data munging” using specialized R packages called the “tidyverse” – highly recommended if you are serious about data science using R