Spatial Data Science with R

This is the “raster/sp” version of this resource. These packages are now obsolete and this version of the website is no longer maintained. Please use the terra version instead.

This website provides materials to learn about spatial data analysis and modeling with R. R is a widely used programming language and software environment for data science. R has advanced capabilities for managing spatial data; and it provides unparalleled opportunities for analyzing such data.

If you have never used R, or if you need a refresher, you should start with our Introduction to R

1. Spatial data

An introduction Spatial Data handling in R. (pdf)

2. Spatial data analysis

An introduction to methods for description, prediction and inference with spatial data. (pdf)

3. Remote sensing image analysis

Introduction to remote sensing (satellite) image analysis spatial data. (pdf)

4. Species Distribution Modeling with R

An in-depth tutorial for predicting the geographic ranges of species. (pdf)

5. Case studies

A (small) collection of case studies that can help you learn more about particular topics and design your own workflows. (pdf)


I. The raster package

An introduction to the raster package. (pdf)

II. Spherical computation

Computing distances and other measures on a sphere or spheroid. (pdf)

III. Geographic Information Analysis

R companion to Geographic Information Analysis by O’Sullivan and Unwin. (pdf)