Spatial Data Science with R

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.

1. Introduction to R

Start here if you have never used R, or if you need a refresher. (pdf)

2. Spatial data manipulation with R

Read this to learn about the basics of reading, writing, and manipulating spatial data. (pdf)

3. Spatial data analysis

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

4. Remote sensing image analysis

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

5. Species Distribution Modeling with R

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

6. 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)