Spatial Data Science with R and “terra”

These resources teach spatial data analysis and modeling with R. R is a widely used programming language and software environment for data science. R also provides unparalleled opportunities for analyzing spatial data and for spatial modeling.

1. Introduction to R

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

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. Processing MODIS data

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

7. Species Distribution Modeling

An tutorial for predicting the geographic ranges of species (under development). (pdf)


I. The terra package

A detailed description of the methods in the terra package. (pdf)

II. Geographic Information Analysis

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

This is the “terra” version of this resource. You can also go to the now outdated “raster/sp” version.