AMMnet Hackathon Session 5: Mapping in R part 2

Welcome back! We hope you enjoyed the first part of our Mapping in R series, which focused on vector data. In this follow-up session, we’ll dive into working with raster data in R. We’ll begin with a brief introduction to raster concepts and attributes, followed by a hands-on walkthrough using real-world examples.

By the end of the session, you’ll be able to confidently load and export raster data, crop and reproject rasters, classify and calculate with raster layers, extract summary statistics, and produce publication-ready visualizations in R. We’ll primarily use the terra, tidyterra and tidyverse packages to support our work.

The AMMnet Hackathon blog is a continual support space that anyone can access to learn how to code and how to code better, to upskill people from a distance and improve abilities in data handling, presentation and analysis, experimental design, quantitative understanding, coding and problem solving and transmission modelling.