Learn to turn real Earth and environmental data into insight using R, starting from your very first line of code. No prior programming or statistics experience required.
This beginner's guide takes you from GPS ground motion and coastal flooding to melting ice and global greenhouse-gas emissions, all analyzed with free, open-source R. Each chapter builds a complete, runnable workflow on a real dataset, so you learn by doing.
Inside you will learn how to:
- Set up R and RStudio and write your first scripts with confidence
- Clean and prepare messy real-world data
- Make maps and analyze spatial data with GIS tools (sf, terra)
- Explore time series: trends, seasonality, and forecasting
- Build and evaluate simple regression and machine-learning models
- Work through real case studies: GPS tectonic motion, flood exposure on Long Island, ice-mass change in Greenland, and worldwide emissions
Every example uses a named, public dataset, and all code and data are provided so you can reproduce and adapt every result. Ideal for students, educators, and self-learners in the earth, environmental, and sustainability sciences, and well suited to a first course or independent study.
A companion website offers the code, datasets, and a free instructor package (slides, labs, and assessments).
