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.

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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.

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Inside you will learn how to:

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- Set up R and RStudio and write your first scripts with confidence

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- Clean and prepare messy real-world data

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- Make maps and analyze spatial data with GIS tools (sf, terra)

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- Explore time series: trends, seasonality, and forecasting

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- Build and evaluate simple regression and machine-learning models

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- Work through real case studies: GPS tectonic motion, flood exposure on Long Island, ice-mass change in Greenland, and worldwide emissions

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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.

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A companion website offers the code, datasets, and a free instructor package (slides, labs, and assessments).

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R for Earth and Sustainability Data Analytics

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