The Book
A Beginner’s Guide to Earth Data Analytics with GIS, Mapping, Time Series, and Machine Learning in R
From GPS motion and Greenland’s vanishing ice to coastal flooding and global greenhouse-gas emissions, this book teaches you to analyze the data of a changing planet, using R, starting from zero.
Available in paperback, hardcover, and Kindle.
About the book
R for Earth and Sustainability Data Analytics teaches you to turn real environmental data into insight, using R, even if you have never written a line of code. Most R, GIS, and data-science books assume you already program. This one does not. It starts with installing R and builds, step by step, to complete Earth-data case studies: tracking ground motion from GPS stations, measuring Greenland’s ice loss, mapping coastal flood risk, and charting global greenhouse-gas emissions.
Along the way you learn the full modern toolkit: data cleaning, spatial analysis and mapping (GIS), time series, statistical modeling, and an introduction to machine learning, all applied to the data of a changing planet. Every method is taught hands-on with datasets you can download and run yourself, so you finish able to do your own analysis, not just read about it.
What you will learn
The book is organized into seven chapters that build on each other, from the very first line of R code to full Earth-data case studies.
- Introduction to R. Install R, run your first commands, and learn how the language works.
- Data Handling and Preparation. Read, clean, and reshape data so it is ready to analyze.
- Spatial Analysis (GIS). Work with maps, coordinates, and spatial layers in R.
- Time Series Fundamentals. Explore data that changes over time and find patterns in it.
- Modeling, Prediction, and Machine Learning. Build models that explain and forecast Earth data.
- Earth System Case Studies. Apply your skills to real measurements of the planet.
- Global Change and Sustainability. Analyze global change data and connect it to sustainability questions.
Real data you will work with
You work with real data from day one. Every technique is taught with actual Earth and environmental datasets:
- GPS station ground displacement
- GRACE / Greenland ice-mass change
- Coastal flooding and DEM (Long Island, NY)
- Global greenhouse-gas emissions (World Bank WDI)
- Groundwater levels
- Climate and temperature series
Why this book is different
Most spatial and data-science books in R assume you already know how to program and how to do statistics, which leaves beginners in the Earth and environmental sciences to bridge that gap on their own. This book closes it. It is a true on-ramp that takes you from your first command to research-ready analysis, using the real data of a changing planet.
Across many years of teaching R in Earth science, sustainability, and business, we kept seeing the same thing: students do not struggle with complexity, they struggle with abstraction. When an idea stays theoretical it slips away; when it becomes hands-on, it sticks. So this book is built to break the ice of coding, putting real data and real results in front of you from the first session.
This is a deliberate choice. The style may not match what seasoned R users expect, but for a genuine beginner it is exactly what makes coding finally click. The aim is not to memorize commands; it is to learn how to ask better questions of data, and to gain the confidence to keep asking them.