Learning R for the spatial sciences
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Learning R for the spatial sciences
Free resources and guides
Over the past two years, I went from knowing nothing about R to becoming fluent in it. Currently, I’m working on my first online application using an R framework called ‘RShiny.’ Although I was quite grumpy about moving away from python (my supervisor preferred R), I couldn’t be happier that I learned it. It’s clear, user-intuitive (I swear), and easy to begin immediately.
Here are some of the most helpful resources for using R for spatial sciences, with links provided. The best part? They’re all completely free to use.
R for data science on edX : This online course hosted to edX provides high-quality educational material for free. This course isn't focused on spatial data science specifically, but it’s a great introductory course if you’re new to the language.
Data science: A first introduction: This online textbook was written by professors at the University of British Columbia and it dives deeper into important R libraries like tidyr, tibble, and more. There are plenty of examples throughout, and you can pick and choose which chapter you want to focus on.
R for Spatial Data Science: Once you’re more comfortable with the syntax, you can really start focusing on the spatial science packages, like raster or terra. This course is more code-based, in the sense that it won’t provide you with an extensive review of the statistical theory behind each function. However, it’s great for a quick breakdown of R functions and their applications.
EarthLab Earth Data Science Course: This is a highly technical course that uses R and RStudio to work through clear, course-based examples of remote sensing data analysis in an R environment. I used this website ALL the time when starting my research, and I highly recommend it to those of you who work extensively with raster-based datasets.
Spatial Data Science with applications in R: This book was published very recently, but it was uploaded through the r-spatial site, which makes it a good, reliable source for all things spatial science in R. Like the other online notebooks I’ve provided, this guide includes lots of examples. One of the authors is Roger Bivand, who invented many of the R spatial science packages commonly used today.
I hope you enjoy looking over these resources. If you have any questions, feel free to reach out!