Geocomputation with R

by Robin Lovelace, Jakub Nowosad, Jannes Muenchow

**Due to an error, some copies have been printed in black & white rather than in colour. If you have received a faulty copy, please reach out to lara.spieker@tandf.co.uk to arrange for a replacement**

Geocomputation with R is for people who want to analyze, visualize, and model geographic data with open source software. The book provides a foundation for learning how to solve a wide range of geographic data analysis problems in a reproducible, and therefore scientifically sound and scalable way. The second edition features numerous updates, including the adoption of the high-performance terra package for all raster data processing, detailed coverage of the spherical geometry engine s2, updated information on coordinate reference systems and new content on openEO, STAC, COG, and gdalcubes. The data visualization chapter has been revamped around version 4 of the tmap package, providing a fresh perspective on creating publication-quality maps from the command line. The importance of the book is also highlighted in a new foreword by Edzer Pebesma.

The book equips you with the knowledge and skills necessary to tackle a wide range of issues manifested in geographic data, including those with scientific, societal, and environmental implications. The book is especially well-suited

Data scientists and engineers interested in upskilling to handle spatial data. People with existing geographic data skills interested in developing powerful geosolutions via code. Anyone who needs to work with spatial data in a reproducible and scalable way. The book is divided into three Foundations, Extensions, and Applications, covering progressively more advanced topics. The exercises at the end of each chapter provide the necessary skills to address various geospatial problems, with solutions and supplementary materials available at r.geocompx.org/solutions/.

Genres: Nonfiction

Kindle Edition

First published March 21, 2019

Reviews

[Vysloczil · Rating 4 out of 5]

Right now this is probably the frontier when it comes to automated spatial tasks and visualisation in R. The reason I make this claim is, inter alia, because it is fully relying on Haldey Wickham's tidyverse principles, and it is using the new sf-class of spatial objects in R (mostly developed by Edzer Pebesma) instead of the older and much clumsier sp class. Make sure to check out the free online version of the book (plus exercises and additional material): https://geocompr.github.io/.

[Malithi · Rating 5 out of 5]

Geocomputation with R is an invaluable resource for anyone who wants to learn spatial analysis techniques with R. The book is written in a very approachable manner that is sure to satisfy R beginners, but provides best practices, examples, online resources, and further applications/extensions which allow more advanced users to delve deeper. From working with spatial datasets, to formatting maps, to creating interactive/animated visuals, Geocomputation with R provides a solid foundation on which to build up spatial analysis and presentation skills. As a fairly new R user who previously only used GIS for spatial analysis, I can credit this book with making the switch to a (nearly) fully R workflow much simpler than it could have been. Highly recommended!

[Lord Farquaard · Rating 4 out of 5]

Bit too much word salad and there are definitely sections of the book that could be skipped (by the authors own admission, but he calls these people that do this 'impatient'). Anyway, overall it covers what it needs to, and was sufficient for my uses.

[GT · Rating 5 out of 5]

Very good resource for teaching/learning spatial analysis in R.

[Anna Abatayo · Rating 5 out of 5]

Wordy, but cleared up a lot of things for me; so I’m giving it 5.