There's no better text for showing students and data analysts how to use R for spatial analysis, mapping and reproducible research. If you want to learn how to make sense of geographic data and would like the tools to do it, this is your guide.
Students and other life-long learners need flexible skills to add value to spatial data. This comprehensive, accessible and thoughtful book unlocks the spatial data value chain. It provides an essential guide to the R spatial analysis ecosystem. This excellent state-of-the-art treatment will be widely used in student classes, continuing professional development and self-tuition.
In this second edition, the authors have once again captured the state of the art in one of the most widely used approaches to spatial analysis. Spanning from the absolute beginner to more advanced concepts and underpinned by a strong ‘learn by doing’ ethos, this book is ideally suited for both students and teachers of spatial analysis using R.
A timely update to the de facto reference and textbook for anyone — geographer, planner, or (geo)data scientist — needing to undertake mapping and spatial analysis in R. Complete with self-tests and valuable insights into the transition from sp to sf, this book will help you to develop your ability to write flexible, powerful, and fast geospatial code in R.
Brunsdon and Comber’s 2nd edition of their acclaimed text book is updated with the key developments in spatial analysis and mapping in R and maintains the pedagogic style that made the original volume such an indispensable resource for teaching and research.
The future of GIS is open-source! An Introduction to R for Spatial Analysis and Mapping is an ideal introduction to spatial data analysis and mapping using the powerful open-source language R. Assuming no prior knowledge, Brunsdon and Comber get the reader up to speed quickly with clear writing, excellent pedagogic material and a keen sense of geographic applications.
While there are many books that provide an introduction to R, this is one of the few that provides both a general and an application-specific (spatial analysis) introduction and is therefore far more useful and accessible. Written by two experts in the field, it covers both the theory and practice of spatial statistical analysis and will be an important addition to the bookshelves of researchers whose spatial analysis needs have outgrown currently available GIS software.
Brunsdon and Comber have produced that rare text that is both an introduction to the field of spatial analysis and, simultaneously, to the programming language R. It has been my go-to text in teaching either subject and this new edition updates and expands an already deeply comprehensive work.
Having already used R for text, audio and image analysis in my course on R, I was very interested in the book by Brunsdon et al. They explain spatial analysis and mapping with the help of R in an extremely understandable way. This leads to an excellent dynamic in the seminar, which also gives me great pleasure as a lecturer. Therefore I recommend this book for seminars with advanced students in R.
This is an excellent resource and a very good textbook for learning to do spatial analyses in R.