Chapter 1 Introduction Chapter 2 Data and Plots Chapter 3 Handling Spatial Data Chapter 4 Programming in R Chapter 5 Using R as a GIS Chapter 6 Point Pattern Analysis Chapter 7 Spatial Attribute Analysis Chapter 8 Localised Spatial Analysis Chapter 9 R and Internet Data Chapter 10 Epilogue
Chris Brunsdon is Professor of Geocomputation at the National University of Ireland, Maynooth. He studied Mathematics at the University of Durham and Medical Statistics at the University of Newcastle upon Tyne, and has worked in a number of universities, holding the Chair in Human Geography at Liverpool University before taking up his current position. His research interests are in health, crime and environmental data analysis, and in the development of spatial analytical tools, including Geographically Weighted Regression approach. He also has interests in the software tools used to develop such approaches, including R. Lex Comber is a Professor of Geographical Information Sciences at the University of Leicester. After studying for a BSc in Plant and Crop Sciences at Nottingham, he did his PhD at the Macaulay Land Use Research Institute (now the Hutton Institute) and the University of Aberdeen. His research covers all areas of spatial analyses and the application and development of quantitative geographical. These have been applied across topic areas that straddle both the social and environmental and include accessibility analyses, land cover / land use monitoring and handling uncertainty in geographic information and spatial data.
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.
-- Richard Harris
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. -- Paul Longley
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. -- Jonny Huck
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. -- Jonathan Reades
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. -- Scott Orford
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. The second edition is timely and fresh. An Introduction to R for Spatial Analysis and Mapping should be required reading for every Geography and GIS student, as well as faculty and professionals.