An Introduction to R for Spatial Analysis and Mapping
- Chris Brunsdon - National University of Ireland, Maynooth, Ireland
- Lex Comber - University of Leeds, UK
Spatial Analytics and GIS
Geographical Methodology | Research Methods (General) | Sociological Research Methods
The ever-expanding availability of spatial data continues to revolutionise research. This book is your go-to guide to getting the most out of handling, mapping and analysing location-based data.
Without assuming prior knowledge of GIS, geocomputation or R, this book helps you understand spatial analysis and mapping and develop your programming skills, from learning about scripting and writing functions to point pattern analysis and spatial attribute analysis.
The book:
- Illustrates approaches to analysis on a range of datasets that are new to this edition.
- Enables you to put your skills into practice with embedded exercises and over 30 self-test questions.
- Showcases the possibilities of using spatial analysis to explore spatial inequalities.
Whether you’re an R novice or experienced user, this book equips upper undergraduates, postgraduates and researchers with the tools needed for spatial data handling and rich analysis.
Supplements
Student Resources (free to access)
- Datasets used in the book
- R scripts for every chapter
- Both sets of resources are available to download and install from co-author Lex Comber's GitHub repository.
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.
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.
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.