Brunsdon Chris - An Introduction to R for Spatial Analysis and Mapping

For my cousin John Poile (19632013) Missed by many people in many ways. CB To Mandy we didnt break each other. AJC

Chris Brunsdon and Lex Comber 2015

First published 2015

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ISBN 978-1-4462-7295-4 (pbk)

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CONTENTS

ABOUT THE AUTHORS

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 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 methods. 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.

FURTHER RESOURCES

All of the data used in the examples in this book are provided inside R packages and so will be automatically available when the packages are installed or are collected by the code that is used. Instructions on installation of packages appears as they are introduced. In some instances data are read directly from websites into R and in these cases details are given in the text.

An annotated R script for each chapter is available at https://study.sagepub.com/brunsdoncomber . The authors will make periodic updates to these as needed (for example if packages or function calls change).

This books draws heavily on the functions available in the GISTools package. For detailed information about this package go to: http://cran.r-project.org/web/packages/GISTools/index.html

PREFACE

R has provided a freely available tool for the analysis of data for well over a decade. The original purpose of R was to provide a programming language and interactive environment for statistical data analysis. By providing a command-line focused and programmable environment for data analysis, it has proved its worth not only as a statistical analysis toolkit (in the manner of say SPSS or Minitab), but also a flexible environment for the development of new techniques. In addition, it provides a number of powerful graphical facilities.

Over recent years both of us have witnessed the increasing use of R for spatial analysis and geo-computation in the scientific activities we engage in directly. In addition we have seen the increasing use and analysis of spatial data in many other scientific and academic fields. This implies that R is now becoming an important tool for anyone who needs to work with spatial data. Although R does not offer a point-and-click approach offering rapid access to a number of standard GIS operations, its programmability implies that it can be used to tackle a very broad range of applications, with virtually any data format. It can be thought of as a Swiss Army Knife of spatial data handling and analysis.

Our motivation for writing this book much of which is about using R as a tool for manipulating geographical information, and the production of maps reflects these perceptions and the need for a text that can be used by both geographers and researchers in other areas to develop spatial analyses. For these reasons the book is structured and sequenced to provide a learning path that does not assume any prior knowledge of R, spatial analysis or GIS. Rather, as the reader progresses through the chapters, they undertake analyses and exercises that build on previously introduced concepts and tools. R provides an incredibly diverse environment within which to conduct data analyses as its functionality is constantly being expanded with the creation and sharing of new tools and functions in contributed packages. We aim to give the reader a sense of the power that R can offer by explaining a number of geographical information based techniques and problems, and demonstrating how R may be used to address these. We are both strong believers in the principle of learning by doing. We hope this approach is not only informative, but also enjoyable.

We would also like to acknowledge the help of Idris Jega Mohammed, who checked through the manuscript and examples, the reviewers of the first draft, David Unwin and Rich Harris, whose helpful and constructive comments made our task much easier, and the authors of R itself and the many packages that we use in this book.

CB, AJC

INTRODUCTION

1.1 OBJECTIVES OF THIS BOOK

This book assumes no prior knowledge of either R or spatial analysis and mapping. It provides an introduction to the use of R and the increasing number of tools that can be used for explicitly spatial analyses, geocomputation and the statistical analysis of geographical information. The text draws from a number of open source, user contributed libraries or packages that support mapping and cartographic outputs arising from both raster and vector analyses. The book implicitly focuses on vector GIS as other texts cover raster with classic geostatistics (see Bivand et al., 2008), although rasters are implicitly included in some of the exercises, for example the outputs of density surfaces and some of the geographically weighted analyses as described in later chapters.