An Introduction to R for Spatial Analysis and Mapping

410 Pages·2015·14.33 MB·English

by  Brunsdon

For my cousin John Poile (1963‒2013) ‒ Missed by many people in many
ways. CB To Mandy ‒ we didn’t break each other. AJC

© Chris Brunsdon and Lex Comber 2015
First published 2015
Apart from any fair dealing for the purposes of research or private study, or criticism or review, as
permitted under the Copyright, Designs and Patents Act, 1988, this publication may be reproduced, stored
or transmitted in any form, or by any means, only with the prior permission in writing of the publishers, or
in the case of reprographic reproduction, in accordance with the terms of licences issued by the Copyright
Licensing Agency. Enquiries concerning reproduction outside those terms should be sent to the publishers.

Library of Congress Control Number: 2014939813
British Library Cataloguing in Publication data
A catalogue record for this book is available from the British Library

ISBN 978-1-4462-7294-7
ISBN 978-1-4462-7295-4 (pbk)
SAGE Publications Ltd
1 Oliver’s Yard
55 City Road
London EC1Y 1SP
SAGE Publications Inc.
2455 Teller Road
Thousand Oaks, California 91320
SAGE Publications India Pvt Ltd
B 1/I 1 Mohan Cooperative Industrial Area
Mathura Road
New Delhi 110 044
SAGE Publications Asia-Pacific Pte Ltd
3 Church Street
#10-04 Samsung Hub
Singapore 049483

Editor: Robert Rojek
Assistant editor: Keri Dickens Production editor: Katherine Haw Copyeditor: Richard Leigh
Proofreader: Neil Dowden
Marketing manager: Michael Ainsley Cover design: Francis Kenney Typeset by: C&M Digitals (P) Ltd,
Chennai, India Printed and bound in Great Britain by Ashford Colour Press Ltd

At SAGE we take sustainability seriously. Most of our products are printed in the UK using FSC papers and
boards. When we print overseas we ensure sustainable papers are used as measured by the Egmont grading
system. We undertake an annual audit to monitor our sustainability.
CONTENTS
About the Authors
Further Resources
Preface
1 INTRODUCTION
1.1 Objectives of This Book
1.2 Spatial Data Analysis in R
1.3 Chapters and Learning Arcs
1.4 The R Project for Statistical Computing
1.5 Obtaining and Running the R software
1.6 The R Interface
1.7 Other Resources and Accompanying Website
References
2 DATA AND PLOTS
2.1 Introduction
2.2 The Basic Ingredients of R: Variables and Assignment
2.3 Data Types and Data Classes
2.3.1 Data types in R
2.3.2 Data classes in R
2.3.3 Self-Test questions
2.4 Plots
2.4.1 Basic plot tools
2.4.2 Plot colours
2.5 Reading, Writing, Loading and Saving Data
2.5.1 Text files
2.5.2 R data files
2.5.3 Spatial data files
Answers to Self-Test Questions
3 HANDLING SPATIAL DATA IN R
3.1 Overview
3.2 Introduction: GISTools
3.2.1 Installing and loading GISTools
3.2.2 Spatial data in GISTools
3.2.3 Embellishing the map
3.2.4 Saving your map
3.3 Mapping Spatial Objects
3.3.1 Introduction
3.3.2 Data
3.3.3 Plotting options
3.3.4 Adding context
3.4 Mapping Spatial Data Attributes
3.4.1 Introduction
3.4.2 Attributes and data frames
3.4.3 Mapping polygons and attributes
3.4.4 Mapping points and attributes
3.4.5 Mapping lines and attributes
3.4.6 Mapping raster attributes
3.5 Simple Descriptive Statistical Analyses
3.5.1 Histograms and boxplots
3.5.2 Scatter plots and regressions
3.5.3 Mosaic plots
3.6 Self-Test Questions
Answers to Self-Test Questions
References
4 PROGRAMMING IN R
4.1 Overview
4.2 Introduction
4.3 Building Blocks for Programs
4.3.1 Conditional statements
4.3.2 Code blocks
4.3.3 Functions
4.3.4 Loops and repetition
4.3.5 Debugging
4.4 Writing Functions
4.4.1 Introduction
4.4.2 Data checking
4.4.3 More data checking
4.4.4 Loops revisited
4.4.5 Further activity
4.5 Writing Functions for Spatial Data
4.5.1 Drawing polygons in a list
4.5.2 Automatically choosing the bounding box
4.5.3 Shaded maps
Answers to Self-Test Questions
5 USING R AS A GIS
5.1 Introduction
5.2 Spatial Intersection or Clip Operations
5.3 Buffers
5.4 Merging Spatial Features
5.5 Point-in-Polygon and Area Calculations
5.5.1 Point-in-polygon
5.5.2 Area calculations
5.5.3 Point and areas analysis exercise
5.6 Creating Distance Attributes
5.6.1 Distance analysis/accessibility exercise
5.7 Combining Spatial Datasets and Their Attributes
5.8 Converting between Raster and Vector
5.8.1 Raster to vector
5.8.2 Converting to sp classes
5.8.3 Vector to raster
5.9 Introduction to Raster Analysis
5.9.1 Raster data preparation
5.9.2 Raster reclassification
5.9.3 Other raster calculations
Answers to Self-Test Questions
References
6 POINT PATTERN ANALYSIS USING R
6.1 Introduction
6.2 What is Special about Spatial?
6.2.1 Point patterns
6.3 Techniques for Point Patterns Using R
6.3.1 Kernel density estimates
6.3.2 Kernel density estimation using R
Self-Test Question 1
6.4 Further Uses of Kernel Density Estimation
6.4.1 Hexagonal binning using R
6.5 Second-Order Analysis of Point Patterns
6.5.1 Using the K-function in R
6.5.2 The L-function
6.5.3 The G-function
6.6 Looking at Marked Point Patterns
6.6.1 Cross-L-function analysis in R
6.7 Interpolation of Point Patterns with Continuous Attributes
6.7.1 Nearest neighbour interpolation
6.7.2 Inverse distance weighting
6.8 The Kriging Approach
6.8.1 A brief introduction to kriging
6.8.2 Random functions
6.8.3 Estimating the semivariogram
6.9 Concluding Remarks
Answers to Self-Test Question
References
7 SPATIAL ATTRIBUTE ANALYSIS WITH R
7.1 Introduction
7.2 The Pennsylvania Lung Cancer Data
7.3 A Visual Exploration of Autocorrelation
7.3.1 Neighbours and lagged mean plots
7.4 Moran’s I: An Index of Autocorrelation
7.4.1 Moran’s I in R
7.4.2 A simulation-based approach
7.5 Spatial Autoregression
7.6 Calibrating Spatial Regression Models in R
7.6.1 Models with predictors: A bivariate example
7.6.2 Further issues
7.6.3 Troubleshooting spatial regression
Answer to Self-Test Question
References
8 LOCALISED SPATIAL ANALYSIS