Quantitative Geography: Perspectives on Spatial Data Analysis

by A Stewart Fotheringham, Martin Charlton, Chris Brunsdon

Overview

Integrating a discussion of the application of quantitative methods with practical examples, this book explains the philosophy of the new quantitative methodologies and contrasts them with the methods associated with geography's 'Quantitative Revolution' of the 1960s. Key issues discussed include: the nature of modern quantitative geography; spatial data; geographical information systems; visualization; local analysis; point pattern analysis; spatial regression; and statistical inference. Concluding with a review of models used in spatial theory, the authors discuss the current challenges to spatial data analysis.

Product Details

ISBN-13:	9780761959472
Publisher:	SAGE Publications
Publication date:	05/02/2000
Pages:	288
Product dimensions:	6.90(w) x 9.76(h) x 0.82(d)

About the Author

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.

Background:

Martin is an expert in the use of Geographical Information Systems and has been a leading researcher in this area for over 20 years. Until recently he was a lecturer in GIS at the University of Newcastle-upon-Tyne.

Research:

Martin, together with Stewart Fotheringham and Chris Brunsdon, is one of the originators of Geographically Weighted Regression, for which he has written much of the software.

Table of Contents

Establishing the Boundaries
Spatial Data
The Role of Geographic Information Systems
Exploring Spatial Data Visually
Local Analysis
Point Pattern Analysis
Spatial Regression and Geostatistical Models
Statistical Inference for Spatial Data
Spatial Modelling and the Evolution of Spatial Theory
Challenges in Spatial Data Analysis