Quantitative Geography

Chris Brunsdon is Professor of Geocomputation and Director of the National Centre for Geocomputation at the National University of Ireland, Maynooth, having worked previously in the Universities of Newcastle, Glamorgan, Leicester and Liverpool, variously in departments focusing on both geography and computing. He has interests that span both of these disciplines, including spatial statistics, geographical information science, and exploratory spatial data analysis, and in particular the application of these ideas to crime pattern analysis, the modelling of house prices, medical and health geography and the analysis of land use data. He was one of the originators of the technique of geographically weighted regression (GWR). He has extensive experience of programming in R, going back to the late 1990s, and has developed a number of R packages which are currently available on CRAN, the Comprehensive R Archive Network. He is an advocate of free and open source software, and in particular the use of reproducible research methods, and has contributed to a large number of workshops on the use of R and of GWR in a number of countries, including the UK, Ireland, Japan, Canada, the USA, the Czech Republic and Australia. When not involved in academic work he enjoys running, collecting clocks and watches, and cooking – the last of these probably cancelling out the benefits of the first.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.

`This is a veritable tour de force of everything that is exciting about quantitative geography and GIS. It is a timely, thorough and exciting account of the state of the art and science of spatial analysis′ - Paul Longley, University of Bristol `A highly innovative and up-to-date text. It is unique in its coverage of the many developments that have taken place in the field over the past few years. The book is one that is highly readable and stimulating for those with some background in the field, and its expositional style and many examples will make it stimulating to newcomers as well′ - Peter Rogerson, State University of New York at Buffalo`Brings the field thoroughly up to date, integrating modern methods of GIS with a comprehensive and easy-to-read overview of the most recent and powerful techniques of spatial analysis. The book will be valuable to students and researchers in any discipline that seeks to explore or explain phenomena in geographical context, and will make excellent reading for geographers, political scientists, criminologists, anthropologists, geologists, epidemiologists, ecologists, and many others. It offers a spirited challenge to critics of a scientific approach to social science, and demonstrates the value of its subject matter through abundant examples′ - Michael Goodchild, National Center for Geographic Information and Analysis, University of California, Santa Barbara`There is a view within some parts of academic geography that what used to be called "quantitative geography" is dead, having been subsumed within "geographical information systems" or else of no continuing interest. This book should correct this view. First, it shows that quantitative methods have remained an exciting area of development and, second, it shows that, if anything, they have more relevance to substantive problems of interest than they have ever had. Although not specifically about GIS, it is a book that should be read by everyone concerned with the analysis of geographicalinformation′ - David Unwin, Birkbeck College, University of London

• Establishing the BoundariesSpatial Data The Role of Geographic Information SystemsExploring Spatial Data VisuallyLocal AnalysisPoint Pattern AnalysisSpatial Regression and Geostatistical ModelsStatistical Inference for Spatial DataSpatial Modelling and the Evolution of Spatial Theory Challenges in Spatial Data Analysis