The use of spatial data is increasing across a broad range of disciplines. The Sage Handbook of Spatial Analysis, edited by Fotheringham and Rogerson, is marketed as a response to this growing demand for specialized statistical and mathematical methods for spatial data. The contributions to this book are written for academics and graduate level students; this is reflected by the relatively high RRP.
The Sage Handbook of Spatial Analysis provides an extension to many of the topics covered by Fotheringham et al’s (2000) Quantitative Geography. Each of the book’s 25 chapters are written by leaders in their respective fields with the list of contributors including Michael Goodchild, David Martin and Luc Anselin; expertise that is reflected by the clarity and currency of much of this book.
Due to the breadth of topics and contributors to this volume I thought it best to provide general overview of the book with select comments on a couple of specific examples. The book can be split into two broad sections. The first focuses on established concepts, and the second outlines key spatial analysis methodologies. Topics covered by the first 12 chapters include the role of GIS, the modifiable areal unit problem (MAUP), geovisualization, spatial autocorrelation and spatial sampling. These early chapters are invaluable, especially to those recently initiated to advanced spatial analysis methodologies. They provide important context for understanding the later chapters of the book.
Beyond chapter 12 the focus becomes more methods-based to cover concepts such as geographically weighted regression (GWR), the detection of spatial clusters, Bayesian spatial analysis, and neural networks. These provide useful reference material to those looking for a “way in” to a particular method. Several authors, for example Fotheringham on GWR, are integral to the development of the methods and concepts they are describing and therefore provide the most authoritative explanations of them. The final two chapters are more conceptual as they discuss the challenges facing, and suggested future directions for, spatial analysis.
Integrating spatial analysis with remotely sensed data is not covered in this volume. It could, however, be included in a chapter on spatial data types and their reliability. An in depth overview of the types of spatial data and their limitations may help readers to avoid some pitfalls that could undermine their subsequent spatial analysis. In addition, the “Future for Spatial Analysis” chapter appears to conflate spatial analysis and geography. The statement that “spatial analysis holds the key for geography” is a view opposed by many who argue that in fact “geography holds the key for spatial analysis”. The contributions of geographic thought to spatial analysis are not considered. Without such considerations, there is risk that many of the quantitative methodologies developed for spatial analysis face being ignored by mainstream geography. A more balanced view has recently been published in the The Professional Geographer, Volume 61, Number 3 (2009).
The criticisms are minor and should detract very little from The SAGE Handbook of Spatial Analysis. The comprehensive insights provided by the world leading contributors are invaluable, and provide a summary of the many excellent books they have written separately on the subsets of spatial analysis. Despite its cost, this book remains a worthwhile investment for any graduate student wishing to develop a firm grounding in cutting edge spatial analysis.
Editors: A. Stewart Fotheringham, Peter A. Rogerson.
RRP: £90 (£85 on Amazon).
511 pages (Hardback).