Suggested reading

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Suggested reading

There are numerous excellent modern books on GIS and spatial analysis, although few address software facilities and developments. Hypertext links are provided here, and throughout the text where they are cited, to the more recent publications and web resources listed.

As a background to this Guide any readers unfamiliar with GIS are encouraged to first tackle “Geographic Information Science and Systems” (GISSc) by Longley et al. (2015). GISSc seeks to provide a comprehensive and highly accessible introduction to the subject as a whole. The GB Ordnance Survey’s “GIS pages” also provides an excellent brief introduction to GIS and its applications.

Some of the basic mathematics and statistics of relevance to GIS analysis is covered in Dale (2005) and Allan (2004). For detailed information on datums and map projections, see Iliffe and Lott (2008). Useful online resources for those involved in data analysis, particularly with a statistical content, include the StatsRef website and the e‑Handbook of Statistical Methods produced by the US National Institute on Standards and Technology, NIST). The more informally produced set of articles on statistical topics provided under the Wikipedia umbrella are also an extremely useful resource. These sites, and the mathematics reference site, Mathworld, are referred to (with hypertext links) at various points throughout this document. For more specific sources on geostatistics and associated software packages, the European Commission’s AI‑GEOSTATS website (now a separate WIKI website) is highly recommended, as is the web site of the Center for Computational Geostatistics (CCG) at the University of Alberta. For those who find mathematics and statistics something of a mystery, de Smith (2018) and Bluman (2003) provide useful starting points. For guidance on how to avoid the many pitfalls of statistical data analysis readers are recommended the material in the classic work by Huff (1993) “How to lie with statistics”, and the 2008 book by Blastland and Dilnot “The tiger that isn’t”.

A relatively new development has been the increasing availability of out-of-print published books, articles and guides as free downloads in PDF format. These include: the series of 59 short guides published under the CATMOG umbrella (Concepts and Methods in Modern Geography), published between 1975 and 1995, most of which are now available at the QMRG website (a full list of all the guides is provided at the end of this book); the Atlas of Cyberspace by Dodge and Kitchin; and Fractal Cities, by Batty and Longley.

Undergraduates and MSc programme students will find Burrough and McDonnell (1998, 2015) provides excellent coverage of many aspects of geospatial analysis, especially from an environmental sciences perspective. Valuable guidance on the relationship between spatial process and spatial modeling may be found in Cliff and Ord (1981) and Bailey and Gatrell (1995). The latter provides an excellent introduction to the application of statistical methods to spatial data analysis. O’Sullivan and Unwin (2010, 2nd ed.) is a more broad-ranging book covering the topic the authors describe as “Geographic Information Analysis”. This work is best suited to advanced undergraduates and first year postgraduate students. In many respects a deeper and more challenging work is Haining’s (2003) “Spatial Data Analysis — Theory and Practice”. This book is strongly recommended as a companion to the present Guide for postgraduate researchers and professional analysts involved in using GIS in conjunction with statistical analysis.

However, these authors do not address the broader spectrum of geospatial analysis and associated modeling as we have defined it. For example, problems relating to networks and location are often not covered and the literature relating to this area is scattered across many disciplines, being founded upon the mathematics of graph theory, with applications ranging from electronic circuit design to computer networking and from transport planning to the design of complex molecular structures. Useful books addressing this field include Miller and Shaw (2001) “Geographic Information Systems for Transportation” (especially Chapters 3, 5 and 6), and Rodrigue et al. (2006) "The geography of transport systems" (see further:

As companion reading on these topics for the present Guide we suggest the two volumes from the Handbooks in Operations Research and Management Science series by Ball et al. (1995): “Network Models”, and “Network Routing”. These rather expensive volumes provide collections of reviews covering many classes of network problems, from the core optimization problems of shortest paths and arc routing (e.g. street cleaning), to the complex problems of dynamic routing in variable networks, and a great deal more besides. This is challenging material and many readers may prefer to seek out more approachable material, available in a number of other books and articles, e.g. Ahuja et al. (1993), Mark Daskin’s excellent book “Network and Discrete Location” (1995) and the earlier seminal works by Haggett and Chorley (1969), and Scott (1971), together with the widely available online materials accessible via the Internet. Final recommendations here are Stephen Wise’s excellent GIS Basics (2002) and Worboys and Duckham (2004) which address GIS from a computing perspective. Both these volumes covers many topics, including the central issues of data modeling and data structures, key algorithms, system architectures and interfaces.

Many recent books described as covering (geo)spatial analysis are essentially edited collections of papers or brief articles. As such most do not seek to provide comprehensive coverage of the field, but tend to cover information on recent developments, often with a specific application focus (e.g. health, transport, archaeology). The latter is particularly common where these works are selections from sector- or discipline-specific conference proceedings, whilst in other cases they are carefully chosen or specially written papers. Classic amongst these is Berry and Marble (1968) “Spatial Analysis: A reader in statistical geography”. More recent examples include “GIS, Spatial Analysis and Modeling” edited by Maguire, Batty and Goodchild (2005), and the excellent (but costly) compendium work “The SAGE handbook of Spatial Analysis” edited by Fotheringham and Rogerson (2008).

A second category of companion materials to the present work is the extensive product-specific documentation available from software suppliers. Some of the online help files and product manuals are excellent, as are associated example data files, tutorials, worked examples and white papers (see for example, ESRI’s What is GIS?), which provides a wide-ranging guide to GIS. In many instances we utilize these to illustrate the capabilities of specific pieces of software and to enable readers to replicate our results using readily available materials. In addition some suppliers, notably ESRI, have a substantial publishing operation, including more general (i.e. not product specific) books of relevance to the present work. Amongst their publications we strongly recommend the “ESRI Guide to GIS Analysis Volume 1: Geographic patterns and relationships” (1999) by Andy Mitchell, which is full of valuable tips and examples. This is a basic introduction to GIS Analysis, which he defines in this context as “a process for looking at geographic patterns and relationships between features”. Mitchell’s Volume 2 (July 2005) covers more advanced techniques of data analysis, notably some of the more accessible and widely supported methods of spatial statistics, and is equally highly recommended. A number of the topics covered in his Volume 2 also appear in this Guide. David Allen has produced a tutorial book and DVD (GIS Tutorial II: Spatial Analysis Workbook) to go alongside Mitchell’s volumes, and these are obtainable from ESRI Press.  For a perspective on modern applications of GIS and geospatial analysis see Esri's GIS For Science series (Volume 3 is the latest and Chapter 7 focuses on geospatial analysis and AI, also referred to now as GeoAI) and the recently published collection of edited chapters brought together as the "Handbook of Geospatial Artificial Intelligence" (2024, Song Gao et al., with a Foreword by Prof Mike Goodchild). Those considering using Open Source software may wish to investigate the books by Neteler and Mitasova (2008), Tyler Mitchell (2005) and Sherman (2008).

In parallel with the increasing range and sophistication of spatial analysis facilities to be found within GIS packages, there has been a major change in spatial analytical techniques. In large measure this has come about as a result of technological developments and the related availability of software tools and detailed publicly available datasets. One aspect of this has been noted already — the move towards network-based location modeling where in the past this would have been unfeasible. More general shifts can be seen in the move towards local rather than simply global analysis, for example in the field of exploratory data analysis; in the increasing use of advanced forms of visualization as an aid to analysis and communication; in the growth of online spatial data, mapping and analysis services; in the development of a wide range of computationally intensive and simulation methods that address problems through micro-scale processes (geocomputational methods); and finally, in the recent development of AI-augmented services, many of which fit within the somewhat portmanteau term, GeoAI. These trends are addressed at many points throughout this Guide.