Geodemographics and GIS – Richard Harris, Peter Sleight, Richard Webber

Geographic information systems have been described as a set of technologies that help us to see our small blue planet in better ways (Longley et al., 1999). More commonly referred to by the acronym GIS, applications include: local governance; business and service planning; logistics; and environmental management and modelling. In both public and private sector research, GIS are used to manage geographic information, help identify geographical trends and patterns and to model spatial processes.

However, GIS have been described as a β€œnearly” technology for marketers (McLuhan, 2003). Beyond the hype, the actual use of GIS presently is limited to the larger retailers and suppliers, with little expansion into marketing applications. This, despite widespread agreement that the true value of geographical information is only revealed once that information is analysed geographically! McLuhan (2003) cites a survey by GeoBusiness Solutions revealing that only 28% of company boards fully understand the operation and marketing benefits of GIS, with the perceived (and often, actual) high cost of investing in GI software and data products being one of the barriers to GIS reaching its potential.

In this chapter they agree with those who see virtue in GIS as tools for managing, analysing and visualizing geographical information; who use them to look at where things happen (or not), to help explain what occurrences are associated with which places and why, and to use that knowledge for planning and management. Yet, we shall also argue that the sorts of tools and methods required by a β€œtypical” geodemographic user are not necessarily those provided by a standard desktop GIS, which has its origins, for instance, in environmental research. A distinction will be made between geographical information systems (GIS) in a broad sense and geodemographic information systems (GDIS) that cater for a more specific clientele.

In this chapter they set the scene for that discussion by first outlining some of the more general principles of neighbourhood analysis that are conducted within a computerized environment and by providing and introduction to some of the principles, theories and methods of the inter-disciplinary subject known as geographical information science (GISc). Readers who wish to β€œdig deeper” into this field should refer to the suggested further reading listed at the close of this chapter.



With the proliferation and diversity of GIS applications it is not surprising that there are many definitions of GIS, each reflecting the nuance and perspectives of different users’ interests. Nevertheless, there is much shared ground and this leads to a commonly recognized view of GIS as a system of β€œcomponent tools used to capture, store, transform, analyse, and display geographical data” (Haggett, 2001, p. 719).

Hagget’sΒ  definition of GIS raises the question of β€œwhat are geographical data”? Literally these are data that describe processes, events or activities that take place on or near the Earth’s surface and which record where those processes, events or activities take place. The key characteristic of a geographic dataset is that it contains both attribute information and information about location. Attribute information is about the process, event or activity being measured (e.g. the temperature is 26Β° C; the building density is 30 dwellings per hectare; the customers on average visit once a week). Location adds where the data were collected or apply to (e.g. the temperature in Paris is 26Β° C; the building density within postcode BS16 7DX is 30 dwellingsΒ  per hectare; the customers visiting the Southbridge store at grid reference x = 529600, y = 181500 do so on average once a week).

There are several terms to describe the act of assigning location to attribute information, including georeferencing (our preference), geolocating and geocoding (Longley et al., 2001). It is the act of georeferecing that transforms data from being non-geographical (aspatial) to geographical (spatial). Georeferencing data is usually a first step towards the mapping and analysis of attribute information within a GIS to create, for example, maps of customers records, population data or neighbourhood statistics.



We have commented that geodemographics is the analysis of people by where they live. Linking this to a GIS framework, the knowledge of where people live, work or socialize is the location component.

Data about what people do to live, work or socialize is the attribute information. In other words, Location + Attributes = Geography + DemographicsΒ = GeoDemographics!

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