Geodemographics and the practices of geographic information science

Abstract

At the core of geographic information science (GIScience) lie enduring organising principles and concepts that have been developed using research methods that are robust, transparent and scientifically reproducible. Yet it is also a science of real-world problem solving, which has come to prominence at a time in which the nature and volume of geographic information (and the human activities that generate it) are profoundly changing. This article assesses and interprets these changes in the context of Goodchild's assessment of challenges to GIScience, using examples from 'geodemographics' -the analysis of people according the places where they live. The conclusions have repercussions not only for the way that we think about neighbourhood profiling, but also for the practice of GIScience itself, specifically with regard to reconciling new sources of 'big' spatial data and understanding the inherent vagaries of citizen science; linkage of conventional social, economic and demographic geographies to patterns of virtual interactions at fine levels of spatial granularity; and improving understanding of the ways in which 'open' geodemographics are specified, estimated and tested.

Carbon footprints of cities and other human settlements in the UK

“…The term 'geo-demographic' is defined broadly as 'analysis of people by where they live' (Harris et al 2005). This can be seen as an attempt to classify areas and their associated lifestyles in terms of collective consumption and locational proximity including geographic, infrastructural as well as socio-demographic factors that characterize them (Harris et al 2005, Longley 2012). As geo-demographics are already defined by spatial and consumption factors, a geo-demographic concept is more adequate to be applied to CF analysis of human settlements (Duchin 1998, Duchin and Hubacek 2003, Baiocchi and Minx et al 2010.…”

A new geodemographic classification of commuting flows for England and Wales

“…4 The brief analysis undertaken in this paper demonstrates the potential for the classification to be used to describe and analyse patterns and structures of commuting differentiated by types of commuter. This analysis could be extended by aligning the classification to area taxonomies in a modelling framework that integrates local spatial context and commuting behaviour (Longley 2012, Singleton et al 2012. This could enable the identification of different places and groups of commuters that could conceivably benefit from the targeting of discrete mobility-related interventions (Ponti et al 2013, Lovelace et al 2014.…”

A spatial typology of human settlements and their CO2 emissions in England

“…Today, entire research fields such as geo-demographics or other variants of consumer segmentation are built around the importance of place-specific contextualization for the prediction of consumer behaviour (Harris et al, 2005;Longley, 2012). The local context is equally important for understanding and predicting the carbon output of settlement areas.…”