Locating Household Profiles in a Polycentric Region to Refine the Inputs to an Agent-Based Model of Residential Mobility

Corentin M Fontaine, Mark D A Rounsevell and Anne-Christelle Barbette
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Corentin M Fontaine: Department of Geography, Namur Centre for Complex Systems, and Namur Interdisciplinary Research Group for Sustainability, Faculty of Sciences, University of Namur, Rue de Bruxelles 61, 5000 Namur, Belgium; and Geography and the Lived Environment, School of GeoSciences, The University of Edinburgh, Drummond Street, Edinburgh EH8 9XP, Scotland
Mark D A Rounsevell: Geography and the Lived Environment, School of GeoSciences, The University of Edinburgh, Drummond Street, Edinburgh EH8 9XP, Scotland
Anne-Christelle Barbette: Department of Geography, University of Louvain, Place Louis Pasteur 3, 1348 Louvain-la-Neuve, Belgium

Environment and Planning B, 2014, vol. 41, issue 1, 163-184

Abstract: In this paper we present a method to analyse data from observed population statistics in order to create a stylised location typology based on household profiles (microgeographic level). The household profiles are used to inform the development of rules for an agent-based model of residential population mobility. The method is demonstrated with the 2001 Population Census data for East Anglia, UK. Household profiles are derived from a principal components analysis to reduce dimensionality in the census data combined with a cluster analysis to aggregate the observations. We test whether a range of household archetypes that link specific locations to specific profiles can be identified simultaneously at both mesogeographic and macrogeographic levels. Results reaffirm conventional archetypes: Single people concentrate in city centres, families mainly locate in the suburbs and periurban areas, and retirees are more prevalent in the suburbs and close to the coast. Surprisingly, however, there is a clear distinction between locations with cohabiting couples (located at the fringe of the periurban areas) and locations with married couples (located in the countryside). The observed spatial distributions reveal different location choices between different household profiles. Identification of these household profiles supports the development of residential mobility models that may be used to explore regional and local planning issues with respect to future population projections and environmental change.

Keywords: location preferences; typology; factor analysis; cluster analysis; urban land-use change; agent-based modeling; residential mobility (search for similar items in EconPapers)
Date: 2014
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Persistent link: https://EconPapers.repec.org/RePEc:sae:envirb:v:41:y:2014:i:1:p:163-184

DOI: 10.1068/b37072

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