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Urban population distribution models and service accessibility estimation

Langford, M., Higgs, G., Radcliffe, Jonathan Stephen and White, Sean Damian 2008. Urban population distribution models and service accessibility estimation. Computers, Environment and Urban Systems 32 (1) , pp. 66-80. 10.1016/j.compenvurbsys.2007.06.001

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Abstract

This paper examines the influence of alternative population distribution models on GIS-based spatial accessibility analyses using the two-step Floating Catchment Analysis technique. Two population models were tested: the de facto standard of even-distribution within census tracts and a dasymetric-based approach. The latter builds on previous research through the use of a novel methodology that integrates raster map data with a recently built mailing information database in order to enhance the precision with which residential areas are identified. Analysis was conducted for a case study area (Cardiff, South Wales) in order to examine variations in accessibility to a number of public services in the city. The dasymetric model showed a general tendency to report lower accessibility scores, but detailed patterns depended on local factors and, to some extent, on modelling assumptions and methodological issues. A paired T-Test analysis demonstrated that significant differences in outcomes were dependant on the population model adopted. Accessibility-based measures are increasingly being incorporated into deprivation indicators and the paper concludes by suggesting that, if such analysis is to inform urban planning, local service provision and the spatial allocation of financial resources, greater attention needs to be given to the method of population representation utilised in such models.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Geography and Planning (GEOPL)
Subjects: H Social Sciences > HT Communities. Classes. Races
Uncontrolled Keywords: Population estimation models; Dasymetric techniques; Accessibility measures; Floating catchment analysis; GIS
Publisher: Elsevier
ISSN: 0198-9715
Last Modified: 07 Nov 2019 09:08
URI: http://orca-mwe.cf.ac.uk/id/eprint/17601

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