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Delineating the perceived functional regions of London from commuting flows

Bibliographic Data

ID5031641
AuthorsYao Shen (0000-0002-7261-4234, Tongji University, P.R. China; University College London, UK, corresponding author), Michael Batty (0000-0002-9931-1305, University College London, UK)
Year2019
Volume51
Issue3
Pages547-550
Publication date2019-05-01
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueEnvironment and Planning A Economy and Space (JOURNAL)
Journal identifiersISSN: 0308-518X • E-ISSN: 1472-3409
PublisherSAGE Publications Inc (PUBLISHER)
DOI10.1177/0308518x18786253
OpenAlexW2881698119
LanguageEN
Citations received17
References cited7

Well-connected urban areas defined by different types of urban flow define the boundaries reflecting the relatedness of places in terms of their functionality. Yet, attempts to define cities and their communities based on aggregated data normally neglect the inherent differences between different groups of people. Based on the disaggregated flow data, this study detects community structures in the London Metropolitan Area perceived by different occupations by using the multi-level modularity optimisation algorithm. The results show the difference between our perceptions of different functional regions across occupations. The higher managerial groups have a more global sense than the lesser managerial occupations who have more segmented and local perceptions regarding their functional regions. This is well illustrated by the shift of the documented modularity scores across groups. Although the transport network and various natural boundaries do play a part in the locational patterns of the derived communities, it is found that the relative self-containment of functional regions is interpreted differently by different occupations. This kind of representation is of great value in advancing our knowledge regarding how different places are perceived by different occupations with all the implications for future commuting that future planning for housing and employment will bring

Economic geography · Geography · Metropolitan area · Neglect · Perception · Political science · Regional science · Sociology · Computer Science · Human Mobility and Location-Based Analysis · Land Use and Ecosystem Services · Psychology · Urban Design and Spatial Analysis

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Unique citing works17
Citations per year2,83
Citation span2020 - 2026 (7)
Citation velocitycurrent
Highly citedNo
Citation typesNeutral: 16

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