Associating street-network centrality with spontaneous and planned subcentres


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Özüduru B. H. , Webster C. J. , Chiaradia A. J. F. , Yücesoy E.

URBAN STUDIES, vol.58, no.10, pp.2059-2078, 2021 (SSCI) identifier identifier

  • Publication Type: Article / Article
  • Volume: 58 Issue: 10
  • Publication Date: 2021
  • Doi Number: 10.1177/0042098020931302
  • Journal Name: URBAN STUDIES
  • Journal Indexes: Social Sciences Citation Index (SSCI), Scopus, Academic Search Premier, IBZ Online, International Bibliography of Social Sciences, Periodicals Index Online, ABI/INFORM, American History and Life, Business Source Elite, Business Source Premier, EconLit, Educational research abstracts (ERA), Geobase, Historical Abstracts, PAIS International, Political Science Complete, Public Administration Abstracts, Public Affairs Index, Social services abstracts, Sociological abstracts, Worldwide Political Science Abstracts, DIALNET
  • Page Numbers: pp.2059-2078
  • Keywords: Ankara, accessibility, centrality, city centres, clustering, street network, ECONOMIC-ACTIVITIES, ACCESSIBILITY, LOCATION, RETAIL, AGGLOMERATION, CENTERS, SPACE, ROAD, GEOGRAPHY, SHANGHAI
  • Gazi University Affiliated: Yes

Abstract

Scientific studies have long demonstrated how economic activities regularly distribute themselves within a city in response to geographical centrality. Following the growing interest in network geography in understanding urban dynamics, rather than measuring centrality (accessibility) bya prioriknowledge of central business district (CBD) locations, in this article we measure the centrality of each link in a city's street network, modelled as a topological graph. We use this to understand clustering behaviour of firms by industrial classification in the city of Ankara, Turkey. Our underlying hypothesis rests on the assumption that the geometry and topology of an urban grid contains accessibility information about the distribution of agglomeration economies and diseconomies, and that different types of enterprises are sensitive to this distribution in various ways. Among other things, the results of the study allow us to predict the evolution of what we call candidate centres (locations that could, by virtue of their connectivity footprint, become subcentres), actual subcentres and CBD functions in response to changes in a city's street network. Decoding how commercial cluster locations interact with the detailed pattern of street-network-based centralities will be helpful for urban planning policy, in particular for commercial zoning decisions such as expanding CBDs and identifying locations for new subcentres that have an acceptable chance of success.