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Measuring polycentricity via network flows, spatial interaction and percolation

Author

Listed:
  • Somwrita Sarkar

    (School of Architecture, Design and Planning, The University of Sydney, Australia)

  • Hao Wu

    (School of Civil Engineering, Faculty of Engineering and Information Technologies, The University of Sydney, Australia)

  • David M Levinson

    (School of Civil Engineering, Faculty of Engineering and Information Technologies, The University of Sydney, Australia)

Abstract

Polycentricity, or the number of central urban places, is commonly measured by location-based metrics (e.g. employment density/total number of workers, above a threshold). While these metrics are good indicators of location ‘centricity’, results are sensitive to threshold choice. We consider the alternative idea that a centre’s status depends on its connectivity to other locations through trip inflows/outflows: this is inherently a network rather than place idea. Three flow and network-based centricity metrics for measuring metropolitan area polycentricity using journey-to-work data are presented: (a) trip-based; (b) density-based; and (c) accessibility-based. Using these measures, polycentricity is computed and rank-centricity distributions are plotted to test Zipf-like or Christaller-like behaviours. Further, a percolation theory framework is proposed for the full origin–destination matrix, where trip flows are used as a thresholding parameter to count the number of sub-centres. Trip flows prove to be an effective measure to count and hierarchically organise metropolitan areas and sub-centres, tackling the arbitrariness of defining any threshold on employment statistics to count sub-centres. Applications on data from the Greater Sydney region show that the proposed framework helps to characterise polycentricity and sub-regional organisation more robustly, and provide unexpected insights into the connections between land use, labour market organisation, transport and urban structure.

Suggested Citation

  • Somwrita Sarkar & Hao Wu & David M Levinson, 2020. "Measuring polycentricity via network flows, spatial interaction and percolation," Urban Studies, Urban Studies Journal Limited, vol. 57(12), pages 2402-2422, September.
    • Handle: RePEc:sae:urbstu:v:57:y:2020:i:12:p:2402-2422
    DOI: 10.1177/0042098019832517
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    References listed on IDEAS

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    Cited by:

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    2. Popovich, Natalie & Spurlock, C. Anna & Needell, Zachary & Jin, Ling & Wenzel, Tom & Sheppard, Colin & Asudegi, Mona, 2021. "A methodology to develop a geospatial transportation typology," Journal of Transport Geography, Elsevier, vol. 93(C).
    3. Ermagun, Alireza, 2021. "Transit access and urban space-time structure of American cities," Journal of Transport Geography, Elsevier, vol. 93(C).
    4. Allen, Jeff & Farber, Steven & Greaves, Stephen & Clifton, Geoffrey & Wu, Hao & Sarkar, Somwrita & Levinson, David M., 2021. "Immigrant settlement patterns, transit accessibility, and transit use," Journal of Transport Geography, Elsevier, vol. 96(C).
    5. Oliveira, Renata Lúcia Magalhães de & Dablanc, Laetitia & Schorung, Matthieu, 2022. "Changes in warehouse spatial patterns and rental prices: Are they related? Exploring the case of US metropolitan areas," Journal of Transport Geography, Elsevier, vol. 104(C).

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