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Measuring polycentricity via network flows, spatial interaction, and percolation
Recent working paper:
Sarkar, Somwrita, Wu, Hao and Levinson, D. (2018) Measuring polycentricity via network flows, spatial interaction, and percolation.
Polycentricity is most commonly measured by location-based metrics (e.g. employment density or total number of workers, above a threshold, used to count the number of centres). While these metrics are good indicators of location ‘centricity’, the results are sensitive to threshold-choice. We consider here the alternate idea that a centre’s status depends on which other locations it is con- nected to in terms of trip inflows and outflows: this is inherently a network rather than a location idea. A set of flow and network-based centricity metrics for measuring metropolitan area poly- centricity using Journey-To-Work (JTW) 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 whether these distributions follow Zipf-like or Chirstaller-like distributions. Further, a percolation theory framework is proposed for the full origin-destination (OD) matrix, where trip flows are used as a thresholding parameter to count the number of sub-centres. It is found that trip flows prove to be an effective measure to count and hierarchically organise metropolitan area sub-centres, and provide one way of dealing with the arbitrariness of defining a threshold on numbers of employed persons, employment density, or centricities to count sub-centres. These measures demonstrated on data from the Greater Sydney region show that the trip flow-based threshold and network centricities help to characterize polycentricity more robustly than the traditional number or density-based thresholds alone and provide unexpected insights into the connections between land use, transport, and urban structure.