Great cities look small.
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Published version
Accepted version
Author(s)
Sim, A
Yaliraki, SN
Barahona, M
Stumpf, MP
Type
Journal Article
Abstract
Great cities connect people; failed cities isolate people. Despite the fundamental importance of physical, face-to-face social ties in the functioning of cities, these connectivity networks are not explicitly observed in their entirety. Attempts at estimating them often rely on unrealistic over-simplifications such as the assumption of spatial homogeneity. Here we propose a mathematical model of human interactions in terms of a local strategy of maximizing the number of beneficial connections attainable under the constraint of limited individual travelling-time budgets. By incorporating census and openly available online multi-modal transport data, we are able to characterize the connectivity of geometrically and topologically complex cities. Beyond providing a candidate measure of greatness, this model allows one to quantify and assess the impact of transport developments, population growth, and other infrastructure and demographic changes on a city. Supported by validations of gross domestic product and human immunodeficiency virus infection rates across US metropolitan areas, we illustrate the effect of changes in local and city-wide connectivities by considering the economic impact of two contemporary inter- and intra-city transport developments in the UK: High Speed 2 and London Crossrail. This derivation of the model suggests that the scaling of different urban indicators with population size has an explicitly mechanistic origin.
Date Issued
2015-07-15
Date Acceptance
2015-06-23
Citation
Journal of the Royal Society Interface, 2015, 12 (109)
ISSN
1742-5689
Publisher
Royal Society, The
Journal / Book Title
Journal of the Royal Society Interface
Volume
12
Issue
109
Copyright Statement
© 2015 The Authors. Published by the Royal Society under the terms of the Creative Commons Attribution
License http://creativecommons.org/licenses/by/4.0/, which permits unrestricted use, provided the original
author and source are credited.
License http://creativecommons.org/licenses/by/4.0/, which permits unrestricted use, provided the original
author and source are credited.
License URL
Identifier
PII: rsif.2015.0315
Subjects
infrastructure
population models
social networks
Publication Status
Published