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@article{Sim:2015:10.1098/rsif.2015.0315,
author = {Sim, A and Yaliraki, SN and Barahona, M and Stumpf, MP},
doi = {10.1098/rsif.2015.0315},
journal = {Journal of the Royal Society Interface},
title = {Great cities look small.},
url = {http://dx.doi.org/10.1098/rsif.2015.0315},
volume = {12},
year = {2015}
}
TY - JOUR
AB - 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.
AU - Sim,A
AU - Yaliraki,SN
AU - Barahona,M
AU - Stumpf,MP
DO - 10.1098/rsif.2015.0315
PY - 2015///
SN - 1742-5689
TI - Great cities look small.
T2 - Journal of the Royal Society Interface
UR - http://dx.doi.org/10.1098/rsif.2015.0315
UR - http://hdl.handle.net/10044/1/25290
VL - 12
ER -