Great cities look small
Aaron Sim, Sophia N Yaliraki, Mauricio Barahona, Michael P H Stumpf

TL;DR
This paper introduces a mathematical model to quantify urban connectivity based on human interaction strategies constrained by travel time, validated with economic and health data, and applied to assess transport infrastructure impacts.
Contribution
The paper develops a novel model of city connectivity that incorporates real transport data and explains urban indicator scaling through mechanistic interactions.
Findings
Connectivity correlates with GDP and health outcomes.
Transport developments significantly impact city connectivity.
Model explains urban scaling laws mechanistically.
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 maximising 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 characterise 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…
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