Topological Convergence of Urban Infrastructure Networks
Christopher Klinkhamer, Jonathan Zischg, Elisabeth Krueger, Soohyun, Yang, Frank Blumensaat, Christian Urich, Thomas Kaeseberg, Kyungrock Paik,, Dietrich Borchardt, Julian Reyes Silva, Robert Sitzenfrei, Wolfgang Rauch,, Gavan McGrath, Peter Krebs, Satish Ukkusuri, and P.S.C. Rao

TL;DR
This study analyzes 125 urban infrastructure networks across 52 cities, revealing common topological features, generative mechanisms, and implications for resilience and design of critical city services.
Contribution
It demonstrates the convergence in the topology of diverse urban networks and proposes a partial preferential attachment model constrained by geospatial factors.
Findings
Node-degree distributions fit Pareto distributions.
Variance decreases with network size, indicating convergence.
High correlation between co-located networks affects network resilience.
Abstract
Urban infrastructure networks play a major role in providing reliable flows of multitude critical services demanded by citizens in modern cities. We analyzed here a database of 125 infrastructure networks, roads (RN); urban drainage networks (UDN); water distribution networks (WDN), in 52 global cities, serving populations ranging from 1,000 to 9,000,000. For all infrastructure networks, the node-degree distributions, p(k), derived using undirected, dual-mapped graphs, fit Pareto distributions. Variance around mean gamma reduces substantially as network size increases. Convergence of functional topology of these urban infrastructure networks suggests that their co-evolution results from similar generative mechanisms. Analysis of growing UDNs over non-concurrent 40 year periods in three cities suggests the likely generative process to be partial preferential attachment under geospatial…
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Taxonomy
TopicsComplex Network Analysis Techniques · Urban Design and Spatial Analysis · Slime Mold and Myxomycetes Research
