Abstract
Spatial embeddedness and planarity of urban road networks limit the range of their node degree values. Therefore, pursuing analysis based on the distribution of node degrees e.g. scale free aspect could not be accomplished in urban road networks. We have inspected the distribution of degree, betweenness centrality, weighted degree (based on incident link capacities), and alpha weighted degree for eight urban road networks across the world. These networks are abstracted from Philadelphia (USA), Berlin (Germany), Chicago (USA), Anaheim (USA), Gold Coast (Australia), Birmingham (UK), and Isfahan (Iran). Our results show that although the degree (weighted and unweighted) distributions of these networks are totally different, they all show power law distributions in betweenness centrality. Thus, scale free aspect could be observed in the betweenness centrality distribution. We then analyzed the collapse of network as a result of node removals. The collapse patterns suggest that critical nodes of urban road networks could not be detected solely based on betweenness centrality. Therefore, we conclude that the concept of betweenness centrality in urban road networks is more of functional merit than topological merit. In other words, central nodes play an important role in transmitting the flow but their loss would not harm the connectivity of urban networks. This claim is supported by analyzing the correlation among node flow and node betweenness in Isfahan and Anaheim.
Highlights
Introduction and methodologyIn an urban context, by abstracting intersections as nodes and streets as links, an urban road network is developed
We show that regardless of degree distribution, betweenness centrality shows a power law distribution
We conclude that the distribution of betweenness centrality values of urban road networks demonstrate power law behavior, this does not mean that nodes with highest values of BC are the most critical nodes
Summary
Introduction and methodologyIn an urban context, by abstracting intersections as nodes and streets as links, an urban road network is developed. In order to overcome obstacles caused by the limited range of node degree values, we analyze other network metrics and see if global patterns could be detected in them across different urban contexts. Alpha weighted degree (CwDαðiÞ) has been developed to evaluate the centrality of a node based on the number and the importance of its neighbors (Opsahl et al 2010): C
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