Topological Patterns of Spatial Urban Street Networks

Abstract

In this paper we analyze the structural properties of four urban street networks in China based on GIS and complex networks theory. We consider the street networks as spatial networks and use the primal approach to turn the GIS data into graph. The urban street networks display similar topological patterns and deviate from random networks and central planned networks, despite the apparent differences in terms of historical, economic and geographic characters. Multiple centrality measures are introduced and used in the network vulnerability analysis. We show that urban street networks are vulnerable to selected attack but robust to random attack. Degree and betweeness measures are very useful in important nodes identification and crisis prevention.