Robustness Analysis of Urban Street Networks Using Complex Network Method

被引:0
|
作者
Tian J. [1 ,2 ,3 ]
Fang H. [4 ]
Liu J. [1 ]
Zhao F. [1 ]
Ren C. [1 ,5 ]
机构
[1] School of Resource and Environmental Sciences, Wuhan University, Wuhan
[2] Key Laboratory of Geographic Information System, Ministry of Education, Wuhan University, Wuhan
[3] Key Laboratory of Digital Mapping and Land Information Application Engineering, National Administration of Surveying, Wuhan University, Wuhan
[4] College of Engineering, Peking University, Beijing
[5] State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan
基金
中国国家自然科学基金;
关键词
Cascade model; Successive removal model; Topological properties; Urban street networks;
D O I
10.13203/j.whugis20150334
中图分类号
学科分类号
摘要
Robustness analysis of street network can contribute to the precaution and loss reduction of terrorism attacks, natural disasters and traffic congestion. We have obtained 50 urban road networks around the world from OpenStreetMap. On the basis of complex network robustness analysis method, we utilize the successive removal model and the cascade model to analyze the urban road network represented by the intersecting relationship of patterns, and discuss the relationship between the robustness of the road network and its topological patterns. It is found that the robustness varies when the network is under different attack model; it also differentiates when the attach strategy is targeting high-degree or high-betweenness nodes. The robustness of urban street networks is sensitive to the attach model and strategy. The road networks show less robustness under consecutive attack, while they vary considerably under cascade attack. In terms of the attack strategies, the betweenness strategy is more destructive than degree strategy under successive removal and the cascade models, which signifies that the high-betweenness nodes play a more important role. The assortativity of street network is significantly positively correlated with its robustness against successive removal of nodes while significant difference observed for the robustness of scale-free and non-scale-free networks under the same model. The robustness under cascade attack shows no correlation with network assortativity and does not differ significantly between groups of different scale-free properties. © 2019, Editorial Department of Wuhan University of Technology. All right reserved.
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页码:771 / 777
页数:6
相关论文
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