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Generative network models for simulating urban networks, the case of inter-city transport network in Southeast Asia

Liang Dai (UGent) , Ben Derudder (UGent) and Xingjian Liu
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Abstract
This paper examines the driving forces of urban network formation through the simulation of inter-city transportation networks in Southeast Asia. We present a generative network model (GNM) considering geographical and topological effects, thus combining factors commonly analysed through traditional spatial simulation models (e.g., gravity models) and topological simulation models (e.g., actor-oriented stochastic models)in a single framework. In our GNM, it is assumed that the probability of connections between cities emerges from competing forces. Stimulating factors are a measure of city size (i.e., population) and a topological rule favouring the formation of connections between cities sharing nearest neighbours (i.e., transitive effects). The hampering factors are physical distance between two cities as well as institutional distance (i.e., border effects). We discuss the model in the context of on-going engagements between urban-geographical research and the network science literature, and validate the credence of the model against empirical data on the transport networks connecting 51 major cities in Southeast Asia. Our results show that (1) the generated networks approximate the observed ones in terms of average path length, clustering, modularity, efficiency and quadratic assignment procedure (QAP) correlation between the observed composite network and the generated one, and that (2) GNM performs best when topographical and topological factors are considered simultaneously. Each factor contributes differently to network formation, with transitive effects playing the most important role.
Keywords
transport network, generative network model, transitivity, Southeast Asia

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MLA
Dai, Liang, Ben Derudder, and Xingjian Liu. “Generative Network Models for Simulating Urban Networks, the Case of Inter-city Transport Network in Southeast Asia.” Ed. Christine Kosmopoulos. Cybergeo : European Journal of Geography (2016): n. pag. Print.
APA
Dai, L., Derudder, B., & Liu, X. (2016). Generative network models for simulating urban networks, the case of inter-city transport network in Southeast Asia. (C. Kosmopoulos, Ed.)Cybergeo : European Journal of Geography.
Chicago author-date
Dai, Liang, Ben Derudder, and Xingjian Liu. 2016. “Generative Network Models for Simulating Urban Networks, the Case of Inter-city Transport Network in Southeast Asia.” Ed. Christine Kosmopoulos. Cybergeo : European Journal of Geography.
Chicago author-date (all authors)
Dai, Liang, Ben Derudder, and Xingjian Liu. 2016. “Generative Network Models for Simulating Urban Networks, the Case of Inter-city Transport Network in Southeast Asia.” Ed. Christine Kosmopoulos. Cybergeo : European Journal of Geography.
Vancouver
1.
Dai L, Derudder B, Liu X. Generative network models for simulating urban networks, the case of inter-city transport network in Southeast Asia. Kosmopoulos C, editor. Cybergeo : European Journal of Geography. 2016;
IEEE
[1]
L. Dai, B. Derudder, and X. Liu, “Generative network models for simulating urban networks, the case of inter-city transport network in Southeast Asia,” Cybergeo : European Journal of Geography, 2016.
@article{8047079,
  abstract     = {This paper examines the driving forces of urban network formation through the simulation of inter-city transportation networks in Southeast Asia. We present a generative network model (GNM) considering geographical and topological effects, thus combining factors commonly analysed through traditional spatial simulation models (e.g., gravity models) and topological simulation models (e.g., actor-oriented stochastic models)in a single framework. In our GNM, it is assumed that the probability of connections between cities emerges from competing forces. Stimulating factors are a measure of city size (i.e., population) and a topological rule favouring the formation of connections between cities sharing nearest neighbours (i.e., transitive effects). The hampering factors are physical distance between two cities as well as institutional distance (i.e., border effects). We discuss the model in the context of on-going engagements between urban-geographical research and the network science literature, and validate the credence of the model against empirical data on the transport networks connecting 51 major cities in Southeast Asia. Our results show that (1) the generated networks approximate the observed ones in terms of average path length, clustering, modularity, efficiency and quadratic assignment procedure (QAP) correlation between the observed composite network and the generated one, and that (2) GNM performs best when topographical and topological factors are considered simultaneously. Each factor contributes differently to network formation, with transitive effects playing the most important role.},
  articleno    = {786},
  author       = {Dai, Liang and Derudder, Ben and Liu, Xingjian},
  editor       = {Kosmopoulos, Christine},
  issn         = {1278-3366},
  journal      = {Cybergeo : European Journal of Geography},
  keywords     = {transport network,generative network model,transitivity,Southeast Asia},
  language     = {eng},
  title        = {Generative network models for simulating urban networks, the case of inter-city transport network in Southeast Asia},
  url          = {http://dx.doi.org/10.4000/cybergeo.27734},
  year         = {2016},
}

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