Abstract
Due to the rising progress of sustainable urban infrastructures, modeling realistic street networks is a fundamental challenge. This study contributes to this modeling direction, by suggesting the utilization of planar proximity graphs, and specifically the \(\beta \)-skeleton graphs. Their goodness of fit on producing real-like urban street networks is verified by comparison to real data. In particular, the basic topological and geometrical properties derived from synthetic \(\beta \)-skeleton planar graphs are compared to the properties of five urban street network datasets, all represented using the Primal approach. A good agreement with empirical patterns is found and a possible explanation is discussed.
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Notes
- 1.
In the samples where the entire set of these properties is not available, only the available properties are kept.
- 2.
It should be noted that the normalized cost is not a measure of construction cost, but only an index of how long the wiring of the graph is, compared to the respective extreme planar graphs (MST and DT).
References
Barthélemy, M., Flammini, A.: Modeling urban street patterns. Phys. Rev. Lett. 100, 138702 (2008)
Kirkpatrick, D.G., Radke, J.D.: A framework for computational morphology. Comput. Geom. 217–248 (1985)
Adamatzky, A.: On growing connected \(\beta \)-skeletons. Comput. Geom. 46, 805–816 (2013)
Hamaina, R., Leduc, T., Moreau, G.: A structural analysis of the streets network to urban fabric characterization. In: 25th International Cartographic Conference (ICC2011), pp. 1–8. Paris, France (2011)
Cardillo, A., Scellato, S., Latora, V., Porta, S.: Structural properties of planar graphs of urban street patterns. Phys. Rev. E. 73, 066107 (2006)
Peponis, J., Allen, D., Haynie, D., Scoppa, M., Zhang, Z.: Measuring the configuration of street networks. In: 6th International Space Syntax Symposium, pp. 1–16. Istanbul, Turkey (2007)
Strano, E., Viana, M., Costa, L. da F., Cardillo, A., Porta, S., Latora, V.: Urban street networks, a comparative analysis of ten European cities. Env. Plann. B: Plann. Des. 40, 1071–1086 (2013)
Chan, S.H., Donner, R.V., Lämmer, S.: Urban road networks-spatial networks with universal geometric features? Eur. Phys. J. B. 84, 563–577 (2011)
Maniadakis, D., Varoutas, D.: Structural properties of urban street networks of varying population density. In: 10th European Conference on Complex Systems (ECCS’13), pp. 1–6. Barcelona, Spain (2013)
Porta, S., Crucitti, P., Latora, V.: The network analysis of urban streets: a primal approach. Environ. Planning B: Planning Des. 33, 705–725 (2006)
Osaragi, T., Hiraga, Y.: Street network created by proximity graphs: its topological structure and travel efficiency. In: 17th Conference of the Association of Geographic Information Laboratories for Europe on Geographic Information Science (AGILE2014), pp. 1–6. Castellón, Spain (2014)
Meyer, J.R., Gómez-Ibáñez, J.A.: Autos, Transit, and Cities: A Twentieth Century Fund Report. Harvard University Press, Cambridge (1981)
Manville, M., Shoup, D.: People, parking and cities. J. Urban Planning Dev. 131, 233–245 (2005)
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Maniadakis, D., Varoutas, D. (2016). Fitting Planar Proximity Graphs on Real Street Networks. In: Battiston, S., De Pellegrini, F., Caldarelli, G., Merelli, E. (eds) Proceedings of ECCS 2014. Springer Proceedings in Complexity. Springer, Cham. https://doi.org/10.1007/978-3-319-29228-1_2
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