IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v387y2008i8p2120-2132.html
   My bibliography  Save this article

On the metric, topological and functional structures of urban networks

Author

Listed:
  • Wagner, Roy

Abstract

Axial Graphs are networks whose nodes are linear axes in urban space, and whose edges represent intersections of such axes. These graphs are used in urban planning and urban morphology studies. In this paper we analyse distance distributions between nodes in axial graphs, and show that these distributions are well approximated by rescaled-Poisson distributions. We then demonstrate a correlation between the parameters governing the distance distribution and the degree of the polynomial distribution of metric lengths of linear axes in cities. This correlation provides ‘topological’ support to the metrically based categorisation of cities proposed in [R. Carvalho, A. Penn, Scaling and universality in the micro-structure of urban space, Physica A 332 (2004) 539–547]. Finally, we attempt to explain this topologico-metric categorisation in functional terms. To this end, we introduce a notion of attraction cores defined in terms of aggregations of random walk agents. We demonstrate that the number of attraction cores in cities correlates with the parameters governing their distance and line length distributions. The intersection of all the three points of view (topological, metric and agent based) yields a descriptive model of the structure of urban networks.

Suggested Citation

  • Wagner, Roy, 2008. "On the metric, topological and functional structures of urban networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(8), pages 2120-2132.
    • Handle: RePEc:eee:phsmap:v:387:y:2008:i:8:p:2120-2132
    DOI: 10.1016/j.physa.2007.11.019
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437107012150
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000
    File URL: https://libkey.io/10.1016/j.physa.2007.11.019?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Jiang, Bin, 2007. "A topological pattern of urban street networks: Universality and peculiarity," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 384(2), pages 647-655.
    2. B Hillier & A Penn & J Hanson & T Grajewski & J Xu, 1993. "Natural Movement: Or, Configuration and Attraction in Urban Pedestrian Movement," Environment and Planning B, , vol. 20(1), pages 29-66, February.
    3. Porta, Sergio & Crucitti, Paolo & Latora, Vito, 2006. "The network analysis of urban streets: A dual approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 369(2), pages 853-866.
    4. J. Buhl & J. Gautrais & N. Reeves & R. V. Solé & S. Valverde & P. Kuntz & G. Theraulaz, 2006. "Topological patterns in street networks of self-organized urban settlements," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 49(4), pages 513-522, February.
    5. Carvalho, Rui & Penn, Alan, 2004. "Scaling and universality in the micro-structure of urban space," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 332(C), pages 539-547.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Jiang, Bin, 2007. "A topological pattern of urban street networks: Universality and peculiarity," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 384(2), pages 647-655.
    2. Boeing, Geoff, 2017. "OSMnx: New Methods for Acquiring, Constructing, Analyzing, and Visualizing Complex Street Networks," SocArXiv q86sd, Center for Open Science.
    3. Sergio Porta & Vito Latora & Fahui Wang & Salvador Rueda & Emanuele Strano & Salvatore Scellato & Alessio Cardillo & Eugenio Belli & Francisco CÃ rdenas & Berta Cormenzana & Laura Latora, 2012. "Street Centrality and the Location of Economic Activities in Barcelona," Urban Studies, Urban Studies Journal Limited, vol. 49(7), pages 1471-1488, May.
    4. Asya Natapov & Daniel Czamanski & Dafna Fisher-Gewirtzman, 2018. "A Network Approach to Link Visibility and Urban Activity Location," Networks and Spatial Economics, Springer, vol. 18(3), pages 555-575, September.
    5. Zhao, Pengxiang & Jia, Tao & Qin, Kun & Shan, Jie & Jiao, Chenjing, 2015. "Statistical analysis on the evolution of OpenStreetMap road networks in Beijing," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 420(C), pages 59-72.
    6. Shiguang Wang & Dexin Yu & Mei-Po Kwan & Huxing Zhou & Yongxing Li & Hongzhi Miao, 2019. "The Evolution and Growth Patterns of the Road Network in a Medium-Sized Developing City: A Historical Investigation of Changchun, China, from 1912 to 2017," Sustainability, MDPI, vol. 11(19), pages 1-25, September.
    7. Boeing, Geoff, 2019. "Street Network Models and Measures for Every U.S. City, County, Urbanized Area, Census Tract, and Zillow-Defined Neighborhood," SocArXiv 7fxjz, Center for Open Science.
    8. Wang, Shiguang & Yu, Dexin & Lin, Ciyun & Shang, Qiang & Lin, Yu, 2018. "How to connect with each other between roads? An empirical study of urban road connection properties," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 512(C), pages 775-787.
    9. Batac, Rene C. & Cirunay, Michelle T., 2022. "Shortest paths along urban road network peripheries," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 597(C).
    10. Xiaokun Su & Chenrouyu Zheng & Yefei Yang & Yafei Yang & Wen Zhao & Yue Yu, 2022. "Spatial Structure and Development Patterns of Urban Traffic Flow Network in Less Developed Areas: A Sustainable Development Perspective," Sustainability, MDPI, vol. 14(13), pages 1-18, July.
    11. Ermal Shpuza, 2017. "Relative size measures of urban form based on allometric subtraction," Environment and Planning B, , vol. 44(1), pages 141-159, January.
    12. Tsiotas, Dimitrios, 2021. "Drawing indicators of economic performance from network topology: The case of the interregional road transportation in Greece," Research in Transportation Economics, Elsevier, vol. 90(C).
    13. Geoff Boeing, 2020. "A multi-scale analysis of 27,000 urban street networks: Every US city, town, urbanized area, and Zillow neighborhood," Environment and Planning B, , vol. 47(4), pages 590-608, May.
    14. Pelin Şahin Körmeçli, 2024. "Accessibility of Urban Tourism in Historical Areas: Analysis of UNESCO World Heritage Sites in Safranbolu," Sustainability, MDPI, vol. 16(6), pages 1-17, March.
    15. Marc Barthelemy, 2017. "From paths to blocks: New measures for street patterns," Environment and Planning B, , vol. 44(2), pages 256-271, March.
    16. Zhao, Shuangming & Zhao, Pengxiang & Cui, Yunfan, 2017. "A network centrality measure framework for analyzing urban traffic flow: A case study of Wuhan, China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 478(C), pages 143-157.
    17. Boeing, Geoff, 2017. "Methods and Measures for Analyzing Complex Street Networks and Urban Form," SocArXiv 93h82, Center for Open Science.
    18. Lowry, Michael, 2014. "Spatial interpolation of traffic counts based on origin–destination centrality," Journal of Transport Geography, Elsevier, vol. 36(C), pages 98-105.
    19. Lee, Byoung-Hwa & Jung, Woo-Sung, 2018. "Analysis on the urban street network of Korea: Connections between topology and meta-information," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 497(C), pages 15-25.
    20. Hiroyuki Usui, 2018. "Estimation of geometric route distance from its topological distance: application to narrow road networks in Tokyo," Journal of Geographical Systems, Springer, vol. 20(4), pages 387-412, October.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:phsmap:v:387:y:2008:i:8:p:2120-2132. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.