Automatic Extraction of Hierarchical Urban Networks: A Micro-Spatial Approach

  • Rui Carvalho
  • Michael Batty
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3038)


We present an image processing technique for the identification of ‘axial lines’ [1] from ridges in isovist fields first proposed by Rana [2,3]. These ridges are formed from the maximum diametric lengths of the individual isovists, sometimes called viewsheds, that make up the isovist fields [4]. We discuss current strengths and weaknesses of the method, and show how it can be implemented easily and effectively.


Univer Alan Isovist 


  1. 1.
    Hillier, B., Hanson, J.: The Social Logic of Space. Cambridge University Press, Cambridge (1984)CrossRefGoogle Scholar
  2. 2.
    Benedikt, M.: To take hold of space: isovists and isovist fields. Environ. Plan. B 6, 47–65 (1979)CrossRefGoogle Scholar
  3. 3.
    Rana, S.: Isovist analyst extension for arcview 3.2 (2002)Google Scholar
  4. 4.
    Batty, M., Rana, S.: The automatic definition and generation of axial lines and axial maps. Environ. Plan. B 31 (2004) (forthcoming)Google Scholar
  5. 5.
    Hillier, B., Penn, A., Hanson, J., T, T.G., Xu, J.: Natural movement: or, configuration and attraction in urban pedestrian movement. Environ. Plan. B 20, 29–66 (1993)CrossRefGoogle Scholar
  6. 6.
    Peponis, J., Ross, C., Rashid, M.: The structure of urban space, movement and co-presence: The case of atlanta. Geoforum 28, 341–358 (1997)CrossRefGoogle Scholar
  7. 7.
    Peponis, J., Wineman, J., Bafna, S., Rashid, M., Kim, S.: On the generation of linear representations of spatial configuration. Environ. Plan. B 25, 559–576 (1998)CrossRefGoogle Scholar
  8. 8.
    Ratti, C.: Urban analysis for environmental prediction. Phd thesis, University of Cambridge (2001)Google Scholar
  9. 9.
    Albert, R., Barabási, A.L.: Statistical mechanics of complex networks. Rev. Mod. Phys. 74, 47–97 (2002)CrossRefMATHGoogle Scholar
  10. 10.
    Newman, M.E.J.: The structure and function of complex networks. SIAM Rev. 45, 167–256 (2003)MATHCrossRefMathSciNetGoogle Scholar
  11. 11.
    Batty, M., Longley, P.: Fractal Cities. Academic Press, San Diego (1994)MATHGoogle Scholar
  12. 12.
    Carvalho, R., Penn, A.: Scaling and universality in the micro-structure of urban space. Physica A 332, 539–547 (2004)CrossRefGoogle Scholar
  13. 13.
    Frankhauser, P.: La Fractalité des Structures Urbaines. Anthropos, Paris (1994)Google Scholar
  14. 14.
    Makse, H.A., Havlin, S., Stanley, H.E.: Modelling urban growth patterns. Nature 377, 608–612 (1995)CrossRefGoogle Scholar
  15. 15.
    Makse Jr., H.A., A., J.S., Batty, M., Havlin, S., Stanley, H.E.: Modeling urban growth patterns with correlated percolation. Phys. Rev. E 58, 7054–7062 (1998)CrossRefGoogle Scholar
  16. 16.
    Latora, V., Marchiori, M.: Is the boston subway a small-world network? Physica A 314, 109–113 (2002)MATHCrossRefGoogle Scholar
  17. 17.
    Chowell, G., Hyman, J.M., Eubank, S., Castillo-Chavez, C.: Scaling laws for the movement of people between locations in a large city. Phys. Rev. E 68, 66–102 (2003)CrossRefGoogle Scholar
  18. 18.
    Blum, H.: Biological shape and visual science (part 1). J. Theor. Biol. 38, 205–287 (1973)CrossRefGoogle Scholar
  19. 19.
    Blum, H., Nagel, R.N.: Shape description using weighted symmetric features. Pattern Recogn. 10, 167–180 (1978)MATHCrossRefGoogle Scholar
  20. 20.
    Illingworth, J., Kittler, J.: A survey of the hough transform. Computer Vision, Graphics, and Image Processing 44, 87–116 (1988)CrossRefGoogle Scholar
  21. 21.
    Batty, M.: Exploring isovist fields: space and shape in architectural and urban morphology. Environ. Plan. B 28, 123–150 (2001)CrossRefGoogle Scholar
  22. 22.
    Turner, A., Doxa, M., O’Sullivan, D., Penn, A.: From isovists to visibility graphs: a methodology for the analysis of architectural space. Environ. Plan. B 28, 103–121 (2001)CrossRefGoogle Scholar
  23. 23.
    Burrough, P.A., McDonnell, R.A.: Principles of Geographical Information Systems. Spatial Information Systems and Geostatistics. Oxford University Press, Oxford (1998)Google Scholar
  24. 24.
    Niblack, C., Gibbons, P., Capson, D.: Generating skeletons and ceterlines from the distance transform. CVGIP: Graphical Models and Image Processing 54, 420–437 (1992)CrossRefGoogle Scholar
  25. 25.
    Gonzalez, R.C., Woods, R.E.: Digital Image Processing. Addison-Wesley, Reading (1992)Google Scholar
  26. 26.
    Mills, K., Fox, G., Heimbach, R.: Implementing an intervisibility analysis model on a parallel computing system. Computers & Geosciences 18, 1047–1054 (1992)CrossRefGoogle Scholar
  27. 27.
    Kamat-Sadekar, V., Ganesan, S.: Complete description of multiple line segments using the hough transform. Image and Vision Computing 16, 597–613 (1998)CrossRefGoogle Scholar
  28. 28.
    Pomerleau, D., Jochem, T.: Rapidly adapting machine vision for automated vehicle steering. IEEE Expert 11, 19–27 (1996)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Rui Carvalho
    • 1
  • Michael Batty
    • 2
  1. 1.The Bartlett School of Graduate Studies 
  2. 2.Centre for Advanced Spatial AnalysisUniversity College LondonLondonUK

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