, Volume 8, Issue 2, pp 157–171 | Cite as

A Structural Approach to the Model Generalization of an Urban Street Network*

  • B. Jiang
  • C. Claramunt


This paper proposes a novel generalization model for selecting characteristic streets in an urban street network. This model retains the central structure of a street network. It relies on a structural representation of a street network using graph principles where vertices represent named streets and links represent street intersections. Based on this representation, so-called connectivity graph, centrality measures are introduced to qualify the status of each individual vertex within the graph. We show that these measures can be used for characterizing the structural properties of an urban street network, and for the selection of important streets. The proposed approach is validated by a case study applied to a middle-sized Swedish city.

model generalization structural analysis space syntax graph modeling urban modeling 


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  1. 1.
    AGENT. Constraint Analysis. ESPRIT report, Department of Geography, University of Zurich, 1998.Google Scholar
  2. 2.
    V. Batagelj and A. Mrvar. Networks/Pajek: Program for Large Networks Analysis, available at, 1997.Google Scholar
  3. 3.
    M. Batty, R. Conroy, B. Hillier, B. Jiang, J. Desyllas, C. Mottram, A. Penn, A. Smith, and A. Turner. The Virtual Tate, CASA working paper available at, 1998.Google Scholar
  4. 4.
    F. Buckley and F. Harary. Distance in Graphs. Addison-Wesley Publishing Company: Reading, MA, 1990.Google Scholar
  5. 5.
    B.P. Buttenfield and R.B. McMaster. Map Generalisation: Making Rules for Knowledge Representation. Longman Scientific & Technical, 1991.Google Scholar
  6. 6.
    D. Douglas and T. Peucker. “Algorithms for the reduction of the number of points required to represent a digital line or its Caricature,” The Canadian Cartographer, Vol. 10:112-122, 1973.Google Scholar
  7. 7.
    L.C. Freeman. “Centrality in social networks: Conceptual clarification,” Social Networks, Vol. 1:215-239, 1979.Google Scholar
  8. 8.
    J. Gross and J. Yellen. Graph Theory and its Application. CRC Press: London, 1999.Google Scholar
  9. 9.
    B. Hillier. Space is the Machine: A Configurational Theory of Architecture. Cambridge University Press: Cambridge, UK, 1996.Google Scholar
  10. 10.
    B. Hillier and J. Hanson. The Social Logic of Space. Cambridge University Press: Cambridge, 1984.Google Scholar
  11. 11.
    B. Hillier (Ed.). Proceedings, First International Symposium on Space Syntax. University College London: London, 16–18 April, 1997.Google Scholar
  12. 12.
    F. Holanda (Ed.). Proceedings, Second International Symposium on Space Syntax. Universidade de Brasilia: Brasilia, 29 March–2 April, 1999.Google Scholar
  13. 13.
    B. Jiang and C. Claramunt. “Integration of space syntax into GIS: New perspectives for urban morphology,” Transactions in GIS, Vol. 6(3):295-309, 2002.Google Scholar
  14. 14.
    B. Jiang and C. Claramunt. “Topological analysis of urban street networks,” Environment and Planning B: Planning and Design, Vol. 31:151-162, 2004.Google Scholar
  15. 15.
    M.V. Kreveld and J. Peschier. On the Automated Generalization of Road Network Maps, GeoComputation'98, available at, 1998.Google Scholar
  16. 16.
    W.A. Mackaness and M.K. Beard. “Use of graph theory to support map generalisation,” Cartography and Geographic Information Systems, Vol. 20:210-221, 1993.Google Scholar
  17. 17.
    W.A. Mackaness. “Analysis of urban road networks to support cartographic generalization,” Cartography and Geographic Information Systems, Vol. 22:306-316, 1995.Google Scholar
  18. 18.
    W.A. Mackaness and G.A. Mackechnie, “Automating the detection and simplification of junctions in road networks,” GeoInformatica, Vol. 3(2):185-200, 1999.Google Scholar
  19. 19.
    J.C. Muller, J.P. Lagrange, and R. Weibel. (Eds.). GIS and Generalization: Methodology and Practice. Taylor and Francis: London, 1995.Google Scholar
  20. 20.
    A. Penn. Intelligent Analysis of Urban Space Patterns: Graphical Interface to Precedent Databases for Urban Design, Auto Carto 11 Proceedings, ACSM-ASPRS, Minneapolis, pp. 53-62.Google Scholar
  21. 21.
    J. Peponis, J. Wineman, and S. Bafna (Eds.). Proceedings, Third International Symposium on Space Syntax. Georgia Institute of Technology Atlanta, May 7–11, 2001.Google Scholar
  22. 22.
    D. Richardson. Generalization of Road Networks, available at, 2000.Google Scholar
  23. 23.
    R.C. Thomson and D.E. Richardson. “A graph theory approach to road network generalisation,” in Proceeding of the 17th International Cartographic Conference, 1871-1880, 1995.Google Scholar
  24. 24.
    D.J. Watts and S.H. Strogatz. “Collective dynamics of ‘Small-World’ networks,” Nature, Vol. 393:440-442, 1998.Google Scholar
  25. 25.
    R. Weibel. “Three essential building blocks for automated generalisation,” in J.C. Muller, J.P. Lagrange, and R. Weibel (Eds.), GIS and Generalization: Methodology and Practice, Taylor and Francis: London, 56-69, 1995.Google Scholar

Copyright information

© Kluwer Academic Publishers 2004

Authors and Affiliations

  • B. Jiang
    • 1
  • C. Claramunt
    • 2
  1. 1.Division of Geomatics, Department of Technology and Built EnvironmentUniversity of GävleGävleSweden
  2. 2.[Brest NavalFrance

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