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International Joint Conference on Computer Vision, Imaging and Computer Graphics

VISIGRAPP 2016: Computer Vision, Imaging and Computer Graphics Theory and Applications pp 287–309Cite as

Analysis and Comparison of Feature-Based Patterns in Urban Street Networks

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Part of the book series: Communications in Computer and Information Science ((CCIS,volume 693))

Abstract

Analysis of street networks is a challenging task, needed in urban planning applications such as urban design or transportation network analysis. Typically, different network features of interest are used for within- and between comparisons across street networks. We introduce StreetExplorer, a visual-interactive system for analysis and comparison of global and local patterns in urban street networks. The system uses appropriate similarity functions to search for patterns, taking into account topological and geometric features of a street network. We enhance the visual comparison of street network patterns by a suitable color-mapping and boosting scheme to visualize the similarity between street network portions and the distribution of network features. Together with experts from the urban morphology domain, we apply our approach to analyze and compare two urban street networks, identifying patterns of historic development and modern planning approaches, demonstrating the usefulness of StreetExplorer.

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Notes

  1. 1.

    A demonstration of StreetExplorer can be found at: https://vimeo.com/149003539.

References

  1. Andrienko, G., Andrienko, N., Bak, P., Keim, D., Wrobel, S.: Visual Analytics of Movement. Springer Publishing Company, Heidelberg (2013)

    Book  Google Scholar 

  2. Andrienko, G., Andrienko, N., Bremm, S., Schreck, T., von Landesberger, T., Bak, P., Keim, D.: Space-in-time and time-in-space self-organizing maps for exploring spatiotemporal patterns. Wiley-Blackwell Comput. Graph. Forum 29(3), 913–922 (2010)

    Article  Google Scholar 

  3. Bak, P., Omer, I., Schreck, T.: Visual analytics of urban environments using high-resolution geographic data. In: Painho, M., Santos, M., Pundt, H. (eds) Geospatial Thinking. LNGC, pp. 25–42. Springer, Heidelberg (2010). doi:10.1007/978-3-642-12326-9_2

  4. Barten, P.G.: Contrast Sensitivity of the Human Eye and its Effects on Image Quality, vol. 72. SPIE Press, Bellingham (1999)

    Google Scholar 

  5. Brehmer, M., Munzner, T.: A multi-level typology of abstract visualization tasks. IEEE Trans. Vis. Comput. Graph. 19(12), 2376–2385 (2013)

    Article  Google Scholar 

  6. Camgöz, N., Yener, C., Güvenç, D.: Effects of hue, saturation, and brightness: part 2: attention. Color Res. Appl. 29(1), 20–28 (2004)

    Article  Google Scholar 

  7. Chu, D., Sheets, D., Zhao, Y., Wu, Y., Yang, J., Zheng, M., Chen, G.: Visualizing hidden themes of taxi movement with semantic transformation. In: 2014 IEEE Pacific Visualization Symposium (PacificVis), pp. 137–144, March 2014

    Google Scholar 

  8. Dunne, C., Shneiderman, B.: Motif simplification: improving network visualization readability with fan, connector, and clique glyphs. In: Proceedings of SIGCHI Conference on Human Factors in Computing Systems, pp. 3247–3256. ACM (2013)

    Google Scholar 

  9. Fairchild, M.D., Johnson, G.M.: iCAM framework for image appearance, differences, and quality. J. Electron. Imaging 13(1), 126–138 (2004)

    Article  Google Scholar 

  10. Ferreira, N., Poco, J., Vo, H.T., Freire, J., Silva, C.T.: Visual exploration of big spatio-temporal urban data: a study of New York city taxi trips. IEEE Trans. Vis. Comput. Graph. 19(12), 2149–2158 (2013)

    Article  Google Scholar 

  11. Heinzle, F., Anders, K., Sester, M.: Graph based approaches for recognition of patterns and implicit information in road networks. In: Proceedings of 22nd International Cartographic Conference, A Coruna, Spain (2005)

    Google Scholar 

  12. Hillier, B.: A theory of the city as object: or, how spatial laws mediate the social construction of urban space. Urban Des. Int. 7(3), 153–179 (2002)

    Article  Google Scholar 

  13. Hillier, B.: Space is the Machine: A Configurational Theory of Architecture. Cambridge University Press, Cambridge (2007)

    Google Scholar 

  14. Itzhak, O., Zafrir-Reuven, O.: The development of street patterns in Israeli cities. J. Urban Reg. Anal. 7(2), 113–127 (2015)

    Google Scholar 

  15. Jiang, B.: A topological pattern of urban street networks: universality and peculiarity. Phys. A: Stat. Mech. Appl. 384(2), 647–655 (2007)

    Article  Google Scholar 

  16. Keim, D.: Designing pixel-oriented visualization techniques: theory and applications. IEEE Trans. Vis. Comput. Graph. 6(1), 59–78 (2000)

    Article  Google Scholar 

  17. Kindlmann, G., Reinhard, E., Creem, S.: Face-based luminance matching for perceptual colormap generation. In: Proceedings of the Conference on Visualization, pp. 299–306. IEEE Computer Society (2002)

    Google Scholar 

  18. Kropf, K.: Aspects of urban form. Urban Morphol. 13(2), 105–120 (2009)

    Google Scholar 

  19. Liu, Y., Zhang, D., Lu, G., Ma, W.-Y.: A survey of content-based image retrieval with high-level semantics. Pattern Recogn. 40(1), 262–282 (2007)

    Article  MATH  Google Scholar 

  20. Luan, X., Yang, B.: Generating strokes of road networks based on pattern recognition. In: 13th Workshop of the ICA Commission on Generalisation and Multiple Representation, Zurich, Switzerland, vol. 12, p. 13 (2010)

    Google Scholar 

  21. Marshall, S.: Streets and Patterns. Spon Press, London and New York (2004)

    Google Scholar 

  22. Marshall, S.: Route structure analysis: a system of representation, calculation and graphical presentation. Working Paper (2008)

    Google Scholar 

  23. Mittelstädt, S., Jäckle, D., Stoffel, F., Keim, D.A.: ColorCAT: guided design of colormaps for combined analysis tasks. In: Proceedings of the Eurographics Conference on Visualization (EuroVis 2015: Short Papers), pp. 115–119 (2015)

    Google Scholar 

  24. Mittelstädt, S., Stoffel, A., Keim, D.A.: Methods for compensating contrast effects in information visualization. Comput. Graph. Forum 33(3), 231–240 (2014)

    Article  Google Scholar 

  25. Oelke, D., Janetzko, H., Simon, S., Neuhaus, K., Keim, D.A.: Visual boosting in pixel-based visualizations. In: Computer Graphics Forum, vol. 30, pp. 871–880. Wiley Online Library (2011)

    Google Scholar 

  26. Omer, I., Bak, P., Schreck, T.: Using space-time visual analytic methods for exploring the dynamics of ethnic groups’ residential patterns. Taylor & Francis Int. J. Geograph. Inf. Sci. 24(10), 1481–1496 (2010). Peer-reviewed article

    Google Scholar 

  27. Omer, I., Zafrir-Reuven, O.: Street patterns and spatial integration of Israeli cities. J. Space Syntax 1(2), 295 (2010)

    Google Scholar 

  28. Pettit, C., Widjaja, I., Russo, P., Sinnott, R., Stimson, R., Tomko, M.: Visualisation support for exploring urban space and place. In: XXII ISPRS Congress, Technical Commission IV, vol. 25 (2012)

    Google Scholar 

  29. Porta, S., Crucitti, P., Latora, V.: The network analysis of urban streets: a primal approach. Environ. Plan. B: Plan. Des. 33, 705–725 (2006)

    Article  MATH  Google Scholar 

  30. Schreck, T., Omer, I., Bak, P., Lerman, Y.: A visual analytics approach for assessing pedestrian friendliness of urban environments. In: Vandenbroucke, D., Bucher, B., Crompvoets, J. (eds.) Proceedings of AGILE International Conference on Geographic Information Science. LNGC, pp. 353–368. Springer, Heidelberg (2013). doi:10.1007/978-3-319-00615-4_20

  31. Shneiderman, B.: The eyes have it: a task by data type taxonomy for information visualizations. In: Proceedings IEEE Symposium on Visual Languages, pp. 336–343, September 1996

    Google Scholar 

  32. Tian, J., Ai, T., Jia, X.: Graph based recognition of grid pattern in street networks. In: Yeh, A., Shi, W., Leung Y., Zhou C. (eds.) Advances in Spatial Data Handling and GIS. LNGC, pp. 129–143. Springer, Heidelberg (2012). doi:10.1007/978-3-642-25926-5_10

  33. Turner, A.: A program to perform visibility graph analysis. In: Proceedings of the 3rd Space Syntax Symposium, Atlanta, University of Michigan, pp. 1–31 (2001)

    Google Scholar 

  34. Vaughan, L., Jones, C.E., Griffiths, S., Haklay, M.M.: The spatial signature of suburban town centres. J. Space Syntax 1(1), 77–91 (2010)

    Google Scholar 

  35. von Landesberger, T., Görner, M., Rehner, R., Schreck, T.: A system for interactive visual analysis of large graphs using motifs in graph editing and aggregation. In: VMV 2009, pp. 331–340 (2009)

    Google Scholar 

  36. von Landesberger, T., Kuijper, A., Schreck, T., Kohlhammer, J., van Wijk, J., Fekete, J.-D., Fellner, D.: Visual analysis of large graphs: state-of-the-art and future research challenges. Comput. Graph. Forum 30(6), 1719–1749 (2011)

    Article  Google Scholar 

  37. Wang, Z., Lu, M., Yuan, X., Zhang, J., Van De Wetering, H.: Visual traffic jam analysis based on trajectory data. IEEE Trans. Vis. Comput. Graph. 19(12), 2159–2168 (2013)

    Article  Google Scholar 

  38. Ware, C.: Color sequences for univariate maps: theory, experiments and principles. IEEE Comput. Graph. Appl. 8(5), 41–49 (1988)

    Article  Google Scholar 

  39. Wheeler, S.M.: The evolution of built landscapes in metropolitan regions. J. Plann. Educ. Res. 27(4), 400–416 (2008)

    Article  Google Scholar 

  40. Yan, X., Zhu, F., Yu, P.S., Han, J.: Feature-based similarity search in graph structures. ACM Trans. Database Syst. 31(4), 1418–1453 (2006)

    Article  Google Scholar 

  41. Yang, B., Luan, X., Zhang, Y.: A pattern-based approach for matching nodes in heterogeneous urban road networks. Trans. GIS 18(5), 718–739 (2014)

    Article  Google Scholar 

  42. Yang, T., Hillier, B.: The fuzzy boundary: the spatial definition of urban areas (2007)

    Google Scholar 

  43. Zhou, Q., Li, Z.: Experimental analysis of various types of road intersections for interchange detection. Trans. GIS 19(1), 19–41 (2015)

    Article  Google Scholar 

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Author information

Authors and Affiliations

  1. Graz University of Technology, Graz, Austria

    Lin Shao & Tobias Schreck

  2. University of Konstanz, Konstanz, Germany

    Sebastian Mittelstädt

  3. Department of Geography and Human Environment, Tel Aviv University, Tel Aviv, Israel

    Ran Goldblatt & Itzhak Omer

  4. IBM Haifa Research Lab, Haifa, Israel

    Peter Bak

Authors
  1. Lin Shao
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  2. Sebastian Mittelstädt
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  3. Ran Goldblatt
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  4. Itzhak Omer
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  5. Peter Bak
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  6. Tobias Schreck
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Corresponding author

Correspondence to Lin Shao .

Editor information

Editors and Affiliations

  1. Escola Superior de Tecnologia do IPS, Setúbal, Portugal

    José Braz

  2. MiraLab, University of Geneva, Carouge, Switzerland

    Nadia Magnenat-Thalmann

  3. LISA - ISTIA, University of Angers, Angers, France

    Paul Richard

  4. Department of Computer Science and Electrical Engineering, Jacobs University, Bremen, Germany

    Lars Linsen

  5. University of Groningen, Groningen, The Netherlands

    Alexandru Telea

  6. Università di Catania, Catania, Italy

    Sebastiano Battiato

  7. Research Innovation Center, Canon U.S.A. Inc., San Jose, California, USA

    Francisco Imai

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Shao, L., Mittelstädt, S., Goldblatt, R., Omer, I., Bak, P., Schreck, T. (2017). Analysis and Comparison of Feature-Based Patterns in Urban Street Networks. In: Braz, J., et al. Computer Vision, Imaging and Computer Graphics Theory and Applications. VISIGRAPP 2016. Communications in Computer and Information Science, vol 693. Springer, Cham. https://doi.org/10.1007/978-3-319-64870-5_14

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  • DOI: https://doi.org/10.1007/978-3-319-64870-5_14

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-64869-9

  • Online ISBN: 978-3-319-64870-5

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