GeoTemCo: Comparative Visualization of Geospatial-Temporal Data with Clutter Removal Based on Dynamic Delaunay Triangulations

  • Stefan Jänicke
  • Christian Heine
  • Gerik Scheuermann
Part of the Communications in Computer and Information Science book series (CCIS, volume 359)


The amount of online data annotated with geospatial and temporal metadata has grown rapidly in the recent years. Providers like Flickr and Twitter are popular, but hard to browse. Many systems exist that, in multiple linked views, show the data under geospatial, temporal, and topical aspects. We unify and extend these systems in a Web application to support comparison of multiple, potentially large result sets of textual queries with extended interaction capabilities. We present a novel fast algorithm using a dynamic Delaunay triangulation for merging glyphs in the map view into so-called circle groups to avoid visual clutter, which is critical for the comparative setting. We evaluate our design by qualitative comparison with existing systems.


Visual data exploration Geovisualization Comparative visualization Dynamic Delaunay triangulation 


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  1. 1.
    Jänicke, S., Heine, C., Stockmann, R., Scheuermann, G.: Comparative visualization of geospatial-temporal data. In: GRAPP/IVAPP, pp. 613–625 (2012)Google Scholar
  2. 2.
    Dent, B.D.: Cartography: Thematic Map Design, 5th edn. McGraw-Hill (1999)Google Scholar
  3. 3.
    Slocum, T.A., McMaster, R.B., Kessler, F.C., Howard, H.H.: Thematic Cartography and Geovisualization, 3rd international edn. Prentice Hall Series in Geographic Information Science. Prentice-Hall (2009)Google Scholar
  4. 4.
    Andrienko, G., Andrienko, N.: Visual Data Exploration: Tools, Principles, and Problems. Classics from IJGIS: Twenty Years of the International Journal of Geographical Information Science and Systems, 475–479 (2006)Google Scholar
  5. 5.
    Andrienko, N., Andrienko, G.: Exploratory Analysis of Spatial and Temporal Data: A Systematic Approach. Springer (2005)Google Scholar
  6. 6.
    Dörk, M., Carpendale, S., Collins, C., Williamson, C.: VisGets: Coordinated Visualizations for Web-based Information Exploration and Discovery. IEEE Transactions on Visualization and Computer Graphics 14, 1205–1212 (2008)CrossRefGoogle Scholar
  7. 7.
    Roth, R.E., Ross, K.S., Finch, B.G., Luo, W., MacEachren, A.M.: A User-Centered Approach for Designing and Developing Spatiotemporal Crime Analysis Tools. In: Purves, R., Weibel, R. (eds.) Proceedings of GIScience (2010)Google Scholar
  8. 8.
    Cleveland, W.S., McGill, R.: Graphical Perception: Theory, Experimentation, and Application to the Development of Graphical Methods. Journal of the American Statistical Association 79, 531–554 (1984)MathSciNetCrossRefGoogle Scholar
  9. 9.
    Rogers, S.: The Guardian - Wikileaks Iraq war logs: every death mapped (2010), (retrieved July 10, 2011)
  10. 10.
    Schuyler: Web map API roundup: Mapping hacks (2006),
  11. 11.
    Wilkinson, L.: The Grammar of Graphics (Statistics and Computing). Springer-Verlag New York, Inc., Secaucus (2005)Google Scholar
  12. 12.
    Carr, D.B., Littlefield, R.J., Nichloson, W.L.: Scatterplot matrix techniques for large n. In: Proceedings of the Seventeenth Symposium on the Interface of Computer Sciences and Statistics on Computer Science and Statistics, pp. 297–306. Elsevier North-Holland, Inc., New York (1986)Google Scholar
  13. 13.
    Cleveland, W.S., Mcgill, R.: The Many Faces of a Scatterplot. Journal of the American Statistical Association 79, 807–822 (1984)MathSciNetCrossRefGoogle Scholar
  14. 14.
    Novotny, M.: Visually effective information visualization of large data. In: 8th Central European Seminar on Computer Graphics (CESCG 2004), pp. 41–48. CRC Press (2004)Google Scholar
  15. 15.
    Lloyd, S.P.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28, 129–137 (1982)MathSciNetzbMATHCrossRefGoogle Scholar
  16. 16.
    Bertin, J.: Semiology of graphics. University of Wisconsin Press (1983)Google Scholar
  17. 17.
    Hardisty, F., Klippel, A.: Analysing Spatio-Temporal Autocorrelation with LISTA-Viz. Int. J. Geogr. Inf. Sci. 24, 1515–1526 (2010)CrossRefGoogle Scholar
  18. 18.
    Ware, C.: Information Visualization: Perception for Design, 3rd edn. Morgan Kaufmann (2004)Google Scholar
  19. 19.
    Tsipidis, S., Koussoulakou, A., Kotsakis, K.: Geovisualization and Archaeology: supporting Excavation Site Research. In: Ruas, A. (ed.) Advances in Cartography and GIScience. Volume 2. Lecture Notes in Geoinformation and Cartography, vol. 6, pp. 85–107. Springer, Heidelberg (2011)CrossRefGoogle Scholar
  20. 20.
    Barker, E., Bouzarovski, S., Pelling, C., Isaksen, L.: Mapping an ancient historian in a digital age: the Herodotus Encoded Space-Text-Image Archive (HESTIA). Leeds International Classical Studies 9 (2010)Google Scholar
  21. 21.
    Harris, R.L.: Information Graphics: A Comprehensive Illustrated Reference. Oxford University Press (1999)Google Scholar
  22. 22.
    Kao, T., Mount, D.M., Saalfeld, A.: Dynamic maintenance of delaunay triangulations. Technical report, University of Maryland at College Park, College Park, MD, USA (1991)Google Scholar
  23. 23.
    Barker, E., Isaksen, L., Byrne, K., Kansa, E.: GAP: a neogeo approach to classical resources. In: European Conference on Complex Systems 2010 (2011)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Stefan Jänicke
    • 1
  • Christian Heine
    • 2
  • Gerik Scheuermann
    • 1
  1. 1.Image and Signal Processing Group, Institute for Computer ScienceUniversity of LeipzigGermany
  2. 2.ETH ZürichSwitzerland

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