Spatiotemporal Visualisation: A Survey and Outlook

  • Chen Zhong
  • Tao Wang
  • Wei Zeng
  • Stefan Müller Arisona
Part of the Communications in Computer and Information Science book series (CCIS, volume 242)

Abstract

Visualisation as a means of communication helps represent massive data sets, exchange knowledge and obtain better understanding of information. Spatiotemporal visualisation concerns changes of information in space and time. It has a natural advantage of revealing overall tendencies and movement patterns. Compared to traditional visual representations, it makes the notion of time accessible to non-expert users, and thus constitutes an important instrument in terms of decision-making that has been used in many application scenarios. As an interdisciplinary approach, substantial progress has been made in different domains, such as geographic information science, visualisation, or visual analytics, but there remains a lot of room for further advancements. In view of this, this paper presents a review of significant research in spatiotemporal visualisation, highlights a general workflow of data acquisition, information modelling and visualisation. Existing work from different domains are introduced, linked to the workflow, and possible integration strategies are given. Inspired by this summary, we also propose future work aiming at improving current spatiotemporal visualisation by integrating visualisation and interaction techniques more tightly.

Keywords

Spatiotemporal visualisation spatiotemporal modelling GIS 

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References

  1. Andrienko, G., Andrienko, N.: Dynamic time transformations for visualizing multiple trajectories in interactive space-time cube. In: International Cartographic Conference, ICC 2011 (2011)Google Scholar
  2. Andrienko, N., Andrienko, G., Gatalsky, P.: Exploratory spatio-temporal visualization: an analytical review. Journal of Visual Languages & Computing 14(6), 503–541 (2003) ISSN 1045-926XCrossRefGoogle Scholar
  3. Baglioni, M., Macedo, J., Renso, C., Wachowicz, M.: An Ontology-Based Approach for the Semantic Modelling and Reasoning on Trajectories. In: Song, I.-Y., Piattini, M., Chen, Y.-P.P., Hartmann, S., Grandi, F., Trujillo, J., Opdahl, A.L., Ferri, F., Grifoni, P., Caschera, M.C., Rolland, C., Woo, C., Salinesi, C., Zimányi, E., Claramunt, C., Frasincar, F., Houben, G.-J., Thiran, P. (eds.) ER Workshops 2008. LNCS, vol. 5232, pp. 344–353. Springer, Heidelberg (2008)CrossRefGoogle Scholar
  4. Baglioni, M., Fernandes de Macêdo, J.A., Renso, C., Trasarti, R., Wachowicz, M.: Towards semantic interpretation of movement behavior. In: Advances in GIScience, pp. 271–288 (2009)Google Scholar
  5. Bertin, J.: Semiology of graphics. University of Wisconsin Press (1983) ISBN 0299090604Google Scholar
  6. Brakatsoulas, S., Pfoser, D., Tryfona, N.: Modeling, storing and mining moving object databases. In: Proceedings of International Database Engineering and Applications Symposium, IDEAS 2004, pp. 68–77. IEEE (2004) ISBN 0769521681Google Scholar
  7. Carpendale, M.S.T., Cowperthwaite, D.J., Fracchia, F.D.: Distortion viewing techniques for 3-dimensional data. In: Proceedings of IEEE Symposium on Information Visualization 1996, pp. 46–53 (1996)Google Scholar
  8. Eccles, R., Kapler, T., Harper, R., Wright, W.: Stories in geotime. Information Visualization 7(1), 3–17 (2008) ISSN 1473-8716CrossRefGoogle Scholar
  9. Erwig, M., Güting, R.H., Schneider, M., Vazirgiannis, M.: Spatio-temporal data types: An approach to modeling and querying moving objects in databases. GeoInformatica 3(3), 269–296 (1999) ISSN 1384-6175CrossRefGoogle Scholar
  10. Forlines, C., Wittenburg, K.: Wakame: sense making of multi-dimensional spatial-temporal data. In: Proceedings of the International Conference on Advanced Visual Interfaces, pp. 33–40. ACM (2010)Google Scholar
  11. Gatalsky, P., Andrienko, N., Andrienko, G.: Interactive analysis of event data using space-time cube. In: Proceedings of Eighth International Conference on Information Visualisation, IV 2004, pp. 145–152. IEEE (2004) ISBN 0769521770Google Scholar
  12. Goodall, J.L., Maidment, D.R., Sorenson, J.: Representation of spatial and temporal data in ArcGIS. In: GIS and Water Resources III, AWRA, Nashville, TN (2004)Google Scholar
  13. Goodchild, M.F.: Citizens as sensors: web 2.0 and the volunteering of geographic information. GeoFocus (Editorial) 2, 24–32 (2007)Google Scholar
  14. Gruen, A.: Building extraction from aerial imagery. Remote Sensing of Impervious Surfaces (2008)Google Scholar
  15. Güting, R.H.: Moving object languages. In: Encyclopedia of Geographic Information Systems, pp. 732–740. Springer, Heidelberg (2008)Google Scholar
  16. Güting, R.H., Schneider, M.: Moving objects databases. Morgan Kaufmann Pub. (2005)Google Scholar
  17. Güting, R.H., Böhlen, M.H., Erwig, M., Jensen, C.S., Lorentzos, N.A., Schneider, M., Vazirgiannis, M.: A foundation for representing and querying moving objects. ACM Transactions on Database Systems (TODS) 25(1), 42 (2000) ISSN 0362-5915CrossRefGoogle Scholar
  18. Hägerstrand, T.: What about people in regional science? Papers in Regional Science 24(1), 6–21 (1970) ISSN 1056-8190CrossRefGoogle Scholar
  19. Hewagamage, K.P., Hirakawa, M., Ichikawa, T.: Interactive visualization of spatiotemporal patterns using spirals on a geographical map. In: vl, p. 296 (1999) ISSN 1049-2615Google Scholar
  20. ITC-2011. What has ITC done with Minard’s map (2011), http://www.itc.nl/personal/kraak/1812/minard-itc.htm (accessed March 1, 2011)
  21. Kraak, M.J.: The space-time cube revisited from a geovisualization perspective. In: Proceedings of the 21st International Cartographic Conference (1995/1988)Google Scholar
  22. Kraak, M.J.: Timelines, temporal resolution, temporal zoom and time geography. In: Proceedings 22nd International Cartographic Conference, A Coruna Spain (2005)Google Scholar
  23. Kraak, M.J.: Visualization viewpoints: beyond geovisualization. IEEE Computer Graphics and Applications 26(4), 6–9 (2006) ISSN 0272-1716CrossRefGoogle Scholar
  24. Langran, G., Chrisman, N.R.: A framework for temporal geographic information. Cartographica: The International Journal for Geographic Information and Geovisualization 25(3), 1–14 (1988) ISSN 0317-7173CrossRefGoogle Scholar
  25. Longley, P., Goodchild, M.F., Maguire, D.J., Rhind, D.W.: Geographical information systems: principles, techniques, management, and applications. John Wiley & Sons (2005)Google Scholar
  26. Maguire, D.J., Batty, M., Goodchild, M.F.: GIS, spatial analysis, and modeling. Esri Press (2005)Google Scholar
  27. Nanni, M., Pedreschi, D.: Time-focused clustering of trajectories of moving objects. Journal of Intelligent Information Systems 27(3), 267–289 (2006) ISSN 0925-9902CrossRefGoogle Scholar
  28. Palma, A.T., Bogorny, V., Kuijpers, B., Alvares, L.: A clustering-based approach for discovering interesting places in trajectories. In: Proceedings of the 2008 ACM Symposium on Applied Computing, pp. 863–868. ACM (2008)Google Scholar
  29. Peuquet, D.J.: Representations of space and time. The Guilford Press (2002) ISBN 1572307730Google Scholar
  30. Peuquet, D.J., Duan, N.: An event-based spatiotemporal data model (ESTDM) for temporal analysis of geographical data. International Journal of Geographical Information Science 9(1), 7–24 (1995) ISSN 1365-8816CrossRefGoogle Scholar
  31. Shekhar, S., Chawla, S.: Spatial databases: a tour. Prentice Hall (2003) ISBN 0130174807Google Scholar
  32. Slocum, T.A., McMaster, R.B., Kessler, F.C., Howard, H.H.: Thematic cartography and geovisualization. Pearson Prentice Hall, Upper Saddle River (2009)Google Scholar
  33. Smith, D.: Mapping, analysing and visualising fine scale urban form and socio-economic datasets. In: Workshop on Geographic Information in a Web-based World, Centre for Advanced Spatial Analysis, University College London (2009)Google Scholar
  34. Spaccapietra, S., Parent, C., Damiani, M.L., De Macedo, J.A., Porto, F., Vangenot, C.: A conceptual view on trajectories. Data & Knowledge Engineering 65(1), 126–146 (2008) ISSN 0169-023XCrossRefGoogle Scholar
  35. Spence, R.: Information Visualization: Design for Interaction. Prentice-Hall (2007) ISBN 0132065509Google Scholar
  36. Vanegas, C.A., Aliaga, D.G., Wonka, P., Müller, P., Waddell, P., Watson, B.: Modeling the appearance and behavior of urban spaces. In: Proceedings of Eurographics, State of the Art Report, vol. 1-18, Eurographics Association (2009)Google Scholar
  37. Vasiliev, I.R.: Mapping time. Cartographica: The International Journal for Geographic Information and Geovisualization 34(2), 1–51 (1997) ISSN 0317-7173MathSciNetCrossRefGoogle Scholar
  38. Waddell, P., Ulfarsson, G.F.: Introduction to urban simulation: design and development of operational models. Handbook in Transport 5, 203–236 (2004)Google Scholar
  39. Ware, C.: Information visualization: perception for design. Morgan Kaufmann (2004) ISBN 1558608192Google Scholar
  40. Weber, B., Müller, P., Wonka, P., Gross, M.: Interactive geometric simulation of 4d cities. Comput. Graph. Forum 28(2), 481–492 (2009) doi:http://dx.doi.org/10.1111/j.1467-8659.2009.01387.xGoogle Scholar
  41. Worboys, M.F.: A model for spatio-temporal information. In: Proceedings of the 5th International Symposium on Spatial Data Handling, vol. 2, pp. 602–611 (1992)Google Scholar
  42. Zhang, C.C., Qin, K.: GIS spatial analysis theory and methodology. Wuhan University Press (2004)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Chen Zhong
    • 1
  • Tao Wang
    • 1
  • Wei Zeng
    • 1
  • Stefan Müller Arisona
    • 1
  1. 1.Future Cities Laboratory SingaporeETH ZurichSwitzerland

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