Advertisement

Visualization of Dynamic Spatial Data and Query Results Over Time in a GIS Using Animation

  • Glenn S. Iwerks
  • Hanan Samet
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1929)

Abstract

Changes in spatial query results over time can be visualized using animation to rapidly step through past events and present them graphically to the user. This enables the user to visually detect patterns or trends over time. This paper presents several methods to build animations of query results to visualize changes in a dynamic spatial database over time.

Keywords

dynamic spatio-temporal data visualization animated cartography 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    W. G. Aref and H. Samet. Effcient window block retrieval in quadtree-based spatial databases. GeoInformatica, 1(1):59–91, April 1997.CrossRefGoogle Scholar
  2. 2.
    O. Buneman and E. Clemons. Effciently monitoring relational databases. ACM Transactions on Database Systems, 4(3):368–382, September 1979.CrossRefGoogle Scholar
  3. 3.
    C. S. Campbell and S. L. Egbert. Animated cartography: Thirty years of scratching the surface. Cartographica, 27(2):24–46, 1990.Google Scholar
  4. 4.
    A. Gupta, I. S. Mumick, and V. S. Subrahmanian. Maintaining views incrementally. InProceedings of the ACM SIGMOD Conference, Washington, D.C., May 1993.Google Scholar
  5. 5.
    G. R. Hjaltason and H. Samet. Incremental distance join algorithms for spatial databases. In Proceedings of the ACM SIGMOD Conference, pages 237–248, Seattle, WA, June 1998.Google Scholar
  6. 6.
    G. R. Hjaltason and H. Samet. Distance browsing in spatial databases. ACM Transactions on Database Systems, 24(2):265–318, June 1999.CrossRefGoogle Scholar
  7. 7.
    G. Iwerks and H. Samet. The spatial spreadsheet. In Visual Information and information Systems: Third International Conference Proceedings, VISUAL’99, pages 317–324, Amsterdam, The Netherlands, June 1999. Springer-Verlag.Google Scholar
  8. 8.
    B. Jobard and W. Lefer. The motion map: Eficient computation of steady ow animations. In Proceedings of Visualization’ 97, pages 323–328. IEEE, October 1997.Google Scholar
  9. 9.
    M. Kang and S. Servign. Animated cartography for urban soundscape information. In Proceedings of the 7th Symposium on Geographic Information Systems, pages 116–121, Kansas City, MO, November 1999. ACM.Google Scholar
  10. 10.
    A. Koussoulakou and M. J. Kraak. Spatio-temporal maps and cartographic communication. The Cartographic Journal, 29:101–108, 1992.Google Scholar
  11. 11.
    M. Kraak and A. M. MacEachren. Visualization of the temporal component of spatial data. In Proceedings of SDH 1994, pages 391–409, 1994.Google Scholar
  12. 12.
    K. Ma, D. Smith, M. Shih, and H. Shen. Effcient encoding and rendering of time-varying volumn data. Technical Report NASA/CR-1998-208424 ICASE Report No. 98-22, National Aeronautics and Space Administration, Langley Research Center, Hampton. VA, June 1998.Google Scholar
  13. 13.
    A. M. MacEachren, F. P. Boscoe, D. Haug, and L. W. Pickle. Geographic visualization: Designing manipulable maps for exploring temporally varying georeferenced statistics. In IEEE Symposium on Information Visualization, 1998, Proceedings, pages 87–94,156. IEEE, 1998.Google Scholar
  14. 14.
    A. M. MacEachren and D. DiBiase. Animated maps of aggregate data: Conceptual and pratical problems. Cartography and Geographic Information Systems, 18(4):221–229, 1991.CrossRefGoogle Scholar
  15. 15.
    R. E. Meisner, M. Bittner, and S.W. Dech. Visualization of satellite derived timeseries datasets using computer graphics and computer animation. In 1997 IEEE International Geoscience and Remote Sensing, 1997. IGARSS’ 97. Remote Sensing-A Scientific Vision for Sustainable Development, pages 1495–1498, Oberpfaffen-hofen, Germany, August 1997. IEEE.Google Scholar
  16. 16.
    R. E. Meisner, M. Bittner, and S.W. Dech. Computer animation of remote sensing-based time series data sets. In IEEE Transactions on Geoscience and Remote Sensing, pages 1100–1106, Oberpfaffenhofen, Germany, March 1999. IEEE.Google Scholar
  17. 17.
    F.Y Schroder. Visualizing meteorological data for a lay audience. IEEE Computer Graphics and Applications, 13(2):12–14, September 1993.CrossRefGoogle Scholar
  18. 18.
    A. Silberschatz, H. F. Korth, and S. Sudarshan. Database System Concepts. McGraw-Hill, New York, third edition, 1996.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2000

Authors and Affiliations

  • Glenn S. Iwerks
    • 1
  • Hanan Samet
    • 1
  1. 1.Computer Science DepartmentCenter for Automation Research, Institute for Advanced Computer Studies University of MarylandMaryland

Personalised recommendations