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Spatio-temporal Aggregates over Streaming Geospatial Image Data

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Current Trends in Database Technology – EDBT 2006 (EDBT 2006)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 4254))

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Abstract

Geospatial image data obtained by satellites and aircraft are increasingly important to a wide range of applications, such as disaster management, climatology, and environmental monitoring. Because of the size of the data and the speed at which it is generated, computing spatio-temporal aggregates over geospatial image data is extremely demanding. Due to the special characteristics of the data, existing spatio-temporal aggregation model and evaluation approaches are not suitable for computing aggregates over such data.

In this paper, we outline the key challenges of computing spatio-temporal aggregates over streaming geospatial image data, and present three goals of our research work. We also discuss several preliminary results and future research directions.

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Author information

Authors and Affiliations

  1. Department of Computer Science, University of California, Davis, CA, 95616, U.S.A.

    Jie Zhang

Authors
  1. Jie Zhang
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Editor information

Editors and Affiliations

  1. Technische Universität München, Germany

    Torsten Grust

  2. International University in Germany, Germany

    Hagen Höpfner

  3. University of the Basque Country,  

    Arantza Illarramendi

  4. University of Bayreuth, Bayreuth, Germany

    Stefan Jablonski

  5. Università di Milano, Italy

    Marco Mesiti

  6. University of Erlangen-Nurmberg, Germany

    Sascha Müller

  7. Institut für Informatik, Ludwig-Maximilians-Universität, Oettingenstr. 67, 80538, München, Germany

    Paula-Lavinia Patranjan

  8. Dept. of Computer Science and Automation, TU Ilmenau

    Kai-Uwe Sattler

  9. Faculty of Computer Science, Otto-von-Guericke-University Magdeburg, Germany

    Myra Spiliopoulou

  10. Université de Mons-Hainaut, Mons, Belgium

    Jef Wijsen

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© 2006 Springer-Verlag Berlin Heidelberg

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Zhang, J. (2006). Spatio-temporal Aggregates over Streaming Geospatial Image Data. In: Grust, T., et al. Current Trends in Database Technology – EDBT 2006. EDBT 2006. Lecture Notes in Computer Science, vol 4254. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11896548_4

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  • DOI: https://doi.org/10.1007/11896548_4

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-46788-5

  • Online ISBN: 978-3-540-46790-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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