A Data and Query Model for Streaming Geospatial Image Data

  • Michael Gertz
  • Quinn Hart
  • Carlos Rueda
  • Shefali Singhal
  • Jie Zhang
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4254)


Most of the recent work on adaptive processing and continuous querying of data streams assume that data objects come in the form of tuples, thus relying on the relational data model and traditional relational operators as basis for query processing techniques. Complex types of objects, such as multidimensional data sets or the vast amounts of raster image data continuously streaming down to Earth from satellites have not been considered.

In this paper, we introduce a data and query model as a comprehensive and practically relevant basis for managing and querying streams of remotely-sensed geospatial image data. Borrowing basic concepts from Image Algebra, we detail a data model that reflects basic properties of such streams of imagery. We present a query model that includes stream restrictions, transforms, and compositions, and provides a sound basis for formulating expressive and practically relevant queries over streams of image data. Finally, we outline how the data and query model is currently realized in a data stream management system for geospatial image data that supports geographic applications.


Point Lattice Query Processing Complex Query Query Model Continuous Query 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Michael Gertz
    • 1
  • Quinn Hart
    • 1
  • Carlos Rueda
    • 1
  • Shefali Singhal
    • 1
  • Jie Zhang
    • 1
  1. 1.Department of Computer ScienceUniversity of CaliforniaDavisU.S.A.

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