A Dual Representation of Uncertain Dynamic Spatial Information

  • Gloria Bordogna
  • Paola Carrara
  • Sergio Chiesa
  • Stefano Spaccapietra
Conference paper
First Online:
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2715)

Abstract

A dual representation of spatio-temporal phenomena whose observation is affected by uncertainty is proposed in the context of fuzzy set and possibility theory. The concept of fuzzy time validity of a snapshot of a dynamic phenomenon is introduced as well as the concept of possible spatial reference of the phenomenon at a given time instant. Then a mechanism to generate virtual snapshots of the phenomenon, showing its possible spatial reference at consecutive time instants, is described.

Keywords

Dual Representation Dynamic Phenomenon Fuzzy Subset Spatial Reference Possibility Theory 
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.
This is a preview of subscription content, log in to check access.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    T. Abraham, J. F. Roddick, Survey of Spatio-temporal databases, Geoinformatica, 3(1), (1999), 61–99.CrossRefGoogle Scholar
  2. 2.
    K.K. Al-Taha, R.T. Snodgrass, M.D. Soo, Bibliography on spatio-temporal databases, SIGMOD Record, 22 (1993), 56–67.CrossRefGoogle Scholar
  3. 3.
    M.J. Egenhofer, R.J. Golledge, Spatial and Temporal reasoning in geographic information systems, Oxford University Press, (1998).Google Scholar
  4. 4.
    Frank ed., Theories and methods of spatio-temporal reasoning in geographic space, Lecture Notes in Computer Science 639, Springer-Verlag, (1992).Google Scholar
  5. 5.
    M.F. Worboys, A Unified model for spatial and temporal information, The Computer Journal, 37(1),(1994),27–34.CrossRefGoogle Scholar
  6. 6.
    Parent, S. Spaccapietra, E. Zimanyi, Spatio-temporal conceptual models: data structures + space + time, 7th ACM Sym. on Advances in GIS, Kansas City, Kansas, (1999).Google Scholar
  7. 7.
    M.F. Goodchild, S. Gopal eds, Accuracy of spatial databases, Taylor and Francis, London, (1989)Google Scholar
  8. 8.
    D.H. Maling, Measurements from maps: principles and methods of cartometry, Pergamon press, NY, (1989).Google Scholar
  9. 9.
    P.A. Burrough, A.U. Frank eds, Geographic Objects with Indeterminate Boundaries, in GISDATA series, Taylor & Francis, (1996).Google Scholar
  10. 10.
    M. Codd, F. Petry, V. Robinson eds, Uncertainty in Geographic Information Systems and Spatial data, special issue of Fuzzy Sets and Systems, 113,(1), (2000), 1–159.Google Scholar
  11. 11.
    D. Dubois, J. Lang, E. Prade, Timed possibilistic logic, Fundamenta Informaticae, XV,4, (1991), 211–234.MathSciNetGoogle Scholar
  12. 12.
    R. De Caluwe, G. De Tré, B. Van der Cruyssen, F. Devos, P. Maesfranckx, Time Management in Fuzzy and Uncertain Object-Oriented Databases, O. Pons, M.A. Vila, J. Kacprzyk (eds.), Knowledge Management in Fuzzy Databases, Studies in Fuzziness and Soft Computing, Physica-Verlag, Heidelberg, Germany, (2000), 67–88.Google Scholar
  13. 13.
    R.R. Yager, Retrieval from Multimedia databases using Fuzzy temporal Concepts, M.A. Vila, J. Kacprzyk (eds.), Knowledge Management in Fuzzy Databases, Studies in Fuzziness and Soft Computing, Physica-Verlag, Heidelberg, Germany, (2000) ibidem, 261–274.Google Scholar
  14. 14.
    S. Dragicevic, D. J. Marceau, An application of fuzzy logic reasoning for GIS temporal modeling of dynamic processes, Fuzzy sets and Systems, 113(1), (2000), 69–80.MATHCrossRefGoogle Scholar
  15. 15.
    Ratsiatou, E. Stefanakis, Spatio-Temporal Multicriteria Decision making under Uncertainty, in Proc. of the 1st Int. Symposium on Robust statistics and fuzzy techniques in geodesy and GIS, Zurich, (2001).Google Scholar
  16. 16.
    Yazici, Q. Zhu, N. Sun, Semantic data modeling of spatiotemporal database applications, Int. J. of Intelligent Systems, 16(7), (2001), 881–904.MATHCrossRefGoogle Scholar
  17. 17.
    L.A. Zadeh, Fuzzy Sets as a Basis for a Theory of Possibility, Fuzzy Sets and Systems, 1, (1978), 3–28.MATHCrossRefMathSciNetGoogle Scholar
  18. 18.
    G. Bordogna, S. Chiesa, A Fuzzy Object based Data Model for Imperfect Spatial Information Integrating Exact-Objects and Fields, Int. J. of Uncertainty, Fuzziness and Knowledge-Based Systems, 11(1) (2003), 23–41.MATHCrossRefGoogle Scholar
  19. 19.
    S. Spaccapietra, C. Parent, E. Zimanyi, MurMur: a research agenda on multiple representations, Proc. of DANTE’99, Kyoto, (1999).Google Scholar
  20. 20.
    P. Fisher, Sorites paradox and vague geographies, Fuzzy Sets and Systems, 113(1), (2000), 7–18.CrossRefGoogle Scholar
  21. 21.
    L. A. Zadeh, The concept of a linguistic variable and its application to approximate reasoning, parts I, II. Information Science, 8, 199–249, (1987), 301–357.CrossRefMathSciNetGoogle Scholar
  22. 22.
    R.M. Guting et al., A foundation for representing and querying moving objects, FernUniversitaet Hagen, Informatik-report 238, (1998).Google Scholar
  23. 23.
    F.E. Petry, Fuzzy Databases, Kluwer Academic Pub., (1996).Google Scholar
  24. 24.
    P. Bosc, and H. Prade, An Introduction to the Fuzzy Set and Possibility Theory-based Treatment of Flexible Queries and Uncertain and Imprecise Databases, in Uncertainty Management in Information Systems: from Needs to Solutions, A. Motro and P. Smets eds, Kluwer Academic Pub., (1994), 285–324.Google Scholar
  25. 25.
    G. Bordogna, S. Chiesa, Fuzzy Querying of Spatial Information, Proc. of EUROFUSE, Varenna, (2002).Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • Gloria Bordogna
    • 1
  • Paola Carrara
    • 2
  • Sergio Chiesa
    • 1
  • Stefano Spaccapietra
    • 3
  1. 1.CNR-IDPAsezione di MilanoBergamoItaly
  2. 2.CNR-IREAsezione di MilanoMilanoItaly
  3. 3.Database Lab.Swiss Federal Institute of Technology (EPFL)LausanneSwitzerland

Personalised recommendations