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Identification of fuzzy objects from field observation data

  • Formal Models of Space
  • Conference paper
  • First Online:
Spatial Information Theory A Theoretical Basis for GIS (COSIT 1997)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1329))

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Abstract

This paper introduces the concept of fuzzy objects for modeling natural phenomena measured by field observation data. The propagation of uncertainties resulting from stochastic data errors and classification fuzziness is discussed, especially the interaction between these two kinds of uncertainties. Four object models are proposed to represent objects of different uncertainty levels. The proposed methodology is illustrated by a case study in coastal geomorphology of Ameland, The Netherlands. The methodology developed in this paper will also be applicable for modeling natural environments and physical processes in other fields.

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Author information

Authors and Affiliations

  1. International Institute for Aerospace Survey and Earth Science - ITC, USA

    Cheng Tao, Martien Molenaar & Theo Bouloucos

Authors
  1. Cheng Tao
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  2. Martien Molenaar
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  3. Theo Bouloucos
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Editor information

Stephen C. Hirtle Andrew U. Frank

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© 1997 Springer-Verlag Berlin Heidelberg

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Tao, C., Molenaar, M., Bouloucos, T. (1997). Identification of fuzzy objects from field observation data. In: Hirtle, S.C., Frank, A.U. (eds) Spatial Information Theory A Theoretical Basis for GIS. COSIT 1997. Lecture Notes in Computer Science, vol 1329. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-63623-4_54

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  • DOI: https://doi.org/10.1007/3-540-63623-4_54

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-63623-6

  • Online ISBN: 978-3-540-69616-2

  • eBook Packages: Springer Book Archive

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