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Geospatial Uncertainty Representation: Fuzzy and Rough Set Approaches

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Fifty Years of Fuzzy Logic and its Applications

Part of the book series: Studies in Fuzziness and Soft Computing ((STUDFUZZ,volume 326))

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Abstract

Uncertainty in geospatial data is often considered in the context of geographical information systems which enable a variety of operations and manipulation of spatial data. Here we consider how both fuzzy set and rough set theory has been used to represent geospatial data with uncertainty. Terrain modeling and triangulated irregular networks techniques utilizing fuzzy sets are presented. Rough set theory is overviewed and its application to spatial data is described. Issues of uncertainty in the representation of spatial relationships such as topological and directional relationships are discussed.

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Acknowledgments

We would like to thank the Naval Research Laboratory’s Base Program, Program Element No. 0602435 N for sponsoring this research.

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Authors and Affiliations

  1. Marine Geosciences Division, Geospatial Science and Technology Branch, Bldg. 1005, Raleigh, USA

    Frederick Petry

  2. Naval Research Laboratory, Stennis Space Center, MS 39529, Washington, USA

    Paul Elmore

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  1. Frederick Petry
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  2. Paul Elmore
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Correspondence to Frederick Petry .

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Editors and Affiliations

  1. Department of Computer Science, Texas State University, San Marcos, Texas, USA

    Dan E. Tamir

  2. School of Computing and Information Sciences, Florida International University, Miami, Florida, USA

    Naphtali D. Rishe

  3. School of Computing and Information Sciences, The University of South Florida, Tampa, Florida, USA, and Florida International University, Miami, Florida, USA

    Abraham Kandel

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Petry, F., Elmore, P. (2015). Geospatial Uncertainty Representation: Fuzzy and Rough Set Approaches. In: Tamir, D., Rishe, N., Kandel, A. (eds) Fifty Years of Fuzzy Logic and its Applications. Studies in Fuzziness and Soft Computing, vol 326. Springer, Cham. https://doi.org/10.1007/978-3-319-19683-1_24

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  • DOI: https://doi.org/10.1007/978-3-319-19683-1_24

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