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Using Semantic Similarity Metrics to Uncover Category and Land Cover Change

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GeoSpatial Semantics (GeoS 2005)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 3799))

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Abstract

Analysis of geographic data that uses a nominal measurement framework is problematic since it limits the possible analytic methods that can be applied. Land cover change analysis is an example of this where both the actual change analysis as well as classification changes over time can be problematic. This study illustrates the use of semantic similarity metrics on parameterized category definitions, and how these metrics can be used to assess land cover change over time as a degree of perceived change with respect to the original landscape state. It also illustrates how changes of the categories, the classification system, over time can be analyzed using semantic similarity measures.

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Author information

Authors and Affiliations

  1. Department of Geography, The Ohio State University, 1036 Derby Hall, 154 North Oval Mall, Columbus, OH, 43210-1361, USA

    Ola Ahlqvist

Authors
  1. Ola Ahlqvist
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Editor information

Editors and Affiliations

  1. Center for Web Research, Chile

    M. Andrea Rodríguez

  2. Department of Computer Science, University of Illinois at Chicago, 851 South Morgan Street (M/C 152), 60607, Chicago, IL, USA

    Isabel Cruz

  3. National Polytechnic, Institute, Mexico, Centro de Investigacion en Computacion, Mexico

    Sergei Levashkin

  4. National Center for Geographic Information and Analysis and Department of Spatial Information Science and Engineering, University of Maine, Boardman Hall, 04469-5711, Orono, ME, USA

    Max J. Egenhofer

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© 2005 Springer-Verlag Berlin Heidelberg

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Ahlqvist, O. (2005). Using Semantic Similarity Metrics to Uncover Category and Land Cover Change. In: Rodríguez, M.A., Cruz, I., Levashkin, S., Egenhofer, M.J. (eds) GeoSpatial Semantics. GeoS 2005. Lecture Notes in Computer Science, vol 3799. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11586180_8

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  • DOI: https://doi.org/10.1007/11586180_8

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-30288-9

  • Online ISBN: 978-3-540-32283-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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