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International Conference on Spatial Information Theory

COSIT 2007: Spatial Information Theory pp 268–284Cite as

Three Sampling Methods for Visibility Measures of Landscape Perception

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 4736))

Abstract

The character of a landscape can be seen as the outcome of people’s perception of their physical environment, which is important for spatial planning and decision making. Three modes of landscape perception are proposed: view from a viewpoint, view from a road, and view of an area. Three sampling methods to calculate visibility measures simulate these modes of perception. We compared the results of the three sampling methods for two study areas. The ROPE method provides information about subspaces. The road method enables the analysis of sequences. The grid point method calculates visibility measures at almost every location in space, providing detailed information about transitions and pattern change between original and new situations. The mean visibility values for the study areas reveal major differences between the sampling methods. Combining the results of the three methods is expected to be useful for describing all the facets of landscape perception.

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Author information

Authors and Affiliations

  1. Wageningen UR, Centre for Geo-Information, PO Box 47, 6700 AA Wageningen, The Netherlands

    Gerd Weitkamp, Arnold Bregt & Ron van Lammeren

  2. Wageningen UR, PO Box 47, 6700 AA Wageningen, The Netherlands

    Agnes van den Berg

Authors
  1. Gerd Weitkamp
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  2. Arnold Bregt
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  3. Ron van Lammeren
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  4. Agnes van den Berg
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Editor information

Stephan Winter Matt Duckham Lars Kulik Ben Kuipers

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© 2007 Springer-Verlag Berlin Heidelberg

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Weitkamp, G., Bregt, A., van Lammeren, R., van den Berg, A. (2007). Three Sampling Methods for Visibility Measures of Landscape Perception. In: Winter, S., Duckham, M., Kulik, L., Kuipers, B. (eds) Spatial Information Theory. COSIT 2007. Lecture Notes in Computer Science, vol 4736. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74788-8_17

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  • DOI: https://doi.org/10.1007/978-3-540-74788-8_17

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-74786-4

  • Online ISBN: 978-3-540-74788-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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