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Generalisation Operators

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Abstracting Geographic Information in a Data Rich World

Part of the book series: Lecture Notes in Geoinformation and Cartography ((ICA))

Abstract

This chapter summarises cartographic generalisation operators used to generalise geospatial data. It includes a review of recent approaches that have been tested or implemented to generalise networks, points, or groups. Emphasis is placed on recent advances that permit additional flexibility to tailor generalisation processing in particular geographic contexts, and to permit more advanced types of reasoning about spatial conflicts, preservation of specific feature characteristics, and local variations in geometry, content and enriched attribution. Rather than an exhaustive review of generalisation operators, the chapter devotes more attention to operators associated with network generalisation, which illustrates well the logic behind map generalisation developments. Three case studies demonstrate the application of operators to road thinning, to river network and braid pruning, and to hierarchical point elimination. The chapter closes with some summary comments and future directions.

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Acknowledgments

Work for this chapter was funded by several federal agencies in several countries. The work of Dr. Brewer is funded by the U.S. Geological Survey’s Center of Excellence for Geospatial Information Science (USGS-CEGIS) grant #06HQAG0131. The work of Dr. Buttenfield is supported by USGS-CEGIS grant #04121HS029. The research reported in the third Case study represents part of the PhD project of Pia Bereuter, funded by the Swiss National Science Foundation through project GenW2 + (SNF no. 200020-138109). Particular thanks go to Silvia Stofer of the National Data and Information Center for Swiss lichens and all the contributors for collecting and providing the data of the SwissLichens dataset.

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Authors and Affiliations

  1. Center of Excellence for Geospatial Information Science, United States Geological Survey, Rolla MO, USA

    Lawrence V. Stanislawski

  2. Department of Geography, University of Colorado, Boulder CO, USA

    Barbara P. Buttenfield

  3. Department of Geography, University of Zurich, Zurich, Switzerland

    Pia Bereuter

  4. Department of Information Engineering, University of Padova, Padova, Italy

    Sandro Savino

  5. Department of Geography, Pennsylvania State University, University Park PA, USA

    Cynthia A. Brewer

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  1. Lawrence V. Stanislawski
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  2. Barbara P. Buttenfield
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  3. Pia Bereuter
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  4. Sandro Savino
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  5. Cynthia A. Brewer
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Correspondence to Lawrence V. Stanislawski .

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Editors and Affiliations

  1. Department of Geosciences, Institute of Cartography, Dresden, Germany

    Dirk Burghardt

  2. IGN COGIT laboratory, Saint-Mande, France

    Cécile Duchêne

  3. Geographical Information Science, School of GeoSciences, Edinburgh, United Kingdom

    William Mackaness

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Stanislawski, L.V., Buttenfield, B.P., Bereuter, P., Savino, S., Brewer, C.A. (2014). Generalisation Operators. In: Burghardt, D., Duchêne, C., Mackaness, W. (eds) Abstracting Geographic Information in a Data Rich World. Lecture Notes in Geoinformation and Cartography(). Springer, Cham. https://doi.org/10.1007/978-3-319-00203-3_6

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