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Exploiting Perceptual Grouping for Map Analysis, Understanding and Generalization: The Case of Road and River Networks

  • Robert C. Thomson
  • Rupert Brooks
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2390)

Abstract

A successful project in automated map generalization under-taken at the National Atlas of Canada made extensive use of the implicit perceptual information present in road and river networks as a means of analysing and understanding their basic structure. Using the perceptual grouping principle of ‘good continuation’, a network is decomposed into chains of network arcs, termed ‘strokes’. The network strokes are then automatically ranked according to derived measures. Deleting strokes from the network following this ranking sequence provides a simple but very effective means of generalizing (attenuating) the network. This technique has practical advantages over previous methods. It has been employed in road network generalization, and applied in the selection of hydrologic data for a map covering Canada’s northern territories. The method may find further application in the interpretation of other forms of documents, such as diagrams or handwriting.

Keywords

Road Network Road Segment Main Stream River Network Perceptual Group 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2002

Authors and Affiliations

  • Robert C. Thomson
    • 1
  • Rupert Brooks
    • 2
  1. 1.School of ComputingRobert Gordon UniversityAberdeenUK
  2. 2.Canada Centre for Remote SensingNational Atlas of CanadaOttawaCanada

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