Terrain Generalisation

  • Eric GuilbertEmail author
  • Julien Gaffuri
  • Bernhard Jenny
Part of the Lecture Notes in Geoinformation and Cartography book series (LNGC)


This chapter reviews recent development in terrain generalisation. We focus on issues of aesthetics and legibility in the application of cartographic generalisation. Generalisation methods are relevant to traditional terrain representations (spot heights, contours, hypsometric colours, shaded relief) and to grid and triangulated surface generalisation. First we consider issues related to relief representation at different scales. As generalisation requires knowledge about the terrain morphology, several approaches focusing on the classification of terrain features according to morphometric or topological criteria have been developed. Cartographic generalisation methods are reviewed with consideration given to conflicts between terrain representations and other object type data on the map. In the second part of this chapter, three case studies illustrating previous developments are presented. First, a generalisation method for hypsometric map production is described where important valleys and mountain ridges are accentuated to improve their representation. Second, a method selecting features represented by isobaths and answering specific constraints of nautical charts is presented. The third case study is a generalisation method which models the relationship between terrain and other objects such as buildings and rivers.


Digital Terrain Model Triangulate Irregular Network Triangulate Irregular Network Safety Constraint Shade Relief 
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 International Publishing Switzerland 2014

Authors and Affiliations

  • Eric Guilbert
    • 1
    Email author
  • Julien Gaffuri
    • 2
    • 3
  • Bernhard Jenny
    • 4
  1. 1.Land Surveying and Geo-Informatics DepartmentThe Hong Kong Polytechnic UniversityKowloonHong Kong
  2. 2.Digital Earth and Reference Data unit, Institute for Environment and Sustainability, Joint Research CentreIspraItaly
  3. 3.Laboratoire COGIT, IGNSaint-MandéFrance
  4. 4.College of Earth, Ocean, and Atmospheric SciencesOregon State UniversityCorvallisUSA

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