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Evaluation in Generalisation

  • Jantien StoterEmail author
  • Xiang Zhang
  • Hanna Stigmar
  • Lars Harrie
Chapter
Part of the Lecture Notes in Geoinformation and Cartography book series (LNGC)

Abstract

This chapter presents the context, the issues and the research associated with the evaluation of map generalisation output as well as of map readability. Two main approaches of evaluation are described, i.e. visual and quantitative evaluation. Visual evaluation is subjective, qualitative, and time-consuming, while it is argued that quantitative evaluation is only appropriate for assessing specific aspects. Since automated evaluation is becoming very important in the field of automated generalisation, this chapter further explores the topic of automated evaluation. The previous frameworks for automated generalisation are reviewed and the three main components of automated evaluation are explained. Related to automated evaluation of generalisation output are formulas to automatically evaluate map readability. These are also discussed. This chapter ends with three case studies. The first Case study identifies and evaluates generalised building patterns. It demonstrates the three-step approach of data enrichment, data matching and constraint evaluation. The second Case study deals with formulas to automatically evaluate map readability and the third Case study carries out a comprehensive evaluation demonstrating the main aspects described in this chapter. Both visual and quantitative evaluation are applied of which the last one includes the three main components of automated evaluation. The chapter closes with conclusions and highlights research issues in evaluation.

Keywords

Hausdorff Distance Generalisation Process Scale Transition Automate Evaluation Target Dataset 
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.

Notes

Acknowledgments

Many people contributed to this chapter. We would like to thank all of them, specifically the EuroSDR project team.

This chapter is written with the support of the Dutch Technology Foundation STW, which is part of the Netherlands Organisation for Scientific Research (NWO), and which is partly funded by the Ministry of Economic Affairs (project code: 11300).

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Jantien Stoter
    • 1
    Email author
  • Xiang Zhang
    • 2
  • Hanna Stigmar
    • 3
  • Lars Harrie
    • 3
  1. 1.Delft University of Technology and KadasterDelftThe Netherlands
  2. 2.Wuhan UniversityWuhanChina
  3. 3.GIS CentreLund UniversityLundSweden

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