Exploring the Influence of Colour Distance and Legend Position on Choropleth Maps Readability

  • Alžběta BrychtováEmail author
Part of the Lecture Notes in Geoinformation and Cartography book series (LNGC)


This paper describes design and results of an experiment, which was aimed at exploring the influence of colour distance and legend position on map users’ ability to correctly interpret choropleth maps. Participants of the experiment were asked to find depicted area on the choropleth map and match it with the corresponding legend class by its colour. Experimental stimuli cover five levels of colour distance between neighbouring classes of choropleth maps (ΔE00 = 2, 4, 6, 8 and 10) and six different legend positions within the map sheet. The colour distance was determined by the method CIEDE2000. Results of the experiment were based primarily on analysing the accuracy of answers, and analysing duration of fixations in defined areas of interest. Research proved that increasing colour distance has a positive influence on the ability of users to interpret choropleth maps correctly. Legend position was not found to be significantly important factor of map readability. It was also proved, that sequential colour schemes with visually equal steps between classes are not appropriate, because map users have problems to interpret classes in the middle of the colour scheme. Based on these observations three optimised colour schemes were designed and evaluated. The highest accuracy of answers were observed for the colour scheme in which the lightness of classes if graduated by values of colour distance ΔE00 = 4, 8, 10, 8 and 4.


Legend Position Color Distance Choropleth Map Sequential Color Scheme Experimental Stimuli 
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.



The article was created within the project CZ.1.07/2.3.00/20.0170, supported by the European Social Fund and the state budget of the Czech Republic.


  1. Bjorke JT (1996) Framework for entropy-based map evaluation. Cartogr Geogr Inf Syst 23(2):78–95CrossRefGoogle Scholar
  2. Brewer CA, Hatchard GW, Harrower MA (2003) ColorBrewer in print: a catalog of color schemes for maps. Cartogr Geogr Inf Soc 30(1):5–32Google Scholar
  3. Brychtová A, Popelka S, Dobešová Z (2012) Eye-tracking methods for investigation of cartographic principles. In: 12th international multidisciplinary scientific geoconference (SGEM 2012), vol II, pp 1041–1048Google Scholar
  4. Chesneau E (2007) Improvement of colour contrasts in maps: application to risk maps. In: Proceedings of 10th AGILE international conference on geographic information science, pp 1–14Google Scholar
  5. CIE (2012) Termlist of International Commission on Illumination. Retrieved from
  6. Culp GM (2012) Increasing accessibility for map readers with acquired and inherited colour vision deficiencies: a re-colouring algorithm for maps. Cartogr J 49(4):302–311CrossRefGoogle Scholar
  7. Dent BD, Torguson JS, Hodler TW (2009) Cartography: thematic map design, 6th edn. Thomas Timp, p 336Google Scholar
  8. Eastman JR (1985) Cognitive models and cartographic design research. Cartogr J 22(2):95–101CrossRefGoogle Scholar
  9. Gilmartin P, Shelton E (1989) Choropleth maps on high resolution CRTs: the effect of number of classes and hue on communication. Cartographica 26(2):40–52CrossRefGoogle Scholar
  10. Harrower M (2007) Unclassed animated choropleth maps. Cartogr J 44(4):313–320CrossRefGoogle Scholar
  11. Holmqvist K, Nyström M, Andersson R, Dewhurst R, Jarodzka H, Van de Weijer J (2011) Eye tracking: a comprehensive guide to methods and measures, 1st edn. Oxford University Press, Oxford, p 560Google Scholar
  12. Jenny B, Kelso NV (2007) Designing maps for the colour-vision impaired. Bull Soc Cartogr SoC 41:9–12Google Scholar
  13. Kimerling JA (1985) The comparison of equal-value gray scales. Am Cartogr 12(2):132–142CrossRefGoogle Scholar
  14. Kröger J, Schiewe J, Weninger B (2013) Analysis and improvement of the open-streetmap street color scheme for users with color vision deficiencies. In: Proceedings of the 26th international cartographic conference, Dresden, p 17Google Scholar
  15. Kuehni RG (2003) Color space and its divisions: color order from antiquity to the present. Wiley, p 434Google Scholar
  16. Mersey JE (1990) Colour and thematic map design: the role of colour scheme and map complexity in choropleth map communication. Cartogr: Int J Geogr Inf Geovis 27(3)Google Scholar
  17. Olson JM, Brewer CA (1997) An evaluation of color selections to accommodate map users with color-vision impairments. Ann Assoc Am Geogr 87(1):103–134CrossRefGoogle Scholar
  18. Poole A, Ball LJ (2005) Eye tracking in human-computer interaction and usability research: current status and future. In: Ghaoui C (ed) Encyclopedia of human-computer interaction. Idea Group, Inc., Pennsylvania, p 13Google Scholar
  19. Schiewe J, Weninger B (2013) Visual encoding of acoustic parameters – framework and application to noise mapping. Cartogr J 50(4):332–344CrossRefGoogle Scholar
  20. SensoMotoric Instruments (2013) SMI experiment CenterTM. Retrieved from
  21. Slocum TA, McMaster RB, Kessler FC, Howard HH (2008) Thematic cartography and geovisualization, 3rd edn. Prentice Hall, p 576Google Scholar
  22. Steinrücken J, Plümer L (2013) Identification of optimal colours for maps from the web. Cartogr J 50(1):19–32CrossRefGoogle Scholar
  23. Stigmar H (2010) Making 21st century maps legible – methods for measuring and improving the legibility and usability of real-time maps. Dissertation thesis, Lund UniversityGoogle Scholar
  24. Stigmar H, Harrie L (2011) Evaluation of analytical measures of map legibility. Cartogr J 48(1):41–53CrossRefGoogle Scholar
  25. Werman M (2012) Improving perceptual color difference using basic color terms. Computer Research Repository, pp 1–14Google Scholar

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.Department of GeoinformaticsPalacký UniversityOlomoucCzech Republic

Personalised recommendations