An Empirical Study on Relevant Aspects for Sketch Map Alignment

  • Jia WangEmail author
  • Christoph Mülligann
  • Angela Schwering
Part of the Lecture Notes in Geoinformation and Cartography book series (LNGC, volume 1)


Sketch maps are drawn from memories and they are in general schematized and distorted. However, the schematizations and distortions are not random. They are a consequence during the cognitive process of perceiving, memorizing, and producing spatial layout. This paper describes an empirical study to investigate the impact of distortions on similarity perception. The study is designed as a human-subjects experiment of similarity ranking with two scenarios. Subjects were presented with 45 sketch maps and one reference map in each scenario; they were asked to rank the sketch maps according to their similarities with the reference map. The results of the experiment are used to develop a cognitively motivated alignment strategy for computer-based comparison of sketch maps and metric maps.


Street Network Street Segment Topological Relation Similarity Perception City Block 
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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  1. Beck RJ, Wood D (1976) Cognitive Transformation of Information from Urban Geographic Fields to Mental Maps. Environment and Behavior 8:199-238.CrossRefGoogle Scholar
  2. Blades M (1990) The reliability of data collected from sketch maps. Journal of Environmental Psychology 10:327-339.CrossRefGoogle Scholar
  3. Blaser A (1998) Technical report: Geo-spatial Sketches. NCGIA (TR 98-1).Google Scholar
  4. Blaser A, Egenhofer M (2000) A visual tool for querying geographic databases. AVI2000-Advanced Visual Databases, Salerno, Italy.Google Scholar
  5. Egenhofer M (1997) Query Processing in Spatial-Query-by-Sketch. Journal of Visual Languages and Computing 8(4): 403-424.CrossRefGoogle Scholar
  6. Egenhofer M and Mark D (1995) Naive Geography, in: Frank A and Kuhn W (eds.) COSIT ’95, Austria. Lecture Notes in Computer Science, Vol. 988, Springer-Verlag, pp. 1-15.Google Scholar
  7. Forbus K, Ferguson R, et al. (2001) Towards a computational model of sketching.Google Scholar
  8. International Conference on Intelligent User Interfaces, Sante Fe, NewGoogle Scholar
  9. Forbus K, Usher J, Chapman V (2003) Qualitative spatial reasoning about sketch maps. Proceedings of the Fifteenth Annual Conference on Innovative Applications of Artificial Intelligence, Acapulco, Mexico.Google Scholar
  10. Goodchild M (2007) Citizens as Sensors: The World of Volunteered Geography. GeoJournal 49(4): 211-221.CrossRefGoogle Scholar
  11. Ladd FC (1970) Black youths view their environment: Neighborhood maps. Environment and Behavior 2: 74-99.CrossRefGoogle Scholar
  12. Lynch K (1960) The Image of the City, Cambridge. MA, MIT Press.Google Scholar
  13. Montello, D, Freundschuh S (2005) Cognition of Geographic Information. A research agenda for geographic information science. R. B. McMaster and E. L. Usery. Boca Raton, Fl, USA, CRC Press: 61-91.Google Scholar
  14. Tversky, B (2003) Navigating by Mind and by Body. Spatial Cognition III: Routes and Navigation, Human Memory and Learning, Spatial Representation and Spatial Learning, Springer.Google Scholar
  15. Tversky, B (2005) How to get around by mind and body - Spatial thought, spatial action. Evolution, Rationality, and Cognition: A Cognitive Science for the Twenty-First Century. A. Zilhão, Routledge: 135-147Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Jia Wang
    • 1
    Email author
  • Christoph Mülligann
    • 1
  • Angela Schwering
    • 1
  1. 1.Institute for GeoinformaticsUniversity of MuensterMuensterGermany

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