Mental Processing of Geographic Knowledge

  • Thomas Barkowsky
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2205)


The contribution presents a computational modeling approach to geographic knowledge processing in mind. Geographic knowledge is assumed to be stored in a piecemeal manner. Spatial knowledge fragments form a hierarchical structure of lean knowledge. An actual mental image representation is constructed when needed to perform a specific task. In this construction process missing information is complemented to create a determinate mental image. – First, the artificial intelligence perspective taken is elaborated. After a short review of conceptions on mental processing of spatial knowledge from psychology and artificial intelligence we outline the model MIRAGE. The internal structure and the operating of the model is elaborated using an exemplary scenario. Problems in constructing mental images from given pieces of knowledge are demonstrated and discussed. The paper concludes with a discussion of the approach with respect to its modeling objective. We point to further research questions and to potential applications.


Cognitive maps spatial knowledge construction mental imagery diagrammatic reasoning experimental computational modeling 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. Anderson, J. R. (1978). Arguments concerning representations for mental imagery. Psychological Review, 85(4), 249–277.CrossRefGoogle Scholar
  2. Appleyard, D. (1970). Styles and methods of structuring a city. Environment and Behavior, 2, 100–118.CrossRefGoogle Scholar
  3. Baddeley, A. D. (1986). Working memory. New York: Oxford University Press.Google Scholar
  4. Braitenberg, V. (1984). Vehicles–Experiments in synthetic psychology. Cambridge, MA: MIT Press.Google Scholar
  5. Bransford, J. D., Barclay, J. R., & Franks, J. J. (1972). Sentence memory: A constructive versus interpretative approach. Cognitive Psychology, 3, 193–209.CrossRefGoogle Scholar
  6. Cohn, A. G. (1997). Qualitative spatial representation and reasoning techniques. In G. Brewka, C. Habel, & B. Nebel (Eds.), KI-97: Advances in Artificial Intelligence (pp. 1–30). Berlin: Springer.Google Scholar
  7. Couclelis, H. (1992). People manipulate objects (but cultivate fields): Beyond the raster-vector debate in GIS. In A. U. Frank, I. Campari, & U. Formentini (Eds.), Theories and methods of spatio-temporal reasoning in geographic space (pp. 65–77). Berlin: Springer.Google Scholar
  8. Downs, R. M., & Stea, D. (1977). Maps in minds: reflections on cognitive mapping. New York: Harper & Row.Google Scholar
  9. Finke, R. (1989). Principles of mental imagery. Cambridge, MA: MIT-Press.Google Scholar
  10. Frank, A. (1992). Qualitative spatial reasoning with cardinal directions. Proc. of the Seventh Austrian Conference on Artificial Intelligence, Vienna (pp. 157–167). Berlin: Springer.Google Scholar
  11. Freksa, C., Barkowsky, T., & Klippel, A. (1999). Spatial symbol systems and spatial cognition: A computer science perspective on perception-based symbol processing. Behavioral and Brain Sciences, 22(4), 616–617.CrossRefGoogle Scholar
  12. Freksa, C., & Röhrig, R. (1993). Dimensions of qualitative spatial reasoning. In N. P. Carreté & M. G. Singh (Eds.), Qualitative reasoning and decision technologies, Proc. QUARDET’93 (pp. 483–492). Barcelona.Google Scholar
  13. Friedman, A., & Brown, N. R. (2000). Reasoning about geography. Journal of Experimental Psychology: General, 129(2), 193–219.CrossRefGoogle Scholar
  14. Glasgow, J., Narayanan, H., & Chandrasekaran, B. (Eds.) (1995). Diagrammatic reasoning: Computational and cognitive perspectives. Cambridge, MA: MIT-Press.Google Scholar
  15. Glasgow, J., & Papadias, D. (1992). Computational imagery. Cognitive Science, 16, 355–394.CrossRefGoogle Scholar
  16. Hegarty, M. (2000). Capacity limits in diagrammatic reasoning. In M. Anderson, P., Cheng., & V. Haarslev (Eds.), Theory and application of diagrams (pp. 194–206). Berlin: Springer.CrossRefGoogle Scholar
  17. Hirtle, S. C. (1998). The cognitive atlas: using GIS as a metaphor for memory. In M. Egenhofer & R. Golledge (Eds.), Spatial and temporal reasoning in geographic information systems (pp. 267–276). Oxford University Press.Google Scholar
  18. Hirtle, S. C., & Heidorn, P. B. (1993). The structure of cognitive maps: Representations and processes. In T. Gärling & R. G. Golledge (Eds.), Behavior and environment: Psychological and geographical approaches (pp. 170–192). Amsterdam: North-Holland.CrossRefGoogle Scholar
  19. Hirtle, S. C., & Jonides J. (1985). Evidence of hierarchies in cognitive maps. Memory & Cognition, 13(3), 208–217.Google Scholar
  20. Intraub, H., & Hoffman, J. E. (1992). Reading and visual memory: Remembering scenes that were never seen. American Journal of Psychology, 105(1), 101–114.CrossRefGoogle Scholar
  21. Johnson-Laird, P. N. (1983). Mental models. Cambridge, MA: Harvard University Press.Google Scholar
  22. Koedinger, K. R. (1992). Emergent properties and structural constraints: Advantages of diagrammatic representations for reasoning and learning. AAAI Spring Symposion on Reasoning with Diagrammatic Representations, Stanford University, March 27–29.Google Scholar
  23. Kosslyn, S. M. (1980). Image and mind. Cambridge, MA: Harvard University Press.Google Scholar
  24. Kosslyn, S. M. (1987). Seeing and imagining in the cerebral hemispheres: a computational approach. Psychological Review, 94, 148–175.CrossRefGoogle Scholar
  25. Kosslyn, S. M. (1994). Image and brain–The resolution of the imagery debate. Cambridge, MA: MIT Press.Google Scholar
  26. Kosslyn, S. M., & Shin, L. M. (1994). Visual mental images in the brain: Current issues. In M. J. Farah & G. Ratcliff (Eds.), The neuropsychology of high-level vision (pp. 269–296). Hillsdale, NJ: Lawrence Erlbaum.Google Scholar
  27. Kuhn, W. (1993). Metaphors create theories for users. In A. U. Frank & I. Campari (Eds.), Spatial information theory–A theoretical basis for GIS (pp. 366–376). Berlin: Springer.Google Scholar
  28. Kuipers, B. (1982). The ‘map in the head’ metaphor. Environment and Behavior, 14(2), 202–220.CrossRefMathSciNetGoogle Scholar
  29. Larkin, J. H., & Simon, H. A. (1987). Why a diagram is (sometimes) worth ten thousand words. Cognitive Science, 11, 65–99.CrossRefGoogle Scholar
  30. Lee, T. R. (1968). Urban neighborhood as a socio-spatial schema. Human Relations, 21, 241–268.CrossRefGoogle Scholar
  31. Lynch, K. (1960). The image of the city. Cambridge, MA: MIT Press.Google Scholar
  32. McNamara, T. P., Hardy, J. K., & Hirtle, S. C. (1989). Subjective hierarchies in spatial memory. Journal of Experimental Psychology: Learning, Memory and Cognition, 15(2), 211–227.CrossRefGoogle Scholar
  33. Montello, D. R. (1992). The geometry of environmental knowledge. In A. U. Frank, I. Campari, & U. Formentini (Eds.), Theories and methods of spatio-temporal reasoning in geographic space (pp. 136–152). Berlin: Springer.Google Scholar
  34. Montello, D. R. (1998). A new framework for understanding the acquisition of spatial knowledge in large-scale environments. In M. J. Egenhofer & R. G. Golledge (Eds.), Spatial and temporal reasoning in geographic information systems (pp. 143–154). New York: Oxford University Press.Google Scholar
  35. Paivio, A. (1971). Imagery and language. In S. J. Segal (Ed.), Imagery: Current cognitive approaches (pp. 7–32). New York: Holt, Rinehart & Winston.Google Scholar
  36. Peterson, M. (1995). Interactive and animated cartography. Englewood Cliffs, NJ: Prentice Hall.Google Scholar
  37. Portugali, J. (Ed.) (1996a). The construction of cognitive maps. Dordrecht: Kluwer Academic Publishers.Google Scholar
  38. Portugali, J. (1996b). Inter-representation networks and cognitive maps. In J. Portugali (Ed.), The construction of cognitive maps (pp. 11–43). Dordrecht: Kluwer Academic Publishers.CrossRefGoogle Scholar
  39. Schacter, D. L., Cooper, L. A., Delaney, S. M., Peterson, M. A., & Tharan, M. (1991). Implicit memory for possible and impossible objects: Constraints on the construction of structural descriptions. Journal of Experimental Psychology: Learning, Memory, and Cognition, 17, 3–19.CrossRefGoogle Scholar
  40. Schlieder, C. (1999). The construction of preferred mental models in reasoning with interval relations. In G. Rickheit & C. Habel (Eds.), Mental models in discourse processing and reasoning (pp. 333–357). Amsterdam: North-Holland.CrossRefGoogle Scholar
  41. Sloman, A. (1994). Explorations in design space. In A. G. Cohn (Ed.), Proceedings of the 11th Conference on Artificial Intelligence (ECAI’94) (pp. 578–582). Chichester et al.: Wiley.Google Scholar
  42. Stevens, A., & Coupe. P. (1978). Distortions in judged spatial relations. Cognitive Psychology, 10, 422–437.CrossRefGoogle Scholar
  43. Sulin, R. A., & Dooling, D. J. (1974). Intrusion of a thematic idea in retention of prose. Journal of Experimental Psychology, 103, 255–262.CrossRefGoogle Scholar
  44. Tolman, E. C. (1948). Cognitive maps in rats and men. The Psychological Review, 55(4), 189–208.CrossRefGoogle Scholar
  45. Tversky, B. (1991). Spatial mental models. The Psychology of Learning and Motivation, 27, 109–145.CrossRefGoogle Scholar
  46. Tversky, B. (1992). Distortions in cognitive maps. Geoforum, 23(2), 131–138.CrossRefGoogle Scholar
  47. Tversky, B. (1993). Cognitive maps, cognitive collages, and spatial mental models. In A. Frank & I. Campari (Eds.), Spatial information theory (pp. 14–24). Berlin: Springer.Google Scholar
  48. Vieu, L. (1997). Spatial representation and reasoning in artificial intelligence. In O. Stock (Ed.), Spatial and temporal reasoning (pp. 5–41). Dordrecht: Kluwer Academic Publishers.CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2001

Authors and Affiliations

  • Thomas Barkowsky
    • 1
  1. 1.Department for InformaticsUniversity of HamburgHamburgGermany

Personalised recommendations