Advertisement

Qualitative representation of change

  • Kathleen Homsby
  • Max J. Egenhofer
Representation of Change
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1329)

Abstract

Current geographic information systems (GISs) have been designed for querying and maintaining static databases representing static phenomena and give little support to those users who wish to represent dynamic information or incorporate temporality into their studies. In order to integrate phenomena that change over space and time in GISs, a better understanding of the underlying components of change and how people reason about change is needed. This paper focuses on a qualitative representation of change. It offers a classification of change based on object identity and the set of operations that either preserve or change identity. These operations can be applied to single or composite objects and combined to express the semantics of sequences of change. An iconic, visual language is developed to represent the various types of change and applied to examples to illustrate the application of this language. Such a formalization of the basic components of change lays the foundation for a new generation of formal models that captures the semantics of change and leads to improved interoperability between GISs and process models or simulation software.

Keywords

Geographic Information System British Columbia Object Identity Original Object Change Operation 
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.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Ackerman, E. (1994). Simulation of micropopulations in epidemiology: Tutorial 1. Simulation: an introduction, International Journal of Bio-Medical Computing 36: 229–238.Google Scholar
  2. Al-Taha, K. and R. Barrera (1994). Identities through time. In: M. Ehlers and D. Steiner (eds.), Proceedings of an International Workshop on Requirements for Integrated GIS, New Orleans, LA, Environmental Research Institute of Michigan (ERIM), pp. 1–12.Google Scholar
  3. Al-Taha, K. and R. Barrera (1990). Temporal data and GIS: An overview. GIS/LIS '90, Anaheim, CA, pp. 244–254.Google Scholar
  4. Armstrong, M. (1988). Temporality in spatial databases. GISILIS '88, San Antonio, TX, pp. 880–889.Google Scholar
  5. Bonfatti, F. and L. Pazzi (1995). Ontological foundations for state and identity within the object-oriented paradigm. International Journal of Human-Computer Studies 43:891–906.Google Scholar
  6. Catarci, T., G. Santucci, and M. Angelaccio (1993). Fundamental graphical primitives for visual query languages. Information Systems 18(2): 75–98.Google Scholar
  7. Chen, P. (1976). The Entity-Relationship Model-toward a unified view of data. ACM Transactions on Database Systems 1(1): 9–36.Google Scholar
  8. Chrisman, N. (1997). Beyond the snapshot: changing the approach to change, error, and process. In: M. Egenhofer and R. Golledge (eds.), Spatial and Temporal Reasoning in Geographic Information Systems. New York, NY, Oxford University Press, pp. 87–95.Google Scholar
  9. Claramunt, C. and M. Thèriault (1996). Toward semantics for modelling spatiotemporal processes within GIS. In: M. Kraak and M. Molenaar (eds.), 7th International Symposium on Spatial Data Handling, Delft, The Netherlands, pp. 2.27–2.43.Google Scholar
  10. Claramunt, C. and M. Thèriault (1995). Managing time in GIS: an event-oriented approach. In: J. Clifford and A. Tuzhilin (eds.), Recent Advances in Temporal Databases. Berlin, Springer-Verlag. pp. 23–42.Google Scholar
  11. Clarke, K., J. Brass, and P. Riggan (1994). A cellular automaton model of wildfire propagation and extinction. Photogrammetric Engineering and Remote Sensing 60(11): 1355–1367.Google Scholar
  12. Cliff, A., P. Haggett, and D. Stroup (1992). The geographic structure of measles epidemics in the Northeastern United States. American Journal of Epidemiology 136(5): 592–602.Google Scholar
  13. Cliff, A., P. Haggett, J. Ord, and G. Versey (1981). Spatial Diffusion: An Historical Geography of Epidemics in an Island Community, Cambridge, UK, Cambridge University Press.Google Scholar
  14. DiBiase, D., A. MacEachren, J. Krygier, and C. Reeves (1992). Animation and the role of map design in scientific visualization. Cartography and Geographic Information Systems 19(4): 201–214.Google Scholar
  15. Egenhofer, M. and J. Herring (1990). A mathematical framework for the definition of topological relationships. In: K. Brassel and H. Kishimoto (eds), Fourth International Symposium on Spatial Data Handling, Zurich, Switzerland, International Geographic Union, pp. 803–813.Google Scholar
  16. Egenhofer, M. and R. Golledge (1997). Spatial and Temporal Reasoning in Geographic Information Systems. New York, NY, Oxford University Press.Google Scholar
  17. Frank, A. (1994). Qualitative temporal reasoning in GIS-ordered time scales. In: T. Waugh and R. Healey (eds.), Sixth International Symposium on Spatial Data Handling, Edinburgh, Scotland, pp. 410–431.Google Scholar
  18. Frank, A. (1996). Qualitative spatial reasoning: cardinal directions as an example, International Journal of Geographical Information Systems 10(3): 269–290.Google Scholar
  19. Helm, R., K. Marriott, and M. Odersky (1991). Building visual language parsers. In: (eds.), CHI '91, pp. 105–112.Google Scholar
  20. Kainz, W., M. Egenhofer, and I. Greasley (1993). Modelling spatial relations and operations with partially ordered sets. International Journal of Geographical Information Systems 7(3): 215–229.Google Scholar
  21. Khoshafian, S., and R. Abnous (1995). Object Orientation: Concepts, Analysis and Design, Languages, Databases, Graphical User Interfaces, Standards. New York, NY, John Wiley & Sons.Google Scholar
  22. Khoshafian, S. and A. Baker (1996). Multimedia and Imaging Databases. San Francisco, CA, Morgan Kaufmann Publishers, Inc.Google Scholar
  23. Khoshafian, S. and G. Copeland (1986). Object identity. SIGPLAN Notices 21: 406–416.Google Scholar
  24. Kim, W., Ed. (1995). Modern Database Systems: The Object Model, Interoperability, and Beyond. New York, NY, ACM Press.Google Scholar
  25. Kim, W., J. Banerjee, H-T. Chou, J. Garza, and D. Woelk (1987). Composite object support in an object-oriented database system, OOPSLA'87 Proceedings, Special Issue of SIGPLAN Notices 22(12): 118–125.Google Scholar
  26. Langran, G. (1992). Time in Geographic Information Systems. Bristol, PA, Taylor & Francis Inc.Google Scholar
  27. Laurini, R. and D. Thompson (1992). Fundamentals of Spatial Information Systems. London, UK, Academic Press.Google Scholar
  28. Peuquet, D. (1994). It's about time: a conceptual framework for the representation of temporal dynamics in geographic information systems. Annals of the Association ofAmerican Geographers 84(3): 441–461.Google Scholar
  29. Raper, J. and D. Livingstone (1995). Development of a geomorphological spatial model using object-oriented design. International Journal of Geographical Information Systems 9(4): 359–383.Google Scholar
  30. Schiel, U. (1989). Abstractions in semantic networks: axiom schemata for generalization. SIGART Newsletter 107: 25–26.Google Scholar
  31. Shoham, Y. (1988). Reasoning about Change. Cambridge, MA, The MIT Press.Google Scholar
  32. Sleezer, A. (1994). Direct Manipulation of Temporally Constrained Activities for Geographic Modelling. Master's Thesis, Department of Surveying Engineering. Orono, ME, University of Maine.Google Scholar
  33. Smith, B. (1995). On drawing lines on a map. In: A. Frank and W. Kuhn (eds.), COSIT '95, Semmering, Austria, Springer-Verlag, Berlin, pp. 475–484.Google Scholar
  34. Smith, B. (1996). On the Origin of Objects. Cambridge, MA, The MIT Press.Google Scholar
  35. Smith, J. and D. Smith (1977). Database abstractions: aggregation. Communications of the ACM 20(6): 405–413.Google Scholar
  36. Worboys, M. (1994). Object-oriented approaches to geo-referenced information. International Journal of Geographical Information Systems 8(4): 385–399.Google Scholar
  37. Xu, J. and R. Lathrop (1995). Improving simulation accuracy of spread phenomenon in a raster-based geographic information system. International Journal of Geographical Information Systems 9(2): 153–168.Google Scholar
  38. Yuan, M. (1994). Wildfire conceptual modeling for building GIS space-time models. Proceedings of GISILIS '94 Phoenix, AZ, pp. 860–869.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1997

Authors and Affiliations

  • Kathleen Homsby
    • 1
    • 2
  • Max J. Egenhofer
    • 1
    • 2
  1. 1.National Center for Geographic Information and AnalysisUniversity of MaineOronoUSA
  2. 2.Department of Spatial Information Science and EngineeringUniversity of MaineOronoUSA

Personalised recommendations