Advertisement

GeoInformatica

, Volume 8, Issue 3, pp 211–235 | Cite as

Development of a Temporal Extension to Query Travel Behavior Time Paths Using an Object-Oriented GIS

  • Ali Frihida
  • Danielle J. Marceau
  • Marius Thériault
Article

Abstract

An essential requirement to better understand activity-based travel behavior (ABTB) at the disaggregate level is the development of a spatio-temporal model able to support queries related to activities of individuals or groups of individuals. This paper describes the development and implementation of a temporal extension to a geographic information system (GIS) object-oriented model for the modeling of the time path and the retrieval of its event chaining. In this approach, time path is formulated as a totally time ordered set composed by activity events and trip events, themselves organized into time ordered sets. As sets, the time path and its components can be searched using their respective indexes. A series of methods were built that implement temporal predicates as an interface to temporally query the database. A set of positional operator methods were also designed that transform temporal topological queries into retrieval functions based on set ordering indices. Taken together, the temporal predicates and the positional operator methods define a temporal query extension that meets the retrieval needs of an ABTB database.

temporal GIS disaggregate activity-based travel behavior space-time path time topology temporal query object-oriented paradigm 
This is a preview of subscription content, log in to check access.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    A. Adamu, S. Khaddaj, and M. Morad. “A framework for tracking the evolution of objects in GIS”, in D.B. Kidnerand G. Higgs (Eds. ), Proceedings of the 9th Annual Conference GIS Research UK, 18–20 April, University of Glamorgan: Wales, 304–310, 2001.Google Scholar
  2. 2.
    J.F. Alien. “Towards a general theory of action and time,” Artificial Intelligence, Vol. 23:123–154, 1984.Google Scholar
  3. 3.
    K. AI–Taha, R.T. Snodgrass, and M.D. Soo. “The Tempis project, bibliography on spatiotemporal databases,” Department of Computer Science, University of Arizona, Tempis Technical Report, No. 44, 1993.Google Scholar
  4. 4.
    L. Becker, A. Voigtmann, and K.H. Klaus. “Temporal support for geo–data in object–oriented databases,” 7th International Conference and Workshop on Database and Expert System Application, DEXA'96, September, Zurich, Switzerland, 1996.Google Scholar
  5. 5.
    W. Boggs and M. Boggs. Mastering UML with Rational Rose. Sybex: San Francisco, CA, 1999.Google Scholar
  6. 6.
    M.H. Bohlen. “Temporal database system implementation,” Sigmod Record, Vol. 24(4):53–60, 1994.Google Scholar
  7. 7.
    D.W. Brown. An Introduction to Object–Oriented Analysis; Objects and UML in Plain English. John Wiley and Sons, p. 668, 2002.Google Scholar
  8. 8.
    J.–P. Cheylan and S. Lardon. “Toward a conceptual model for the analysis of spatio–temporal processes,” in A.U. Frank and I. Campari (Eds.), Spatial Information Theory, Springer–Verlag: Berlin, pp. 158–176, 1993.Google Scholar
  9. 9.
    C. Claramunt and B. Jiang. “A representation of relationships in temporal spaces,” in P. Atkinson and D. Martin (Eds.), GIS and Geocomputation, Innovations in GIS 7, Taylor and Francis: London, 2000.Google Scholar
  10. 10.
    C. Claramunt and M. Theriault. “Managing time in GIS: An event–oriented approach,” in J. Clifford and A. Tuzhilin (Eds.), Recent Advances in Temporal Databases, Proceedings of the International Workshop on Temporal Databases, Zurich, Switzerland, 17–18 September, Springer: Berlin, pp. 23–42, 1995.Google Scholar
  11. 11.
    O.–J. Dahl and K. Nygaard. “SIMULA–an ALGOL–based simulation language,” Communications of the ACM, Vol. 9:671–678,1966.Google Scholar
  12. 12.
    O.–J. Dahl, B. Kyhrhoug, and K. Nygaard. The Simula 67 Common Based Language. Norvegian Computer Center: Oslo. Publication S22, 1970.Google Scholar
  13. 13.
    S. Doherty and E. Miller. “A computerized household activity scheduling survey,” Transportation, Vol. 27(l):75–97,2000.Google Scholar
  14. 14.
    M.J. Egenhofer and K.K. AI–Taha. “Reasonning about gradual changes of topological relationships,” Proceedings of tile Conference on Theories and Methods on Spatio–Temporal Reasonning, 196–219, 1992.Google Scholar
  15. 15.
    M. Erwig, R.H. Guting, M. Schneider, and M. Vazirgiannis. “Spatio–temporal data types: An approach to modelling and quering moving objects in databases,” Geoinformatica, Vol. 3(3):269–296, 1999.Google Scholar
  16. 16.
    A. Frihida, D.J. Marceau, and M. Theriault. “Spatio–temporal object–oriented data mode for disaggregate travel behavior,” Transactions in GIS, Vol. 6(3):277–294, 2002.Google Scholar
  17. 17.
    T. Garling, T. Kalen, J. Romanus, and M. Selart. “Computer simulation of household activity scheduling,” Environment and Planning A, Vol. 30:665–679, 1998.Google Scholar
  18. 18.
    T. Garling, M.P. Kwan, and R.G. Golledge. “Computational–process modelling of household activity scheduling.” Transportation Research, Vol. 28B(5):355–364, 1994.Google Scholar
  19. 19.
    R.G. Golledge, M.P. Kwan, and T. Garling. “Computational process modeling of household travel decisions using a geographical information system,” Papers in Regional Science, Vol. 73(2):99–117, 1994.Google Scholar
  20. 20.
    S. Greaves and P. Stopher. “A synthesis of GIS and activity–based travel forecasting,” Geographical Systems, Vol. 5:59–89,1998.Google Scholar
  21. 21.
    T. Hagerstrand. “What about people in regional science?” Papers of the Regional Science Association, Vol. 4:7–21,1970.Google Scholar
  22. 22.
    K. Hornsby and M.J. Egenhofer. “Identity–based change: A foundation for spatio–temporal knowledge representation,” International Journal of Geographical Information Science, Vol. 14(3):207–224, 2000.Google Scholar
  23. 23.
    C.S. Jansen, J. Clifford, S.K. Gadia, and R.T. Snodgrass. “A glossary of temporal database concepts,” Sigmod Record, Vol. 21(3):35–53, 1992.Google Scholar
  24. 24.
    C.S. Jensen and R.T. Snodgrass. “Temporal data management, institute of information systems,” TimeCenter, Zurich, Technical Report TR–17, 1997.Google Scholar
  25. 25.
    G. Jornier, M.A. Peerbocus, and J.B. Huntzinger. “Visualizing the evolution of spatiotemporal objects,” in P. Foru and J. He (Eds.), Proceedings of the Spatial Data Handling Conference, 10–12 August, Beijing, 7a.l3–7a.25,2000.Google Scholar
  26. 26.
    M. Kwan. “Space–time and integral measures of individual accessibility: A comparative analysis using a point–based framework,” Geographical Analysis, Vol. 30(3):191–216, 1998.Google Scholar
  27. 27.
    M. Kwan. “Gisicas: An activity–based travel decision support system using a GIS interfaced computational– process model,” in D. Ettema and H. Timmermans (Eds.), Activity Based Approaches to Travel Analysis. Elsevier Science Ltd: UK, pp. 263–282, 1999.Google Scholar
  28. 28.
    M. Kwan and X. Hong. “Network based constraints oriented choice set formation using gis,” Geographical Systems, Vol. 5:139–162,1998.Google Scholar
  29. 29.
    B. Lenntorp. “A time–geographical simulation of activity programs,” in T. Carlstein, D. Parkes, and N. Thrift (Eds.), Timing Space and Spacing Time, Vol. 2: Human Activity and Time Geography, Edward Amold Ltd: London, UK, 1978.Google Scholar
  30. 30.
    J. Makin, R.G. Healey, and S. Dowers. “Simulation modelling with object–oriented GIS: A prototype application to time geography of shopping behaviour,” Geographical Systems, Vol. 4(4):397–429, 1997.Google Scholar
  31. 31.
    M.G. McNally. “Activity based forecasting models integrating gis,” Geographical Systems, Vol. 5:163–187,1998.Google Scholar
  32. 32.
    H.J. Miller. “Modelling accessibility using space–time prism concepts within geographical information systems,” International Journal of Geographical Information Science, Vol. 5(3):287–301, 1991.Google Scholar
  33. 33.
    H.J. Miller. “Measuring space–time accessibility benefits within transportation networks: Basic theory and computational procedures,” Geographical Analysis, Vol. 31(2):187–212, 1999.Google Scholar
  34. 34.
    D. O'Sullivan, A. Morrisson, and J. Shearer. “Using desktop GIS for the investigation of accessibility by public transport: An isochrone approach,” International Journal of Geographical Information Science, Vol. 14(l):85–104,2000.Google Scholar
  35. 35.
    D.J. Peuquet. “It about time: A conceptual framework for the representation of temporal dynamics in geographic information systems,” Annals of the Association of American Geographers, Vol. 84(3):441–461,1994.Google Scholar
  36. 36.
    D.J. Peuquet and N. Duan. “An event–based spatiotemporal data model (ESTDM) for temporal analysis of geographical data,” International Journal of Geographical Information Systems, Vol. 9(l):7–24, 1995.Google Scholar
  37. 37.
    R.T. Snodgrass. Developing Time–Oriented Database Application in SQL. Morgan Kaufman Publishers: San Francisco, CA, 2000.Google Scholar
  38. 38.
    M. Theriault, D. Leroux, and M.H. Vandersmissen. “Modelling travel route and time within GIS: Its use for planning,” in A. Bargiela and E. Kerckhoffs (Eds.), ESS'98, Tile 10th European Simulation Symposium Society for Computer Simulation International.Netherlands, October 26–28, 402–407, 1998.Google Scholar
  39. 39.
    M. Theriault and C. Claramunt. “La representation du temps et des processus dans les SIG: Une necessite pour la recherche interdisciplinaire,” Revue Internationale de Geomatique, Vol. 9(l):67–99, 1999.Google Scholar
  40. 40.
    V.J. Tsotras and A. Kumar. “Temporal database bibliography update,” Sigmod Record, Vol. 25(l):41–51, 1996.Google Scholar
  41. 41.
    W.G.M. Van der Knaap. “Analysis of time–space activity patterns in tourist recreation complexes, a gis oriented methodology,” in D. Ettema and H. Timmermans (Eds.), Activity Based Approaches to Travel Analysis. Elsevier Science Ltd: UK, pp. 283–311, 1999.Google Scholar
  42. 42.
    M. Wachowicz. Object–Oriented Design for Temporal Databases. Taylor and Francis: London, UK, 1999.Google Scholar
  43. 43.
    D. Wang and T. Cheng. “A spatio–temporal data model for activity–based transport modeling,”International Journal of Geographical Information Science, Vol. 15:561–585, 2001.Google Scholar

Copyright information

© Kluwer Academic Publishers 2004

Authors and Affiliations

  • Ali Frihida
    • 1
  • Danielle J. Marceau
    • 1
  • Marius Thériault
    • 2
  1. 1.Geocomputing Laboratory, Department of GeographyUniversity of MontrealMontreal, QuebecCanada
  2. 2.Centre de Recherche en Aménagement et DéveloppementUniversitéLaval, QuebecCanada

Personalised recommendations

Cite article

Buy options