IDEAS home Printed from https://ideas.repec.org/a/sae/envira/v23y1991i10p1483-1499.html
   My bibliography  Save this article

Geographic Information Abstractions: Conceptual Clarity for Geographic Modeling

Author

Listed:
  • T L Nyerges

    (Department of Geography, University of Washington, Seattle, WA 98195, USA)

Abstract

Just as we abstract our reality to make life intellectually manageable, we must create abstractions when we build models of geographic structure and process. Geographic information abstractions with aspects of theme, time, and space can be used to provide a comprehensive description of geographic reality in a geographic information system (GIS): In the context of geographic modeling a geographic information abstraction is defined as a simultaneous focus on important characteristics of geographic content, structure, and process while temporarily suppressing certain details—rather than elimination or deletion of detail. Geographic information abstractions can be used in a database design process to develop a more realistic description of reality in the form of a database model. The geographic information abstraction types are: classification, generalization, aggregation, and association. They are used to structure a descriptive GIS database model by using an example from urban transportation. The embedding of a practically adequate descriptive database model in explanatory and predictive models of urban change is discussed.

Suggested Citation

  • T L Nyerges, 1991. "Geographic Information Abstractions: Conceptual Clarity for Geographic Modeling," Environment and Planning A, , vol. 23(10), pages 1483-1499, October.
    • Handle: RePEc:sae:envira:v:23:y:1991:i:10:p:1483-1499
    DOI: 10.1068/a231483
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1068/a231483
    Download Restriction: no
    File URL: https://libkey.io/10.1068/a231483?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Arthur M. Geoffrion, 1987. "An Introduction to Structured Modeling," Management Science, INFORMS, vol. 33(5), pages 547-588, May.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Kaushal Chari, 2002. "Model Composition Using Filter Spaces," Information Systems Research, INFORMS, vol. 13(1), pages 15-35, March.
    2. Gordon P. Wright & Alok R. Chaturvedi & Radha V. Mookerjee & Susan Garrod, 1998. "Integrated Modeling Environments in Organizations: An Empirical Study," Information Systems Research, INFORMS, vol. 9(1), pages 64-84, March.
    3. Srinivasan, Ananth & Sundaram, David, 2000. "An object relational approach for the design of decision support systems," European Journal of Operational Research, Elsevier, vol. 127(3), pages 594-610, December.
    4. Mentzas, Gregory N., 1996. "Team coordination in decision support projects," European Journal of Operational Research, Elsevier, vol. 89(1), pages 70-85, February.
    5. Amit V. Deokar & Omar F. El-Gayar, 2011. "Decision-enabled dynamic process management for networked enterprises," Information Systems Frontiers, Springer, vol. 13(5), pages 655-668, November.
    6. Huh, Soon-Young & Kim, Hyung-Min & Chung, Q. B., 1999. "Framework for change notification and view synchronization in distributed model management systems," Omega, Elsevier, vol. 27(4), pages 431-443, August.
    7. Andronico, Alfio & Cossa, Laura & Gagliardi, Marco & Spera, Cosimo, 1995. "A structured model to manage a large number of transactions," European Journal of Operational Research, Elsevier, vol. 86(3), pages 402-421, November.
    8. Binbasioglu, Meral, 1995. "Key features for model building decision support systems," European Journal of Operational Research, Elsevier, vol. 82(3), pages 422-437, May.
    9. Tsai, Yao-Chuan, 2001. "Comparative analysis of model management and relational database management," Omega, Elsevier, vol. 29(2), pages 157-170, April.
    10. Steiger, David M. & Sharda, Ramesh, 1996. "Analyzing mathematical models with inductive learning networks," European Journal of Operational Research, Elsevier, vol. 93(2), pages 387-401, September.
    11. Ruth Schwartz & Frederic Murphy, 1996. "Organizing a Model Base of Linear Programming Models Using Analogical Processes," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 5(4), pages 217-228, December.
    12. A. Atamtürk & E. L. Johnson & J. T. Linderoth & M. W. P. Savelsbergh, 2000. "A Relational Modeling System for Linear and Integer Programming," Operations Research, INFORMS, vol. 48(6), pages 846-857, December.
    13. Chaturvedi, Alok & Mehta, Shailendra & Dolk, Daniel & Ayer, Rick, 2005. "Agent-based simulation for computational experimentation: Developing an artificial labor market," European Journal of Operational Research, Elsevier, vol. 166(3), pages 694-716, November.
    14. Gu, Jifa & Tang, Xijin, 2005. "Meta-synthesis approach to complex system modeling," European Journal of Operational Research, Elsevier, vol. 166(3), pages 597-614, November.
    15. Craig A. Tovey, 2002. "Tutorial on Computational Complexity," Interfaces, INFORMS, vol. 32(3), pages 30-61, June.
    16. Dolk, Daniel R., 2000. "Integrated model management in the data warehouse era," European Journal of Operational Research, Elsevier, vol. 122(2), pages 199-218, April.
    17. Makowski, Marek, 2005. "A structured modeling technology," European Journal of Operational Research, Elsevier, vol. 166(3), pages 615-648, November.
    18. Gelman, Irit Askira, 2005. "Addressing time-scale differences among decision-makers through model abstractions," European Journal of Operational Research, Elsevier, vol. 160(2), pages 325-335, January.
    19. Therani Madhusudan, 2007. "A web services framework for distributed model management," Information Systems Frontiers, Springer, vol. 9(1), pages 9-27, March.
    20. Pedro Gazmuri & Sergio Maturana, 2001. "Developing and Implementing a Production Planning DSS for CTI Using Structured Modeling," Interfaces, INFORMS, vol. 31(4), pages 22-36, August.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:sae:envira:v:23:y:1991:i:10:p:1483-1499. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: SAGE Publications (email available below). General contact details of provider: .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.