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The Problem of Aggregation and Distance for Analyses of Accessibility and Access Opportunity in Location-Allocation Models

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  • L Bach

    (Department of Urban and Regional Planning, University of Dortmund, D-4600 Dortmund 50, FRG)

Abstract

The acceptability of information stemming from analyses of accessibility and access opportunity for social, educational, and cultural infrastructure facilities largely depends on two factors: exactness and efficiency. Both of these factors are influenced by the data bases available for the analyses. This paper will focus on the problem of data requirements for spatial distributions of demand as well as on data requirements for spatial distances with respect to the exactness of the results of analyses and on the efficiency of preparing analyses. The effects of different levels of aggregation and of different types of distance measures are investigated.

Suggested Citation

  • L Bach, 1981. "The Problem of Aggregation and Distance for Analyses of Accessibility and Access Opportunity in Location-Allocation Models," Environment and Planning A, , vol. 13(8), pages 955-978, August.
    • Handle: RePEc:sae:envira:v:13:y:1981:i:8:p:955-978
    DOI: 10.1068/a130955
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    References listed on IDEAS

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    1. Richard C. Larson & Keith A. Stevenson, 1972. "On Insensitivities in Urban Redistricting and Facility Location," Operations Research, INFORMS, vol. 20(3), pages 595-612, June.
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    Cited by:

    1. Müller, Sven & Tscharaktschiew, Stefan & Haase, Knut, 2008. "Travel-to-school mode choice modelling and patterns of school choice in urban areas," Journal of Transport Geography, Elsevier, vol. 16(5), pages 342-357.
    2. R. Francis & T. Lowe & M. Rayco & A. Tamir, 2009. "Aggregation error for location models: survey and analysis," Annals of Operations Research, Springer, vol. 167(1), pages 171-208, March.
    3. Tira, Maurizio & Tiboni, Michela & Badiani, Barbara, 2002. "High speed/high capacity railway and regional development - evaluation of effects on spatial accessibility," ERSA conference papers ersa02p362, European Regional Science Association.
    4. Carling, Kenneth & Han, Mengjie & Håkansson, Johan & Rebreyend, Pascal, 2012. "Distance measure and the p-median problem in rural areas," HUI Working Papers 78, HUI Research.
    5. Kiril Stanilov, 2003. "Accessibility and Land Use: The Case of Suburban Seattle, 1960-1990," Regional Studies, Taylor & Francis Journals, vol. 37(8), pages 783-794.
    6. Kenneth Carling & Mengjie Han & Johan Håkansson & Pascal Rebreyend, 2015. "Distance measure and the $$p$$ p -median problem in rural areas," Annals of Operations Research, Springer, vol. 226(1), pages 89-99, March.
    7. Irawan, Chandra Ade & Salhi, Said & Scaparra, Maria Paola, 2014. "An adaptive multiphase approach for large unconditional and conditional p-median problems," European Journal of Operational Research, Elsevier, vol. 237(2), pages 590-605.
    8. Yuhong Tian & C. Y. Jim & Yiqing Liu, 2017. "Using a Spatial Interaction Model to Assess the Accessibility of District Parks in Hong Kong," Sustainability, MDPI, vol. 9(11), pages 1-14, October.
    9. Kenneth Carling & Mengjie Han & Johan Håkansson, 2012. "Does Euclidean distance work well when the p-median model is applied in rural areas?," Annals of Operations Research, Springer, vol. 201(1), pages 83-97, December.
    10. Tamás Dusek, 2005. "The modifiable areal unit problem in regional economics," ERSA conference papers ersa05p357, European Regional Science Association.

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