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Spatial representation in the social interaction potential metric: an analysis of scale and parameter sensitivity

Author

Listed:
  • Xiao Li

    (University of Utah)

  • Steven Farber

    (University of Toronto Scarborough)

Abstract

The social interaction potential (SIP) metric measures urban structural constraints on social interaction opportunities of a metropolitan region based on the time geographic concept of joint accessibility. Previous implementations of the metric used an interaction surface based on census tracts and the locations of their centroids. This has been shown to be a shortcoming, as the metric strongly depends on the scale of the zoning system in the region, making it difficult to compare the SIP metric between metropolitan regions. This research explores the role of spatial representation in the SIP metric and identifies a suitable grid-based representation that allows for comparison between regions while retaining cost-effectiveness with respect to computational burden. We also report on findings from an extensive sensitivity analysis investigating the SIP metric’s input parameters such as a travel flow congestion factor and the length of the allowable time budget for social activities. The results provide new insights on the role of the modifiable areal unit problem in the computation of time geographic measures of accessibility.

Suggested Citation

  • Xiao Li & Steven Farber, 2016. "Spatial representation in the social interaction potential metric: an analysis of scale and parameter sensitivity," Journal of Geographical Systems, Springer, vol. 18(4), pages 331-357, October.
    • Handle: RePEc:kap:jgeosy:v:18:y:2016:i:4:d:10.1007_s10109-016-0238-6
    DOI: 10.1007/s10109-016-0238-6
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    References listed on IDEAS

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    1. Farber, Steven & Li, Xiao, 2013. "Urban sprawl and social interaction potential: an empirical analysis of large metropolitan regions in the United States," Journal of Transport Geography, Elsevier, vol. 31(C), pages 267-277.
    2. Jae Yong Lee & Mei‐Po Kwan, 2011. "Visualisation Of Socio‐Spatial Isolation Based On Human Activity Patterns And Social Networks In Space‐Time," Tijdschrift voor Economische en Sociale Geografie, Royal Dutch Geographical Society KNAG, vol. 102(4), pages 468-485, September.
    3. Farber, Steven & O'Kelly, Morton & Miller, Harvey J. & Neutens, Tijs, 2015. "Measuring segregation using patterns of daily travel behavior: A social interaction based model of exposure," Journal of Transport Geography, Elsevier, vol. 49(C), pages 26-38.
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    7. S Openshaw, 1977. "Optimal Zoning Systems for Spatial Interaction Models," Environment and Planning A, , vol. 9(2), pages 169-184, February.
    8. Farber, Steven & Páez, Antonio, 2011. "Running to stay in place: the time-use implications of automobile oriented land-use and travel," Journal of Transport Geography, Elsevier, vol. 19(4), pages 782-793.
    9. Farber, Steven & Páez, Antonio, 2009. "My car, my friends, and me: a preliminary analysis of automobility and social activity participation," Journal of Transport Geography, Elsevier, vol. 17(3), pages 216-225.
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    Cited by:

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    2. Arnaud Adam & Jean-Charles Delvenne & Isabelle Thomas, 2018. "Detecting communities with the multi-scale Louvain method: robustness test on the metropolitan area of Brussels," Journal of Geographical Systems, Springer, vol. 20(4), pages 363-386, October.

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    More about this item

    Keywords

    Social interaction potential; Time geography; Joint accessibility; MAUP; Sensitivity analyses;
    All these keywords.

    JEL classification:

    • R41 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics - - - Transportation: Demand, Supply, and Congestion; Travel Time; Safety and Accidents; Transportation Noise

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