An exact statistical method for analyzing co-location on a street network and its computational implementation

Wataru Morioka, Atsuyuki Okabe, Mei Po Kwan, Sara L. McLafferty

Research output: Contribution to journalArticlepeer-review

Abstract

In many central districts in cities across the world, different types of stores form clusters resulting from the benefits of spatial agglomeration. To precisely analyze co-location relationships in a micro-scale space, this study develops a new statistical method by addressing the limitations of the ordinary cross K function method. The objectives of this paper are, first, to formulate an exact statistical method for analyzing co-location along streets in a central district constrained by a street network; second, to implement this statistical method in computational procedures. Third, this method is extended to the analysis of repulsive-location, i.e. phenomena of stores locating repulsively among different types of stores. Fourth, the paper shows a graph-theoretic diagram illustrating the spatial structure of stores in a central district consisting of bilateral, unilateral co-location and repulsive-location. Last, the proposed method is applied to eight different types of stores in a trendy district in Tokyo. The results show that the method is useful for revealing the spatial structure consisting of co-location and repulsive-location in the central district.

Original languageEnglish (US)
JournalInternational Journal of Geographical Information Science
DOIs
StateAccepted/In press - 2021

Keywords

  • economic geography
  • GIS
  • Network spatial analysis
  • point pattern analysis
  • Ripley’s K function

ASJC Scopus subject areas

  • Information Systems
  • Geography, Planning and Development
  • Library and Information Sciences

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