Network dual K function: Exact statistical methods for analyzing co-location on street networks
Morioka, Wataru
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Permalink
https://hdl.handle.net/2142/121228
Description
Title
Network dual K function: Exact statistical methods for analyzing co-location on street networks
Author(s)
Morioka, Wataru
Issue Date
2023-07-10
Director of Research (if dissertation) or Advisor (if thesis)
Kwan, Mei-Po
Doctoral Committee Chair(s)
Kwan, Mei-Po
Committee Member(s)
McLafferty, Sara
Cidell, Julie
Kolak, Marynia
Department of Study
Geography & GIS
Discipline
Geography
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
Ph.D.
Degree Level
Dissertation
Keyword(s)
network spatial analysis, point pattern analysis, GIS
Abstract
In many central districts in cities across the world, different types of retail outlets and service firms form clusters (i.e., co-location) for benefits of spatial agglomeration. To analyze such spatial phenomena, the cross K function has been widely used. However, this method and other existing methods are likely to be unsuitable for analyzing co-locations in a micro-scale space due to some limitations. To precisely analyze the micro-scale co-location, this dissertation develops a new statistical measure named network dual K function. Compared to the ordinary cross K function, the proposed method has distinctive features such as assuming network-constrained space and using an exact statistical formula for a test. This dissertation proposes a set of three methods of network dual K function: global, local, and incremental methods. Each method corresponds with Chapters 2, 3, and 4 of this dissertation. The proposed methods are applied to various types of stores in trendy districts in Tokyo to demonstrate the usefulness of the methods for studies on economic geography, and to improve the understanding of urban agglomeration. In addition, this research project highlights the significance of conducting network spatial analysis.
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