Network dual K function: Exact statistical methods for analyzing co-location on street networks

Morioka, Wataru

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https://hdl.handle.net/2142/121228 Copy

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.

Graduation Semester

2023-08

Type of Resource

Thesis

Handle URL

https://hdl.handle.net/2142/121228

Copyright and License Information

Copyright 2023 Wataru Morioka

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