Discovery of statistically significant regional co-location patterns on urban road networks. Issue 4 (3rd April 2022)

• Record Type: Journal Article
• Authors: Liu, Wenkai; Liu, Qiliang; Deng, Min; Cai, Jiannan; Yang, Jie
• Is Part Of: International journal of geographical information science. Volume 36:Issue 4(2022)
• Page Start: 749
• Page End: 772
• Publication Date: 2022-04-03
• Subjects: Combinational optimization -- regional co-location pattern -- road network -- significance test; Geography -- Data processing -- Periodicals; Information storage and retrieval systems -- Periodicals; Géomatique -- Périodiques; Systèmes d'information -- Périodiques; 910.285
• DOI: 10.1080/13658816.2021.1981335
• Languages: English
• ISSNs: 1365-8816

Abstract

ABSTRACT: Detecting regional co-location patterns on urban road networks is challenging because it is computationally prohibitive to search all potential co-location patterns and their localities, and effective statistical methods for evaluating the prevalence of regional co-location patterns are lacking. To overcome these challenges, this study developed an adaptive method for detecting network-constrained regional co-location patterns. Specifically, an alternate prevalence measure of regional co-location patterns was defined based on the likelihood ratio statistic. A network-constrained k -nearest neighbor method was used to construct instances of candidate co-location patterns, and a heuristic two-phase expansion method was proposed to identify candidate localities of regional co-location patterns. The statistical significance of regional co-location patterns was evaluated using a Monte Carlo simulation. Experiments using extensive simulated datasets showed that our method was superior to three state-of-the-art methods. The proposed method was also applied to a Beijing points of interest (POI) dataset. The identified regional POI co-location patterns could support a better understanding of the spatial organization of urban functions and may be useful for facilitating urban planning.