A Clustering Refinement Approach for Revealing Urban Spatial Structure from Smart Card Data
Source abstract
Abstract
Facilitated by rapid development of the data-intensive techniques together with communication and sensing technology, we can take advantage of smart card data collected through Automatic Fare Collection (AFC) systems to establish connections between public transit and urban spatial structure. In this paper, with a case study on Shenzhen metro system in China, we investigate the agglomeration pattern of passenger flow among subway stations. Specifically, leveraging inbound and outbound passenger flows at subway stations, we propose a clustering refinement approach based on cluster member stability among multiple clusterings produced by isomorphic or heterogeneous clusterers. Furthermore, we validate and elaborate five clusters of subway stations in terms of regional functionality and urban planning by comparing station clusters with reference to government planning policies and regulations of Shenzhen city. Additionally, outlier stations with ambiguous functionalities are detected using proposed clustering refinement framework.
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Research context
OpenAlex topics: Human Mobility and Location-Based Analysis · Transportation Planning and Optimization · Urban Transport and Accessibility
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
China Electronics Technology Group Corporation 38th Research Institute, Hefei 230088, China
Anhui Province Key Laboratory for Emergency Information Technology of Public Safety, Hefei 230088, China
Centre for Systems Informatics Engineering, City University of Hong Kong, Hong Kong 999077, Hong Kong
School of Data Science, City University of Hong Kong, Hong Kong 999077, Hong Kong
Grado Department of Industrial and Systems Engineering, Virginia Polytechnic Institute and State University, 225 Durham Hall, 1145 Perry Street, Blacksburg, VA 24061, USA
Funding
National Key Research and Development Program of China · National Natural Science Foundation of China · Major Research Program of the National Natural Science Foundation of China · Anhui Provincial Natural Science Foundation
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