Transit Travel Community Detection and Evolutionary Analysis: A Case Study of Shenzhen

Jingjing Yan, Zhengdong Huang (), Tianhong Zhao, Ying Zhang and Fei Chang
Additional contact information
Jingjing Yan: Research Institute for Smart Cities, School of Architecture and Urban Planning, Shenzhen University, Shenzhen 518060, China
Zhengdong Huang: Research Institute for Smart Cities, School of Architecture and Urban Planning, Shenzhen University, Shenzhen 518060, China
Tianhong Zhao: Research Institute for Smart Cities, School of Architecture and Urban Planning, Shenzhen University, Shenzhen 518060, China
Ying Zhang: Research Institute for Smart Cities, School of Architecture and Urban Planning, Shenzhen University, Shenzhen 518060, China
Fei Chang: Research Institute for Smart Cities, School of Architecture and Urban Planning, Shenzhen University, Shenzhen 518060, China

Sustainability, 2023, vol. 15, issue 7, 1-17

Abstract: Community detection can reveal specific urban spatial structures related to human activities, and is achieved using mobility data from various sources. In the existing research, less attention has been devoted to communities related to urban transit travel. As public transit is a key component of the urban transport system, it is important to understand how transit communities are organized and how they evolve. This research proposes an approach to urban transit travel community detection using transit travel data and examines how the communities have evolved over time. The results in Shenzhen from 2015 to 2017 showed that the transit travel network had an obvious community structure, and the components (TAZs in this case) of the communities changed over time. During the three years, the western part of Shenzhen experienced more component changes on weekdays, and the central part of the city underwent more component changes on weekdays. In addition, the transit travel communities had a significant coupling relationship with urban administrative divisions. Exploring transit travel communities provides insight for improving public transit systems and enriches the research genealogy of urban spatial structure.

Keywords: travel network of transit; community structure; transit smart card; dynamic evolution; Shenzhen (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2071-1050/15/7/5900/pdf (application/pdf)
https://www.mdpi.com/2071-1050/15/7/5900/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:15:y:2023:i:7:p:5900-:d:1110036

Access Statistics for this article

Sustainability is currently edited by Ms. Alexandra Wu

More articles in Sustainability from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().