Understanding the interplay between bus, metro, and cab ridership dynamics in Shenzhen, China

Mengxue Yue, Chaogui Kang, Clio Andris, Kun Qin, Yu Liu, Qingxiang Meng

Research output: Contribution to journalArticle

5 Citations (Scopus)

Abstract

The most common mass transit modes in metropolitan cities include buses, subways, and taxicabs, each of which contribute to an interconnected complex network that delivers urban dwellers to their destinations. Understanding the intertwined usages of these three transit modes at different places and time allows for better sensing of urban mobility and the built environment. In this article, we leverage a comprehensive data collection of bus, metro, and taxicab ridership from Shenzhen, China to unveil the spatio-temporal interplay between different mass transit modes. To achieve this goal, we develop a novel spectral clustering framework that imposes spatio-temporal similarities between mass transit mode usage in urban space and differentiates urban spaces associated with distinct ridership patterns of mass transit modes. Five resulting categories of urban spaces are identified and interpreted with auxiliary knowledge of the city's metro network and land-use functionality. In general, different categorized urban spaces are associated with different accessibility levels (such as high-, medium-, and low-ranked) and different urban functionalities (such as residential, commercial, leisure-dominant, and home–work balanced). The results indicate that different mass transit modes cooperate or compete based on demographic and socioeconomic attributes of the underlying urban environments. Our proposed analytical framework provides a novel and effective way to explore the mass transit system and the functional heterogeneity in cities. It demonstrates great potential for assisting policymakers and municipal managers in optimizing public transportation facility allocation and city-wide daily commuting distribution.

Original languageEnglish (US)
Pages (from-to)855-871
Number of pages17
JournalTransactions in GIS
Volume22
Issue number3
DOIs
StatePublished - Jun 2018

Fingerprint

commuting
analytical framework
accessibility
bus
land use
city
built environment
attribute
socioeconomics
distribution
allocation
public

All Science Journal Classification (ASJC) codes

  • Earth and Planetary Sciences(all)

Cite this

Yue, Mengxue ; Kang, Chaogui ; Andris, Clio ; Qin, Kun ; Liu, Yu ; Meng, Qingxiang. / Understanding the interplay between bus, metro, and cab ridership dynamics in Shenzhen, China. In: Transactions in GIS. 2018 ; Vol. 22, No. 3. pp. 855-871.
@article{47edb0c3605141eeae8cc623d7db32f9,
title = "Understanding the interplay between bus, metro, and cab ridership dynamics in Shenzhen, China",
abstract = "The most common mass transit modes in metropolitan cities include buses, subways, and taxicabs, each of which contribute to an interconnected complex network that delivers urban dwellers to their destinations. Understanding the intertwined usages of these three transit modes at different places and time allows for better sensing of urban mobility and the built environment. In this article, we leverage a comprehensive data collection of bus, metro, and taxicab ridership from Shenzhen, China to unveil the spatio-temporal interplay between different mass transit modes. To achieve this goal, we develop a novel spectral clustering framework that imposes spatio-temporal similarities between mass transit mode usage in urban space and differentiates urban spaces associated with distinct ridership patterns of mass transit modes. Five resulting categories of urban spaces are identified and interpreted with auxiliary knowledge of the city's metro network and land-use functionality. In general, different categorized urban spaces are associated with different accessibility levels (such as high-, medium-, and low-ranked) and different urban functionalities (such as residential, commercial, leisure-dominant, and home–work balanced). The results indicate that different mass transit modes cooperate or compete based on demographic and socioeconomic attributes of the underlying urban environments. Our proposed analytical framework provides a novel and effective way to explore the mass transit system and the functional heterogeneity in cities. It demonstrates great potential for assisting policymakers and municipal managers in optimizing public transportation facility allocation and city-wide daily commuting distribution.",
author = "Mengxue Yue and Chaogui Kang and Clio Andris and Kun Qin and Yu Liu and Qingxiang Meng",
year = "2018",
month = "6",
doi = "10.1111/tgis.12340",
language = "English (US)",
volume = "22",
pages = "855--871",
journal = "Transactions in GIS",
issn = "1361-1682",
publisher = "Wiley-Blackwell",
number = "3",

}

Understanding the interplay between bus, metro, and cab ridership dynamics in Shenzhen, China. / Yue, Mengxue; Kang, Chaogui; Andris, Clio; Qin, Kun; Liu, Yu; Meng, Qingxiang.

In: Transactions in GIS, Vol. 22, No. 3, 06.2018, p. 855-871.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Understanding the interplay between bus, metro, and cab ridership dynamics in Shenzhen, China

AU - Yue, Mengxue

AU - Kang, Chaogui

AU - Andris, Clio

AU - Qin, Kun

AU - Liu, Yu

AU - Meng, Qingxiang

PY - 2018/6

Y1 - 2018/6

N2 - The most common mass transit modes in metropolitan cities include buses, subways, and taxicabs, each of which contribute to an interconnected complex network that delivers urban dwellers to their destinations. Understanding the intertwined usages of these three transit modes at different places and time allows for better sensing of urban mobility and the built environment. In this article, we leverage a comprehensive data collection of bus, metro, and taxicab ridership from Shenzhen, China to unveil the spatio-temporal interplay between different mass transit modes. To achieve this goal, we develop a novel spectral clustering framework that imposes spatio-temporal similarities between mass transit mode usage in urban space and differentiates urban spaces associated with distinct ridership patterns of mass transit modes. Five resulting categories of urban spaces are identified and interpreted with auxiliary knowledge of the city's metro network and land-use functionality. In general, different categorized urban spaces are associated with different accessibility levels (such as high-, medium-, and low-ranked) and different urban functionalities (such as residential, commercial, leisure-dominant, and home–work balanced). The results indicate that different mass transit modes cooperate or compete based on demographic and socioeconomic attributes of the underlying urban environments. Our proposed analytical framework provides a novel and effective way to explore the mass transit system and the functional heterogeneity in cities. It demonstrates great potential for assisting policymakers and municipal managers in optimizing public transportation facility allocation and city-wide daily commuting distribution.

AB - The most common mass transit modes in metropolitan cities include buses, subways, and taxicabs, each of which contribute to an interconnected complex network that delivers urban dwellers to their destinations. Understanding the intertwined usages of these three transit modes at different places and time allows for better sensing of urban mobility and the built environment. In this article, we leverage a comprehensive data collection of bus, metro, and taxicab ridership from Shenzhen, China to unveil the spatio-temporal interplay between different mass transit modes. To achieve this goal, we develop a novel spectral clustering framework that imposes spatio-temporal similarities between mass transit mode usage in urban space and differentiates urban spaces associated with distinct ridership patterns of mass transit modes. Five resulting categories of urban spaces are identified and interpreted with auxiliary knowledge of the city's metro network and land-use functionality. In general, different categorized urban spaces are associated with different accessibility levels (such as high-, medium-, and low-ranked) and different urban functionalities (such as residential, commercial, leisure-dominant, and home–work balanced). The results indicate that different mass transit modes cooperate or compete based on demographic and socioeconomic attributes of the underlying urban environments. Our proposed analytical framework provides a novel and effective way to explore the mass transit system and the functional heterogeneity in cities. It demonstrates great potential for assisting policymakers and municipal managers in optimizing public transportation facility allocation and city-wide daily commuting distribution.

UR - http://www.scopus.com/inward/record.url?scp=85051333651&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85051333651&partnerID=8YFLogxK

U2 - 10.1111/tgis.12340

DO - 10.1111/tgis.12340

M3 - Article

AN - SCOPUS:85051333651

VL - 22

SP - 855

EP - 871

JO - Transactions in GIS

JF - Transactions in GIS

SN - 1361-1682

IS - 3

ER -