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Discovering the evolution of urban structure using smart card data: The case of London

Zhang, Y; Marshall, S; Cao, M; Manley, E; Chen, H; (2021) Discovering the evolution of urban structure using smart card data: The case of London. Cities , 112 , Article 103157. 10.1016/j.cities.2021.103157. (In press).

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Abstract

Cities are continuing to develop and are grappling with uncertainties and difficulties as they do so. It has therefore become essential to understand how urban spatial structure changes, particularly with the increasingly available sources of ‘big data’. However, most studies mainly focus on delineating the spatial structure and its variations. Only a few have investigated the incentives behind the movement dynamics. To identify the urban structure of Greater London and uncover how it co-evolves with socio-economic and spatial policy factors, this study applies network community detection, using smart card data derived from the years 2013, 2015 and 2017, respectively. Our findings show that, firstly, between 2013 and 2017, London's urban structure moved towards a more polycentric and compact pattern. Secondly, it is found that Greater London can be clustered into five communities based on the characteristics of passengers' travel patterns. Thirdly, the dynamics of structural change in different urban clusters differ both in terms of changing intensity and potential motivation. In addition to spatial impact and spatial strategic policies, our results show that employment density and residential densities are also the main indicators that affected the interaction between Londoners in different areas on various levels.

Type: Article
Title: Discovering the evolution of urban structure using smart card data: The case of London
DOI: 10.1016/j.cities.2021.103157
Publisher version: https://doi.org/10.1016/j.cities.2021.103157
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher's terms and conditions.
Keywords: Urban structure, Big data analytics, Urban planning, Community detection, Network analysis, London
UCL classification: UCL
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of the Built Environment
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of the Built Environment > Centre for Advanced Spatial Analysis
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of the Built Environment > The Bartlett School of Planning
URI: https://discovery.ucl.ac.uk/id/eprint/10124045
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