Discovering the evolution of urban structure using smart card data: The case of London. (May 2021)

• Record Type: Journal Article
• Authors: Zhang, Yuerong; Marshall, Stephen; Cao, Mengqiu; Manley, Ed; Chen, Huanfa
• Is Part Of: Cities. Volume 112(2021)
• Publication Date: 2021-05
• Subjects: Urban structure -- Big data analytics -- Urban planning -- Community detection -- Network analysis -- London; City planning -- Periodicals; Urban policy -- Periodicals; 711.4
• DOI: 10.1016/j.cities.2021.103157
• Languages: English
• ISSNs: 0264-2751

Abstract

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. Highlights: A technique borrowed from the complex network sciences, namely community detection, is applied using smart card data. London's urban structure moved towards a more polycentric and compact pattern. Greater London can be clustered into five communities based on the characteristics of passengers' travel patterns. The dynamics of structural change differ both in terms of changing intensity and potential motivation. Employment density and residential densities affect the movement of and interaction between Londoners in different areas.