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dc.contributor.author
Zhong, Chen
dc.contributor.author
Batty, Michael
dc.contributor.author
Manley, Ed
dc.contributor.author
Wang, Jiaqiu
dc.contributor.author
Wang, Zijia
dc.contributor.author
Chen, Feng
dc.contributor.author
Schmitt, Gerhard
dc.date.accessioned
2018-10-04T12:57:30Z
dc.date.available
2017-06-12T02:44:21Z
dc.date.available
2018-10-04T12:57:30Z
dc.date.issued
2016-02-12
dc.identifier.issn
1932-6203
dc.identifier.other
10.1371/journal.pone.0149222
en_US
dc.identifier.uri
http://hdl.handle.net/20.500.11850/114229
dc.identifier.doi
10.3929/ethz-b-000114229
dc.description.abstract
To discover regularities in human mobility is of fundamental importance to our understanding of urban dynamics, and essential to city and transport planning, urban management and policymaking. Previous research has revealed universal regularities at mainly aggregated spatio-temporal scales but when we zoom into finer scales, considerable heterogeneity and diversity is observed instead. The fundamental question we address in this paper is at what scales are the regularities we detect stable, explicable, and sustainable. This paper thus proposes a basic measure of variability to assess the stability of such regularities focusing mainly on changes over a range of temporal scales. We demonstrate this by comparing regularities in the urban mobility patterns in three world cities, namely London, Singapore and Beijing using one-week of smart-card data. The results show that variations in regularity scale as non-linear functions of the temporal resolution, which we measure over a scale from 1 minute to 24 hours thus reflecting the diurnal cycle of human mobility. A particularly dramatic increase in variability occurs up to the temporal scale of about 15 minutes in all three cities and this implies that limits exist when we look forward or backward with respect to making short-term predictions. The degree of regularity varies in fact from city to city with Beijing and Singapore showing higher regularity in comparison to London across all temporal scales. A detailed discussion is provided, which relates the analysis to various characteristics of the three cities. In summary, this work contributes to a deeper understanding of regularities in patterns of transit use from variations in volumes of travellers entering subway stations, it establishes a generic analytical framework for comparative studies using urban mobility data, and it provides key points for the management of variability by policy-makers intent on for making the travel experience more amenable.
en_US
dc.format
application/pdf
en_US
dc.language.iso
en
en_US
dc.publisher
PLOS
dc.rights.uri
http://creativecommons.org/licenses/by/4.0/
dc.title
Variability in Regularity: Mining Temporal Mobility Patterns in London, Singapore and Beijing Using Smart-Card Data
en_US
dc.type
Journal Article
dc.rights.license
Creative Commons Attribution 4.0 International
ethz.journal.title
PLoS ONE
ethz.journal.volume
11
en_US
ethz.journal.issue
2
en_US
ethz.journal.abbreviated
PLoS ONE
ethz.pages.start
e0149222
en_US
ethz.size
17 p.
en_US
ethz.version.deposit
publishedVersion
en_US
ethz.identifier.wos
ethz.identifier.scopus
ethz.publication.status
published
en_US
ethz.date.deposited
2017-06-12T02:44:43Z
ethz.source
ECIT
ethz.identifier.importid
imp59365439cf54a60519
ethz.ecitpid
pub:176003
ethz.eth
yes
en_US
ethz.availability
Open access
en_US
ethz.rosetta.installDate
2017-07-26T14:40:12Z
ethz.rosetta.lastUpdated
2024-02-02T06:15:40Z
ethz.rosetta.exportRequired
true
ethz.rosetta.versionExported
true
ethz.COinS
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