Cited by 461Human Mobility and Location-Based AnalysisUrban Design and Spatial AnalysisGlobal Urban Networks and Dynamics

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Structure of Urban Movements: Polycentric Activity and Entangled Hierarchical Flows

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Roth, Camille, Kang, Soong Moon, Batty, Michael, Barthélemy, Marc·2011·PLoS ONE

DOI 10.1371/journal.pone.0015923PMC PMC3017563

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Abstract

The spatial arrangement of urban hubs and centers and how individuals interact with these centers is a crucial problem with many applications ranging from urban planning to epidemiology. We utilize here in an unprecedented manner the large scale, real-time 'Oyster' card database of individual person movements in the London subway to reveal the structure and organization of the city. We show that patterns of intraurban movement are strongly heterogeneous in terms of volume, but not in terms of distance travelled, and that there is a polycentric structure composed of large flows organized around a limited number of activity centers. For smaller flows, the pattern of connections becomes richer and more complex and is not strictly hierarchical since it mixes different levels consisting of different orders of magnitude. This new understanding can shed light on the impact of new urban projects on the evolution of the polycentric configuration of a city and the dense structure of its centers and it provides an initial approach to modeling flows in an urban system.

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The Elements of Statistical Learning
Hastie, T., Friedman, J., & Tibshirani, R. (2001) · Springer Series in Statistics · doi:10.1007/978-0-387-21606-5 · Cited by 24,162
Understanding individual human mobility patterns
González, M. C., Hidalgo, C. A., & Barabási, A.-Ĺ. (2008) · Nature · doi:10.1038/nature06958 · Cited by 6,186
The Spatial Economy: Cities, Regions, and International Trade
Fujita, M., Krugman, P., & Venables, A. J. (1999) · doi:10.7551/mitpress/6389.001.0001 · Cited by 4,788
Random graphs with arbitrary degree distributions and their applications
Newman, M. E. J., Strogatz, S. H., & Watts, D. J. (2001) · Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics · doi:10.1103/physreve.64.026118 · Cited by 3,675
A critical point for random graphs with a given degree sequence
Molloy, M. S. O., & Reed, B. A. (1995) · Random Structures and Algorithms · doi:10.1002/rsa.3240060204 · Cited by 2,267
The scaling laws of human travel
Brockmann, D., Hufnagel, L., & Geisel, T. (2006) · Nature · doi:10.1038/nature04292 · Cited by 2,182
Modelling disease outbreaks in realistic urban social networks
Eubank, S., Güçlü, H., Kumar, V. S. A., MARATHE, M. V., Srinivasan, A., Toroczkai, Z., & Wang, N. (2004) · Nature · doi:10.1038/nature02541 · Cited by 2,098
Urban Spatial Structure
Warf, B. (2010) · Encyclopedia of Geography · doi:10.4135/9781412939591.n1196 · Cited by 1,196
URBAN SPATIAL STRUCTURE.
Anas, A., Arnott, R., & Small, K. A. (1997) · RePEc: Research Papers in Economics · Cited by 819
The Polycentric Urban Region: Towards a Research Agenda
Kloosterman, R. C., & Musterd, S. (2001) · Urban Studies · doi:10.1080/00420980120035259 · Cited by 597

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Hedenqvist, P., Trbakovic, A., Thor, A. L. I., Ley, C., Ekman, S., & Jensen‐Waern, M. (2016) · Research in Veterinary Science · doi:10.1016/j.rvsc.2016.05.010 · Cited by 22
Characterizing the Spatial Structure(s) of Cities “on the fly”: The Space‐Time Calendar
Arribas‐Bel, D., & Tranos, E. (2017) · Geographical Analysis · doi:10.1111/gean.12137 · Cited by 22
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Wang, Z., Hu, Y.-X., Zhu, P., Qin, Y., & Jia, L. (2017) · Physica A Statistical Mechanics and its Applications · doi:10.1016/j.physa.2017.08.105 · Cited by 22
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Yang, J. F., Sun, Y., Shang, B., Wang, L., & Zhu, J. (2019) · Sensors · doi:10.3390/s19122812 · Cited by 22
Supplementary Information for “Quantifying long-term evolution of intra-urban spatial interactions”
Sun, L., Jin, J. G., Axhausen, K. W., Lee, D., & Cebrián, M. (2015) · Repository for Publications and Research Data (ETH Zurich) · doi:10.3929/ethz-b-000164394 · Cited by 22
Big data‐enabled social sensing in spatial analysis: Potentials and pitfalls
Liao, C., Brown, D. G., Fei, D., Long, X., Chen, D., & Che, S. (2018) · Transactions in GIS · doi:10.1111/tgis.12483 · Cited by 21
Urbanization alters the composition, but not the diversity and structure, of Neotropical savanna woody plant communities
de Freitas, É. V. D., Veloso, M. D. D. M., & de Araújo, W. S. (2020) · Folia Geobotanica · doi:10.1007/s12224-020-09366-4 · Cited by 21
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Authors: Roth, C., Kang, S. M., Batty, M., & Barthélemy, M.
Affiliations: Centre National de la Recherche Scientifique (FR)
University College London (GB)
Corresponding author: Barthélemy, Marc
ORCID: Roth, Camille
Kang, Soong Moon
Batty, Michael
Barthélemy, Marc
Venue: PLoS ONE
Publisher: Public Library of Science (PLoS)
Published: 2011-01-07
Volume: 6
Issue: 1
Pages: e15923
ISSN: 1932-6203 (ISSN-L)
DOI: 10.1371/journal.pone.0015923
PMC: PMC3017563
OpenAlex: W2015480405
Cited by: 461
References: 31
Citations by year: 2026: 10 · 2025: 19 · 2024: 14 · 2023: 19 · 2022: 25 · 2021: 36 · 2020: 43 · 2019: 48 · 2018: 39 · 2017: 39 · 2016: 50 · 2015: 39 · 2014: 31 · 2013: 22 · 2012: 19
FWCI: 72.59
Type: journal article
Language: en
Open access: gold
doi.org
Licence: cc-by
creativecommons.org/licenses/by/4.0/ (unspecified)
Locations: PLoS ONE (publishedVersion, cc-by)
PubMed Central (publishedVersion, cc-by)
PubMed (publishedVersion)
arXiv (Cornell University) (submittedVersion)
RePEc: Research Papers in Economics (submittedVersion)
DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
UCL Discovery (University College London) (submittedVersion)
arXiv (Cornell University)
Topics: Social Sciences › Transportation › Human Mobility and Location-Based Analysis
Social Sciences › Urban Studies › Urban Design and Spatial Analysis
Social Sciences › Urban Studies › Global Urban Networks and Dynamics
Keywords: urban mobility, activity centers, flow heterogeneity, urban hubs
MeSH terms: City Planning, Humans, London, Population Dynamics, Urban Population

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Structure of Urban Movements: Polycentric Activity and Entangled Hierarchical Flows

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