Evidence map›Paper›PMID 38802395›Full record

ArticleNature communications2024

Unravelling the spatial directionality of urban mobility.

Pengjun Zhao, Hao Wang, Qiyang Liu, Xiao-Yong Yan, Jingzhong Li

Erratum issuedAbstract read
In one paragraph

Article in Nature communications, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. ICT usage increases workforce geographical diversity.Proceedings of the National Academy of Sciences of the United States of America · 2025
    Article
  7. Article
  8. Article
  9. Congestion Transition on Random Walks on Graphs.Entropy (Basel, Switzerland) · 2024
    Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors.

Pengjun ZhaoCollege of Urban and Environmental Sciences, Peking University, Beijing, 100871, China. pengjun.zhao@pku.edu.cn.ORCID http://orcid.org/0000-0001-5373-5551
Hao WangSchool of Urban Planning and Design, Shenzhen Graduate School, Peking University, Shenzhen, 518055, China.ORCID http://orcid.org/0009-0001-5286-0868
Qiyang LiuSchool of Urban Planning and Design, Shenzhen Graduate School, Peking University, Shenzhen, 518055, China. tsql@pku.edu.cn.ORCID http://orcid.org/0000-0003-0953-7050
Xiao-Yong YanSchool of Systems Science, Beijing Jiaotong University, Beijing, 100044, China. yanxy@bjtu.edu.cn.ORCID http://orcid.org/0000-0003-2091-6967
Jingzhong LiCollege of Urban and Environmental Sciences, Xuchang University, Xuchang, 461000, China.

Funding

National Natural Science Foundation of China (National Science Foundation of China) 41925003National Natural Science Foundation of China (National Science Foundation of China) 42130402National Natural Science Foundation of China (National Science Foundation of China) 72271019Shenzhen Science and Technology Innovation Commission JCYJ20220818100810024Shenzhen Science and Technology Innovation Commission KQTD20221101093604016
6 · The paper itself

Abstract

As it is central to sustainable urban development, urban mobility has primarily been scrutinised for its scaling and hierarchical properties. However, traditional analyses frequently overlook spatial directionality, a critical factor in city centre congestion and suburban development. Here, we apply vector computation to unravel the spatial directionality of urban mobility, introducing a two-dimensional anisotropy-centripetality metric. Utilising travel data from 90 million mobile users across 60 Chinese cities, we effectively quantify mobility patterns through this metric, distinguishing between strong monocentric, weak monocentric, and polycentric patterns. Our findings highlight a notable difference: residents in monocentric cities face increasing commuting distances as cities expand, in contrast to the consistent commuting patterns observed in polycentric cities. Notably, mobility anisotropy intensifies in the outskirts of monocentric cities, whereas it remains uniform in polycentric settings. Additionally, centripetality wanes as one moves from the urban core, with a steeper decline observed in polycentric cities. Finally, we reveal that employment attraction strength and commuting distance scaling are key to explaining these divergent urban mobility patterns. These insights are important for shaping effective policies aimed at alleviating congestion and guiding suburban housing development.

Identifiers

PMID38802395
PMCPMC11130278

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.