• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

富人不会早起:不同社会经济阶层出行网络中的时空模式。

Rich do not rise early: spatio-temporal patterns in the mobility networks of different socio-economic classes.

作者信息

Lotero Laura, Hurtado Rafael G, Floría Luis Mario, Gómez-Gardeñes Jesús

机构信息

Facultad de Ingeniería Industrial, Universidad Pontificia Bolivariana, Medellín, Colombia; Departamento de Ciencias de la Computación y de la Decisión, Universidad Nacional de Colombia, Medellín, Colombia.

Departamento de Física , Universidad Nacional de Colombia , Bogotá, Colombia.

出版信息

R Soc Open Sci. 2016 Oct 12;3(10):150654. doi: 10.1098/rsos.150654. eCollection 2016 Oct.

DOI:10.1098/rsos.150654
PMID:27853531
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5098956/
Abstract

We analyse the urban mobility in the cities of Medellín and Manizales (Colombia). Each city is represented by six mobility networks, each one encoding the origin-destination trips performed by a subset of the population corresponding to a particular socio-economic status. The nodes of each network are the different urban locations whereas links account for the existence of a trip between two different areas of the city. We study the main structural properties of these mobility networks by focusing on their spatio-temporal patterns. Our goal is to relate these patterns with the partition into six socio-economic compartments of these two societies. Our results show that spatial and temporal patterns vary across these socio-economic groups. In particular, the two datasets show that as wealth increases the early-morning activity is delayed, the midday peak becomes smoother and the spatial distribution of trips becomes more localized.

摘要

我们分析了麦德林和马尼萨莱斯(哥伦比亚)这两座城市的城市交通流动性。每个城市由六个交通网络表示,每个网络对特定社会经济地位的一部分人口所进行的起讫点出行进行编码。每个网络的节点是不同的城市地点,而边表示城市两个不同区域之间存在出行。我们通过关注其时空模式来研究这些交通网络的主要结构特性。我们的目标是将这些模式与这两个社会划分为六个社会经济阶层联系起来。我们的结果表明,这些社会经济群体的时空模式各不相同。特别是,这两个数据集表明,随着财富增加,清晨活动推迟,中午高峰变得更平缓,出行的空间分布变得更集中。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/108c/5098956/4ad6e456d565/rsos150654-g4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/108c/5098956/91712ae63f27/rsos150654-g1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/108c/5098956/409ba029f2e7/rsos150654-g2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/108c/5098956/bbf655ef736e/rsos150654-g3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/108c/5098956/4ad6e456d565/rsos150654-g4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/108c/5098956/91712ae63f27/rsos150654-g1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/108c/5098956/409ba029f2e7/rsos150654-g2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/108c/5098956/bbf655ef736e/rsos150654-g3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/108c/5098956/4ad6e456d565/rsos150654-g4.jpg

相似文献

1
Rich do not rise early: spatio-temporal patterns in the mobility networks of different socio-economic classes.富人不会早起:不同社会经济阶层出行网络中的时空模式。
R Soc Open Sci. 2016 Oct 12;3(10):150654. doi: 10.1098/rsos.150654. eCollection 2016 Oct.
2
Ranking places in attributed temporal urban mobility networks.赋予时间属性的城市移动性网络中的位置排序。
PLoS One. 2020 Oct 14;15(10):e0239319. doi: 10.1371/journal.pone.0239319. eCollection 2020.
3
Revealing latent characteristics of mobility networks with coarse-graining.利用粗粒化揭示移动性网络的潜在特征。
Sci Rep. 2019 May 17;9(1):7545. doi: 10.1038/s41598-019-44005-9.
4
How did micro-mobility change in response to COVID-19 pandemic? A case study based on spatial-temporal-semantic analytics.微出行如何因应新冠疫情而发生变化?基于时空语义分析的案例研究。
Comput Environ Urban Syst. 2021 Nov;90:101703. doi: 10.1016/j.compenvurbsys.2021.101703. Epub 2021 Aug 19.
5
Identifying Important Nodes in Trip Networks and Investigating Their Determinants.识别出行网络中的重要节点并研究其决定因素。
Entropy (Basel). 2023 Jun 20;25(6):958. doi: 10.3390/e25060958.
6
Visual exploration of big spatio-temporal urban data: a study of New York City taxi trips.大时空城市数据的可视化探索:以纽约市出租车出行为例。
IEEE Trans Vis Comput Graph. 2013 Dec;19(12):2149-58. doi: 10.1109/TVCG.2013.226.
7
Age and socio-economic status affect dengue and COVID-19 incidence: spatio-temporal analysis of the 2020 syndemic in Buenos Aires City.年龄和社会经济地位影响登革热和 COVID-19 的发病率:布宜诺斯艾利斯市 2020 年综合征的时空分析。
PeerJ. 2023 Sep 22;11:e14735. doi: 10.7717/peerj.14735. eCollection 2023.
8
Importance of Public Transport Networks for Reconciling the Spatial Distribution of Dengue and the Association of Socio-Economic Factors with Dengue Risk in Bangkok, Thailand.重要的是公共交通网络的协调空间分布登革热和社会经济因素与登革热风险在曼谷,泰国。
Int J Environ Res Public Health. 2022 Aug 16;19(16):10123. doi: 10.3390/ijerph191610123.
9
Socio-economic, built environment, and mobility conditions associated with crime: a study of multiple cities.社会经济、建筑环境和流动条件与犯罪相关:对多个城市的研究。
Sci Rep. 2020 Aug 17;10(1):13871. doi: 10.1038/s41598-020-70808-2.
10
Combining urban scaling and polycentricity to explain socio-economic status of urban regions.结合城市规模和多中心化解释城市区域的社会经济地位。
PLoS One. 2019 Jun 14;14(6):e0218022. doi: 10.1371/journal.pone.0218022. eCollection 2019.

引用本文的文献

1
A network-based analysis to assess COVID-19 disruptions in the Bogotá BRT system.一项基于网络的分析,以评估波哥大快速公交系统中新冠疫情造成的干扰。
Environ Plan B Urban Anal City Sci. 2023 May;50(4):983-999. doi: 10.1177/23998083221150646. Epub 2023 Jan 11.
2
Quantifying the heterogeneous impact of lockdown policies on different socioeconomic classes during the first COVID-19 wave in Colombia.量化新冠疫情第一波期间封锁政策对哥伦比亚不同社会经济阶层的异质影响。
Sci Rep. 2023 Sep 30;13(1):16481. doi: 10.1038/s41598-023-43685-8.
3
Intermunicipal travel networks of Mexico during the COVID-19 pandemic.

本文引用的文献

1
The structure and dynamics of multilayer networks.多层网络的结构与动态特性
Phys Rep. 2014 Nov 1;544(1):1-122. doi: 10.1016/j.physrep.2014.07.001. Epub 2014 Jul 10.
2
Evidence That Calls-Based and Mobility Networks Are Isomorphic.基于呼叫和移动网络同构的证据。
PLoS One. 2015 Dec 29;10(12):e0145091. doi: 10.1371/journal.pone.0145091. eCollection 2015.
3
Influence of sociodemographic characteristics on human mobility [corrected].社会人口学特征对人口流动的影响[已修正]
墨西哥在 COVID-19 大流行期间的城际旅行网络。
Sci Rep. 2023 May 26;13(1):8566. doi: 10.1038/s41598-023-35542-5.
4
Uncovering commercial activity in informal cities.揭示非正规城市中的商业活动。
R Soc Open Sci. 2022 Nov 2;9(11):211841. doi: 10.1098/rsos.211841. eCollection 2022 Nov.
5
Differences in the spatial landscape of urban mobility: Gender and socioeconomic perspectives.城市流动性空间格局的差异:性别和社会经济视角。
PLoS One. 2022 Mar 2;17(3):e0260874. doi: 10.1371/journal.pone.0260874. eCollection 2022.
6
COVID-19 policy analysis: labour structure dictates lockdown mobility behaviour.新冠政策分析:劳动力结构决定封锁期间的流动行为。
J R Soc Interface. 2021 Mar;18(176):20201035. doi: 10.1098/rsif.2020.1035. Epub 2021 Mar 31.
7
Entropy as a Measure of Attractiveness and Socioeconomic Complexity in Rio de Janeiro Metropolitan Area.熵作为里约热内卢大都市区吸引力和社会经济复杂性的一种度量
Entropy (Basel). 2020 Mar 23;22(3):368. doi: 10.3390/e22030368.
8
The bridging and bonding structures of place-centric networks: Evidence from a developing country.以地点为中心的网络的连接和结合结构:来自发展中国家的证据。
PLoS One. 2019 Sep 5;14(9):e0221148. doi: 10.1371/journal.pone.0221148. eCollection 2019.
9
The time geography of segregation during working hours.工作时间内隔离的时间地理学
R Soc Open Sci. 2018 Oct 3;5(10):180749. doi: 10.1098/rsos.180749. eCollection 2018 Oct.
10
An overview of city analytics.城市分析概述。
R Soc Open Sci. 2017 Feb 1;4(2):161063. doi: 10.1098/rsos.161063. eCollection 2017 Feb.
Sci Rep. 2015 May 20;5:10075. doi: 10.1038/srep10075.
4
From mobile phone data to the spatial structure of cities.从手机数据到城市的空间结构。
Sci Rep. 2014 Jun 13;4:5276. doi: 10.1038/srep05276.
5
Uncovering patterns of inter-urban trip and spatial interaction from social media check-in data.从社交媒体签到数据中揭示城市间出行模式和空间相互作用
PLoS One. 2014 Jan 17;9(1):e86026. doi: 10.1371/journal.pone.0086026. eCollection 2014.
6
Transport on coupled spatial networks.耦合空间网络上的传输。
Phys Rev Lett. 2012 Sep 21;109(12):128703. doi: 10.1103/PhysRevLett.109.128703. Epub 2012 Sep 18.
7
A tale of many cities: universal patterns in human urban mobility.多座城市的故事:人类城市流动性的普遍模式。
PLoS One. 2012;7(5):e37027. doi: 10.1371/journal.pone.0037027. Epub 2012 May 29.
8
Modeling the spatial spread of infectious diseases: the GLobal Epidemic and Mobility computational model.传染病空间传播建模:全球疫情与流动性计算模型
J Comput Sci. 2010 Aug 1;1(3):132-145. doi: 10.1016/j.jocs.2010.07.002.
9
The GLEaMviz computational tool, a publicly available software to explore realistic epidemic spreading scenarios at the global scale.GLEaMviz 计算工具,一个可公开获取的软件,用于探索全球范围内真实的传染病传播场景。
BMC Infect Dis. 2011 Feb 2;11:37. doi: 10.1186/1471-2334-11-37.
10
Structure of urban movements: polycentric activity and entangled hierarchical flows.城市运动的结构:多中心化活动和纠缠的层级流动。
PLoS One. 2011 Jan 7;6(1):e15923. doi: 10.1371/journal.pone.0015923.