IF 5.8 2区 综合性期刊 Q1 MULTIDISCIPLINARY SCIENCES Scientific Data Pub Date : 2025-02-12 DOI:10.1038/s41597-025-04494-y
Yue Li, Qunshan Zhao, Mingshu Wang
{"title":"High-resolution traffic flow data from the urban traffic control system in Glasgow.","authors":"Yue Li, Qunshan Zhao, Mingshu Wang","doi":"10.1038/s41597-025-04494-y","DOIUrl":null,"url":null,"abstract":"<p><p>Traffic flow data has been used in various disciplines, including geography, transportation, urban planning, and public health. However, existing datasets often have limitations such as low spatiotemporal resolution and inconsistent quality due to data collection methods and the need for an adequate data cleaning process. This paper introduces a long-term traffic flow dataset at an intra-city scale with high spatio-temporal granularity. The dataset covers the Glasgow City Council area for four consecutive years spanning the COVID-19 pandemic, from October 2019 to September 2023, providing comprehensive temporal and spatial coverage. Such detailed information facilitates diverse applications, including traffic dynamic analysis, traffic management, infrastructure planning, and urban environment improvement. Also, it provides a valuable dataset to understand traffic flow change during a once-in-a-lifetime pandemic event.</p>","PeriodicalId":21597,"journal":{"name":"Scientific Data","volume":"12 1","pages":"253"},"PeriodicalIF":5.8000,"publicationDate":"2025-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11821839/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Scientific Data","FirstCategoryId":"103","ListUrlMain":"https://doi.org/10.1038/s41597-025-04494-y","RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MULTIDISCIPLINARY SCIENCES","Score":null,"Total":0}
引用次数: 0

摘要

交通流数据已被用于地理、交通、城市规划和公共卫生等多个学科。然而,现有的数据集往往存在一些局限性,如时空分辨率低、数据质量不稳定等,这些都是由数据收集方法和适当的数据清洗过程所造成的。本文介绍了一个具有高时空粒度的城市内长期交通流量数据集。该数据集覆盖格拉斯哥市议会辖区,时间跨度为 COVID-19 大流行期间的连续四年,即 2019 年 10 月至 2023 年 9 月,提供了全面的时间和空间覆盖。如此详尽的信息为交通动态分析、交通管理、基础设施规划和城市环境改善等多种应用提供了便利。此外,它还为了解千载难逢的大流行事件期间的交通流量变化提供了宝贵的数据集。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
High-resolution traffic flow data from the urban traffic control system in Glasgow.

Traffic flow data has been used in various disciplines, including geography, transportation, urban planning, and public health. However, existing datasets often have limitations such as low spatiotemporal resolution and inconsistent quality due to data collection methods and the need for an adequate data cleaning process. This paper introduces a long-term traffic flow dataset at an intra-city scale with high spatio-temporal granularity. The dataset covers the Glasgow City Council area for four consecutive years spanning the COVID-19 pandemic, from October 2019 to September 2023, providing comprehensive temporal and spatial coverage. Such detailed information facilitates diverse applications, including traffic dynamic analysis, traffic management, infrastructure planning, and urban environment improvement. Also, it provides a valuable dataset to understand traffic flow change during a once-in-a-lifetime pandemic event.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Scientific Data
Scientific Data Social Sciences-Education
CiteScore
11.20
自引率
4.10%
发文量
689
审稿时长
16 weeks
期刊介绍: Scientific Data is an open-access journal focused on data, publishing descriptions of research datasets and articles on data sharing across natural sciences, medicine, engineering, and social sciences. Its goal is to enhance the sharing and reuse of scientific data, encourage broader data sharing, and acknowledge those who share their data. The journal primarily publishes Data Descriptors, which offer detailed descriptions of research datasets, including data collection methods and technical analyses validating data quality. These descriptors aim to facilitate data reuse rather than testing hypotheses or presenting new interpretations, methods, or in-depth analyses.
期刊最新文献
A Comprehensive Dataset of Surface Water Quality Spanning 1940-2023 for Empirical and ML Adopted Research. A large open access dataset of transillumination imaging the toward realization of optical computed tomography. A neuroimaging dataset during sequential color qualia similarity judgments with and without reports. An ageing study of twenty 18650 lithium-ion Graphite/LFP cells in first and second life use. An electronic toll collection gateway BLE RSSI dataset for localization of smartphones in vehicular scenarios.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1