来自格拉斯哥城市交通控制系统的高分辨率流量数据
Yue Li1, Qunshan Zhao2, Mingshu Wang3
1Urban Big Data Centre, School of Social and Political Sciences, University of Glasgow, Glasgow, UK.
Scientific data
|February 12, 2025
概括
这项研究为格拉斯哥提供了高分辨率的长期交通流数据集,涵盖了COVID-19大流行. 这些数据为城市交通动态和流行病影响提供了宝贵的见解.
科学领域:
- 城市规划 城市规划
- 运输科学 运输科学
- 地理信息科学 地理信息科学
背景情况:
- 现有流量数据集的空间时间分辨率低,质量不一致.
- 数据收集方法和清理过程往往限制了当前交通数据的实用性.
- 需要详细的,长期的交通流量数据来进行全面的城市分析.
研究的目的:
- 引入一种新的,具有高时空细粒度的长期交通流数据集.
- 在四年内覆盖格拉斯哥市议会地区,包括COVID-19大流行期间 (2019年10月 - 2023年9月).
- 为了促进交通分析,管理和城市规划中的多样化应用.
主要方法:
- 收集和处理城市内交通流量数据.
- 在四年内确保高时空分辨率和数据质量.
- 数据集涵盖了格拉斯哥市议会地区的2019年10月至2023年9月.
主要成果:
- 已经生成了一个全面的,长期的流量数据集,具有很高的细节性.
- 该数据集提供了城市交通的详细时间和空间覆盖.
- 它捕捉了包括COVID-19流行病在内的重要时期的交通动态.
结论:
- 新的数据集支持先进的交通动态分析和管理.
- 它对基础设施规划和城市环境改善有价值.
- 该数据集为研究流行病引起的交通变化提供了一个独特的资源.
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