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一套2023年赫尔辛基地区的旅行时间矩阵数据集,对时间,模式和人际差异敏感,并使用开放数据和新的开源软件
Christoph Fink1,2, Elias Willberg3,4, Robert Klein3
1Digital Geography Lab, Department of Geosciences and Geography, University of Helsinki, Helsinki, Finland. christoph.fink@helsinki.fi.
Scientific data
|August 9, 2024
概括
本研究介绍了芬兰赫尔辛基的一个开放的旅行时间矩阵,详细说明了各种模式的门到门旅行时间. 这一数据集增强了对城市空间可访问性和规划的理解.
科学领域:
- 城市规划 城市规划
- 运输科学 运输科学
- 地理信息系统 (GIS) 是一个地理信息系统.
背景情况:
- 空间可访问性对于城市的运作,可持续性和公平性至关重要.
- 当代的测量依赖于地点之间的旅行时间.
- 了解城市动态需要准确的交互潜力的估计.
研究的目的:
- 为赫尔辛基大都会地区提供开放的旅行时间矩阵数据集.
- 通过使用门到门的行程时间,对空间可访问性的详细分析.
- 用可复制和可转移的数据支持城市和交通规划.
主要方法:
- 开发了r5py Python包用于旅行时间计算.
- 计算了步行,骑自行车,公共交通工具和汽车的门到门旅行时间.
- 在赫尔辛基大都会地区覆盖了13,132个电网单元.
- 与谷歌指南API相对验证的数据.
主要成果:
- 现在可以获得赫尔辛基的开放旅行时间矩阵数据集.
- 该数据集包括多种运输方式的全面门到门行程时间.
- 数据解释了白天变化和个体差异 (例如步行速度).
结论:
- 该数据集为城市规划者,企业和研究人员提供了宝贵的资源.
- 关键设计原则确保数据可比性,可复制性和可转移性.
- 这些数据有助于在城市和交通分析中的多种应用.
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