Université Paris-Saclay, CNRS, CEA, Institut de physique théorique, 91191, Gif-sur-Yvette, France.
École des Ponts ParisTech, Champs-sur-Marne, France.
Sci Data. 2020 Sep 8;7(1):301. doi: 10.1038/s41597-020-00639-3.
As mitigating car traffic in cities has become paramount to abate climate change effects, fostering public transport in cities appears ever-more appealing. A key ingredient in that purpose is easy access to mass rapid transit (MRT) systems. So far, we have however few empirical estimates of the coverage of MRT in urban areas, computed as the share of people living in MRT catchment areas, say for instance within walking distance. In this work, we clarify a universal definition of such a metrics - People Near Transit (PNT) - and present measures of this quantity for 85 urban areas in OECD countries - the largest dataset of such a quantity so far. By suggesting a standardized protocol, we make our dataset sound and expandable to other countries and cities in the world, which grounds our work into solid basis for multiple reuses in transport, environmental or economic studies.
随着在城市中减少汽车交通对于缓解气候变化影响变得至关重要，促进城市公共交通的发展显得更加有吸引力。实现这一目标的一个关键因素是方便地使用大众快速交通（MRT）系统。到目前为止，我们对于城市地区的 MRT 覆盖率（例如，在步行距离内）的经验估计还很少。在这项工作中，我们澄清了这样一个指标——People Near Transit（PNT）的通用定义，并为经合组织国家的 85 个城市地区提出了这一数量的度量标准——这是迄今为止此类数量的最大数据集。通过提出一个标准化协议，我们使我们的数据集具有稳定性和可扩展性，可以适用于世界上其他国家和城市，这为我们在交通、环境或经济研究中的多种用途奠定了坚实的基础。
