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美国的空间可达性:机会可达性的多个指标。

Spatial Access of America: Multiple indicators of accessibility to opportunities.

作者信息

Verma Rajat, Mittal Shagun, Ukkusuri Satish V

机构信息

Lyles School of Civil and Construction Engineering, Purdue University, West Lafayette, IN, 47907, USA.

出版信息

Sci Data. 2025 Jul 15;12(1):1223. doi: 10.1038/s41597-025-05440-8.

Abstract

Spatial measures of accessibility are widely used in urban and transportation planning to understand the impact of the transportation system on influencing people's access to places, but publicly available large-scale datasets are rare and limited. This paper presents a highly parametric dataset containing values of spatial accessibility measured by combinations of multiple metrics, travel modes, types of opportunity (including jobs and amenities like schools, hospitals, and electric vehicle charging stations), and travel time thresholds. This includes both cumulative opportunities types of measures as well as competition metrics. A total of 600 accessibility values are computed for each zone at three administrative levels for the 50 most populous urban areas of the United States. Additionally, the dataset also includes the travel time matrix files for each of these urban areas by three travel modes - driving, walking, and bicycling - to facilitate self-validation. Further, comparisons with similar travel time and accessibility datasets show a high degree of similarity with our dataset.

摘要

可达性的空间测度在城市和交通规划中被广泛应用,以了解交通系统对人们到达各地的影响,但公开可用的大规模数据集却很少且有限。本文展示了一个高度参数化的数据集,其中包含通过多种指标、出行方式、机会类型(包括就业岗位以及学校、医院和电动汽车充电站等便利设施)和出行时间阈值的组合来衡量的空间可达性值。这包括累积机会类型的测度以及竞争指标。针对美国人口最多的50个城市地区,在三个行政级别上为每个区域计算了总共600个可达性值。此外,该数据集还包括这些城市地区中每种出行方式(驾车、步行和骑自行车)的出行时间矩阵文件,以方便自我验证。此外,与类似的出行时间和可达性数据集的比较表明,我们的数据集与之具有高度相似性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4483/12260004/5f37bc3f56af/41597_2025_5440_Fig1_HTML.jpg

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