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Xiao-guang RUAN


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Journal of Zhejiang University SCIENCE A 2022 Vol.23 No.8 P.621-638


How fast is it to city centers? The average travel speed as an indicator of road traffic accessibility potential

Author(s):  Xiao-guang RUAN

Affiliation(s):  College of Geomatics and Municipal Engineering, Zhejiang University of Water Resources and Electric Power, Hangzhou 310018, China

Corresponding email(s):   ruanxg@zjweu.edu.cn

Key Words:  Traffic accessibility, Google Maps application programming interface (API), Travel speed, Road traffic network, Geographic information system (GIS)

Xiao-guang RUAN. How fast is it to city centers? The average travel speed as an indicator of road traffic accessibility potential[J]. Journal of Zhejiang University Science A, 2022, 23(8): 621-638.

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%T How fast is it to city centers? The average travel speed as an indicator of road traffic accessibility potential
%A Xiao-guang RUAN
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%I Zhejiang University Press & Springer
%DOI 10.1631/jzus.A2100435

T1 - How fast is it to city centers? The average travel speed as an indicator of road traffic accessibility potential
A1 - Xiao-guang RUAN
J0 - Journal of Zhejiang University Science A
VL - 23
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SP - 621
EP - 638
%@ 1673-565X
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PB - Zhejiang University Press & Springer
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DOI - 10.1631/jzus.A2100435

Transportation is the lifeblood of a modern metropolis. Accessibility generally refers to the interconnection between nodes in a regional traffic network. The purpose of the paper is to obtain more realistic and accurate measures of travel speed and to study the road traffic accessibility potential in cities. This study proposes a method for analyzing road traffic accessibility potential which is based on the average travel speed to city centers in off-peak times and which ranks 80 cities around the world. Based on the Suomi National Polar-Orbiting Partnership satellite’s visible-infrared imaging radiometer suite (NPP-VIIRS) night-time light data, urban built-up areas and city centers were extracted. Further, with the aid of the google Maps application programming interface (API) network crawling technique, travel times and travel distances for several optimal routes to city centers by car were obtained. Feasible proposals for improving road traffic accessibility and planning urban transportation in different cities are presented. The proposed method offers a new possibility of analyzing traffic accessibility using internet data and geo-spatial methods.


方法:1.数据预处理:NPP-VIIRS和Landsat-8 OLI/TIRS遥感影像进行辐射和几何校正、图像拼接、图像配准、图像增强等;所有栅格数据、矢量数据(行政区数据)统一坐标系。2.起点和终点确定:基于阈值法提取建成区;行政区和建成区的500 m×500 m格网数据作为路径起点;基于局部轮廓树法确定城市中心位置,并作为路径终点。3.路径爬取:借助Google MapDirections API爬取起点到达城市中心的若干最佳驾车路径数据,包括时间和距离。4.速度计算:基于路径时间和距离,计算起点抵达市中心的出行速度,分析城市内部道路的通达性潜力(图1);以平均出行速度对研究城市进行通达性潜力排名。
结论:1.所研究城市行政区平均出行速度为37.56 km/h,城市建成区平均出行速度为34.30 km/h,速度与道路基础设施水平、车流和区域发展水平一致。2.所选指标可以有效地确定道路通达性潜力的空间分异;通过该方法获得的行程时间和行程距离可作为城市道路分析的地理数据,即高出行速度的地区通达性潜力好,而低出行速度的地区通达性潜力差。3.该方法为利用互联网数据和地理空间方法分析交通通达性提供了新的可能性,且能够定量分析交通地理学中的问题;城市出行速度结果和排名可以作为一个国际数据集。


Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article


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