确定格拉斯哥新自行车共享站的位置:空间公平和需求因素分析

IF 2.7 Q1 GEOGRAPHY Annals of GIS Pub Date : 2020-11-24 DOI:10.1080/19475683.2021.1936172
J. Beairsto, Yufan Tian, Linyu Zheng, Qunshan Zhao, Jinhyun Hong
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引用次数: 13

摘要

作为一种可替代的环保交通方式,全球范围内的共享单车系统越来越受欢迎。随着城市寻求进一步发展自行车共享计划,重要的是要考虑系统应该如何扩展,以同时解决现有的可达性不平等问题,并最好地满足需求。在本文中,我们通过将需求模型与可达性考虑相结合,确定了苏格兰格拉斯哥未来共享单车站的理想位置。我们首先分析了共享单车使用的时空趋势,并评估了格拉斯哥车站的空间公平性。为了确定共享单车需求的重要决定因素,我们使用Nextbike Glasgow的共享单车出行数据运行了一个普通最小二乘回归模型。然后,我们采用两步浮动集水区(2SFCA)方法定量测量了车站的空间可达性水平,并使用车站需求的重要决定因素进行了GIS加权叠加分析。最后,我们将需求和可达性结果结合起来,使用最大覆盖位置问题(MCLP)来确定新车站的位置,从而最大化服务的人口。研究结果表明,与公交车站的距离、与市中心的距离、就业率和附近的自行车道是影响车站级需求的显著因素。此外,格拉斯哥的中部和东部地区的空间通道水平最高。这些发现有助于确定未来车站位置的优先区域,我们的方法可以很容易地应用于其他自行车共享计划,并根据系统扩展的不同目标进行调整。
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Identifying locations for new bike-sharing stations in Glasgow: an analysis of spatial equity and demand factors
ABSTRACT Worldwide bike-sharing systems are growing in popularity as an alternative, environmentally friendly mode of transportation. As cities seek to further develop bike-sharing programmes, it is important to consider how systems should expand to simultaneously address existing inequalities in accessibility, and best serve demand. In this paper, we determine ideal locations for future bike-sharing stations in Glasgow, Scotland, by integrating demand modelling with accessibility considerations. We began by analysing the spatio-temporal trends of bike-sharing usage, and assessed the spatial equity of access to stations in Glasgow. To identify important determinants of bike-sharing demand, we ran an ordinary least squares regression model using bike sharing trip data from Nextbike Glasgow. We then quantifiably measured the level of spatial accessibility to stations by applying the two-step floating catchment area (2SFCA) methodology and ran a GIS weighted overlay analysis using the significant determinants of station demand. Lastly, we combined the demand and accessibility results to determine where new stations should be located using a maximum covering location problem (MCLP) that maximized the population served. Our results show that distance from transit stations, distance from downtown, employment rates, and nearby cycling lanes are significant factors affecting station-level demand. Furthermore, levels of spatial access were found to be highest primarily in the centre and eastern neighbourhood of Glasgow. These findings aided in determining areas to prioritize for future station locations, and our methodology can easily be applied to other bike-share programmes with adjustments according to varying aims for system expansion.
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来源期刊
Annals of GIS
Annals of GIS Multiple-
CiteScore
8.30
自引率
2.00%
发文量
31
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