| 城市公共自行车使用与建成环境的关系研究——以南京市桥北片区为例 |
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| 引用本文： | 罗桑扎西,甄峰,尹秋怡.城市公共自行车使用与建成环境的关系研究——以南京市桥北片区为例[J].地理科学,2018,38(3):332-341. |
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| 作者姓名： | 罗桑扎西 甄峰 尹秋怡 |
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| 作者单位： | 南京大学建筑与城市规划学院, 江苏 南京210093 |
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| 基金项目： | 国家自然科学基金项目（41571146）、江苏省科技重点研发计划项目（SBE2015710009）资助 |
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| 摘 要： | 公共自行车作为一种绿色低碳的交通出行方式,在国内外许多城市得到了快速发展。目前国内公共自行车相关研究多以使用特征分析为主,而与建成环境关系的研究较少。采用运营大数据与网络开放大数据相结合的方法,以南京市桥北区为案例,研究公共自行车站点使用特征及建成环境对其的影响。研究结果表明：① 公共自行车的使用存在明显的时空间差异;② 使用主要受站点300 m范围内日常服务设施网点密度、基础设施及公共交通条件等建成环境因子影响;③ 建成环境对不同时段使用的影响存在较大差异。研究结果可为片区站点的优化布局与管理建设,以及无桩型共享单车的投放与运营管理提供科学的参考依据。
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| 关 键 词： | 公共自行车 大数据 建成环境 使用率 南京桥北 |
| 收稿时间： | 2017-04-04 |
| 修稿时间： | 2017-08-15 |
How Built Environment Influence Public Bicycle Usage: Evidence from the Bicycle Sharing System in Qiaobei Area,Nanjing |
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| Sangzhaxi Luo,Feng Zhen,Qiuyi Yin.How Built Environment Influence Public Bicycle Usage: Evidence from the Bicycle Sharing System in Qiaobei Area,Nanjing[J].Scientia Geographica Sinica,2018,38(3):332-341. |
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| Authors: | Sangzhaxi Luo Feng Zhen Qiuyi Yin |
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| Institution: | School of Architecture and Urban Planning, Nanjing University, Nanjing 210093, Jiangsu, China |
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| Abstract: | In the content of sustainable and smart city development, more and more cites in the world start building Bicycle Sharing System (BSS) which is a green and low-carbon way to travel. Most previous studies on BSS focus on analysis of trip characteristics with small sample survey and simple statistical analysis in China, few studies focus on quantitatively exploring built environment factors that affecting public bicycle flows and usage employing real bicycle usage data. In this article we aim to build a method to examine the influence of the built environment attributes on arrival and departure flows at station level using real bicycle usage data and combined with internet open data. Then by taking Qiaobei area of Nanjing as study object, first we analyzed the temporal and spatial characteristics of public bicycle usage, then we examine the influence of bicycle infrastructure, daily service facilities (such as super market restaurant) and built environment attributes on arrival and departure flows at station level using the a multiple linear regression model. The results show that: 1) There are significant spatial difference between station distribution and usage. Meanwhile there are significant differences in the public bicycles usage at different periods; the use of public bicycles is mainly concentrated in the morning and evening peak stage. It indicates that bicyclists mainly use public bicycle for commuting during morning and evening peak. 2) In built environment factors that in a buffer zone of 300 m around each bike sharing station, the length of secondary road in station catchment and the distance to the closest metro station as well as the number of shopping network, restaurant, around station and the capacity of station were most important factors that influence the bike usage. There is a significant positive correlation between the usage of public bicycle and the density of nearby living facilities, including restaurants, shopping centres and metro stations etc.. The closer station of public bicycle sits from the metro station, the higher frequency of public bicycle usage will occur. Another interesting finding is that there is somewhat competition between bus and public bicycle. 3) In different time periods,there are also significant differences between the built environment factors that influencing bike usage. The developed methodology and findings provide some useful information for urban planners and BSS administrators who design or optimize BSS to improve the demand and turnover of bikes at bike stations with the goal of maximizing usage and availability. At the same time, these finds put forward scientific and reasonable reference for the operation and management of the non-pile-type shared bicycle. |
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| Keywords: | bicycle sharing system big data built environment usage Nanjing City |
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