Centre for Advanced Spatial Analysis, University College London, London, United Kingdom.
PLoS One. 2013 Sep 6;8(9):e74685. doi: 10.1371/journal.pone.0074685. eCollection 2013.
Bicycle sharing systems exist in hundreds of cities around the world, with the aim of providing a form of public transport with the associated health and environmental benefits of cycling without the burden of private ownership and maintenance. Five cities have provided research data on the journeys (start and end time and location) taking place in their bicycle sharing system. In this paper, we employ visualization, descriptive statistics and spatial and network analysis tools to explore system usage in these cities, using techniques to investigate features specific to the unique geographies of each, and uncovering similarities between different systems. Journey displacement analysis demonstrates similar journey distances across the cities sampled, and the (out)strength rank curve for the top 50 stands in each city displays a similar scaling law for each. Community detection in the derived network can identify local pockets of use, and spatial network corrections provide the opportunity for insight above and beyond proximity/popularity correlations predicted by simple spatial interaction models.
自行车共享系统在全球数百个城市中存在，其目的是提供一种公共交通形式，让人们在享受骑自行车带来的健康和环境效益的同时，不必承担私人拥有和维护的负担。五个城市提供了关于其自行车共享系统中发生的行程（开始和结束时间和地点）的研究数据。在本文中，我们使用可视化、描述性统计以及空间和网络分析工具来探索这些城市的系统使用情况，使用技术来调查每个城市独特地理特征的特定功能，并揭示不同系统之间的相似之处。行程置换分析表明，抽样城市的行程距离相似，每个城市排名前 50 的（出）强度等级曲线都显示出相似的比例定律。从衍生网络中进行社区检测可以识别出使用的局部聚集区域，空间网络校正提供了超越简单空间交互模型预测的接近度/流行度相关性的洞察力。
