Exploring Associations between the Built Environment and Cycling Behaviour around Urban Greenways from a Human-Scale Perspective

Yiwei Bai,Yihang Bai,Ruoyu Wang,Tianren Yang, Xinyao Song, Bo Bai

LAND(2023)

引用 0|浏览12
暂无评分
摘要
The incorporation of cycling as a mode of transport has been shown to have a positive impact on reducing traffic congestion, improving mental health outcomes, and contributing to the development of sustainable cities. The proliferation of bike-sharing systems, characterised by their wide availability and high usage rates, has made cycling in urban areas more accessible and convenient for individuals. While the existence of a relationship between cycling behaviour and the built environment has been established, few studies have specifically examined this connection for weekdays and weekends. With the emergence of new data sources, new methodologies have become available for research into this area. For instance, bike-sharing spatio-temporal datasets have made it possible to precisely measure cycling behaviour over time, while street-view images and deep learning techniques now enable researchers to quantify the built environment from a human perspective. In this study, we used 139,018 cycling trips and 14,947 street-view images to examine the connection between the built environment consisting of urban greenways and cycling behaviour. The results indicated that the greenness and enclosure of the level of greenway were positively correlated with increased cycling on both weekdays and weekends. However, the openness of the greenway appears to have opposing effects on cycling behaviour depending on the day of the week, with high levels of openness potentially promoting cycling on weekends but hindering it on weekdays. Based on the findings of this study, policymakers and planners should focus on the cycling environment and prioritise improving its comfort and safety to promote green transportation and bicycle-friendly cities.
更多
查看译文
关键词
urban planning,bicycle sharing,cycling behaviour,urban greenways,built environment,urban perceptions
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要