Journal of Transport and Land Use

Correlation between the built environment and dockless bike-sharing trips connecting to urban metro stations

Jiaomin Wei

Beijing University of Technology

Yanyan Chen

Beijing University of Technology

Zhuo Liu

Beijing University of Technology

Yang Wang

Beijing University of Technology

DOI: https://doi.org/10.5198/jtlu.2023.2262

Keywords: Bike sharing, Built environment, Metro station, Street-view image, Cycling speed

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Abstract

The influence of the built environment on dockless bike-sharing (DBS) trips connecting to urban metro stations has always been a significant problem for planners. However, the evidence for correlations between microscale built-environment factors and DBS-metro transfer trips remains inconclusive. To address this, a framework, augmented by big data, is formulated to analyze the correlation of built environment with DBS–metro transfer trips from the macroscopic and microscopic views, considering Beijing as a case study. The trip density and cycling speed are calculated based on 11,120,676 pieces of DBS data and then used to represent the characteristic of DBS-metro transfer trips in a multiple linear regression model. Furthermore, a novel method is proposed to determine the built-environment sampling area around a station by its corresponding DBS travel distances. Accordingly, 6 microscale built-environment factors are extracted from street-view images using deep learning and integrated into the analysis model, together with 14 macroscale built-environment factors and 8 potential influencing factors of socioeconomic attributes and metro station attributes. The results reveal the significant positive influence of greenery and presence of barriers on trip density and cycling speed. Additionally, presence of streetlights is found to be negatively correlated with both trip density and cycling speed. Presence of signals is also found to have an influence on DBS-metro transfer trips, but it only negatively impacts trip density.

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References

Beijing Metro. (2019). Station information. Retrieved from https://www.bjsubway.com/-en/station/xltcx/

Beijing Municipal Commission of Planning and Natural Resources. (2021). Beijing rail transit network planning (2020-2035). Retrieved from https://ks3-cn-beijing.ksyun.com/attachment/383eb6614bd5c91e-6975cc4dcae5a060

Beijing Transportation Institute (2020). 2020 Beijing transport development annual report. Retrieved from https://www.bjtrc.org.cn/List/index/-cid/7.html

Biljecki, F., & Ito, K. (2021). Street view imagery in urban analytics and GIS: A review. Landscape and Urban Planning, 215, 104217.

Boufous, S., Hatfield, J., & Grzebieta, R. (2018). The impact of environmental factors on cycling speed on shared paths. Accident Analysis & Prevention, 110, 171–176.

Bullock, C., Brereton, F., & Bailey, S. (2017). The economic contribution of public bike-share to the sustainability and efficient functioning of cities. Sustainable Cities and Society, 28, 76–87.

Campbell, A., Both, A., & Sun, Q. (Chayn). (2019). Detecting and mapping traffic signs from Google Street View images using deep learning and GIS. Computers, Environment and Urban Systems, 77, 101350.

Caspi, O., & Noland, R. B. (2019). Bike sharing in Philadelphia: Do lower-income areas generate trips? Travel Behavior and Society, 16, 143–152.

Chen, E., & Ye, Z. (2021). Identifying the nonlinear relationship between free-floating bike-sharing usage and built environment. Journal of Cleaner Production, 280, 124281.

Chen, J., Zhou, D., Zhao, Y., Wu, B., & Wu, T. (2020). Life-cycle carbon dioxide emissions of bike sharing in China: Production, operation, and recycling. Resources, Conservation and Recycling, 162, 105011.

Chen, W., Chen, X., Chen, J., & Cheng, L. (2022). What factors influence ridership of station-based bike sharing and free-floating bike sharing at rail transit stations? International Journal of Sustainable Transportation, 16(4), 357–373.

Chen, Y., Chen, Y., Tu, W., & Zeng, X. (2020). Is eye-level greening associated with the use of dockless shared bicycles? Urban Forestry & Urban Greening, 51, 126690.

Chen, Y., Zhang, Y., Coffman, D., & Mi, Z. (2022). An environmental benefit analysis of bike sharing in New York City. Cities, 121, 103475.

Chen, Z., van Lierop, D., & Ettema, D. (2020). Dockless bike-sharing systems: What are the implications? Transport Reviews, 40(3), 333–353.

Clockston, R. L. M., & Rojas-Rueda, D. (2021). Health impacts of bike-sharing systems in the U.S. Environmental Research, 202, 111709.

Dai, L., Zheng, C., Dong, Z., Yao, Y., Wang, R., Zhang, X., ,,, & Guan, Q. (2021). Analyzing the correlation between visual space and residents’ psychology in Wuhan, China using street-view images and deep-learning technique. City and Environment Interactions, 11, 100069.

Fan, Y., & Zheng, S. (2020). Dockless bike sharing alleviates road congestion by complementing subway travel: Evidence from Beijing. Cities, 107, 102895.

Gan, Z., Yang, M., Zeng, Q., & Timmermans, H. J. P. (2021). Associations between built environment, perceived walkability/bikeability and metro transfer patterns. Transportation Research Part A: Policy and Practice, 153, 171–187.

Gao, J., Sha, A., Huang, Y., Hu, L., Tong, Z., & Jiang, W. (2018). Evaluating the cycling comfort on urban roads based on cyclists’ perception of vibration. Journal of Cleaner Production, 192, 531–541.

Gibbs, H., Liu, Y., Pearson, C. A. B., Jarvis, C. I., Grundy, C., Quilty, B. J., Diamond, C., & Eggo, R. M. (2020). Changing travel patterns in China during the early stages of the COVID-19 pandemic. Nature Communications, 11(1), 5012.

Guo, Y., & He, S. Y. (2020). Built environment effects on the integration of dockless bike-sharing and the metro. Transportation Research Part D: Transport and Environment, 83, 102335.

Guo, Y., & He, S. Y. (2021). Perceived built environment and dockless bikeshare as a feeder mode of metro. Transportation Research Part D: Transport and Environment, 92, 102693.

Guo, Y., Yang, L., Lu, Y., & Zhao, R. (2021). Dockless bike-sharing as a feeder mode of metro commute? The role of the feeder-related built environment: Analytical framework and empirical evidence. Sustainable Cities and Society, 65, 102594.

Hankey, S., Zhang, W., Le, H. T. K., Hystad, P., & James, P. (2021). Predicting bicycling and walking traffic using street view imagery and destination data. Transportation Research Part D: Transport and Environment, 90, 102651.

Hatfield, J., & Prabhakharan, P. (2016). An investigation of behavior and attitudes relevant to the user safety of pedestrian/cyclist shared paths. Transportation Research Part F: Traffic Psychology and Behavior, 40, 35–47.

Helbich, M., Yao, Y., Liu, Y., Zhang, J., Liu, P., & Wang, R. (2019). Using deep learning to examine street view green and blue spaces and their associations with geriatric depression in Beijing, China. Environment International, 126, 107–117.

Hsu, W., Zhang, Y., & Long, Y. (2022). Valuing the micropublic space: A perspective from Beijing housing prices. Journal of Urban Planning and Development, 148(2), 04022012.

Hu, S., Chen, M., Jiang, Y., Sun, W., & Xiong, C. (2022). Examining factors associated with bike-and-ride (BnR) activities around metro stations in large-scale dockless bike-sharing systems. Journal of Transport Geography, 98, 103271.

Ji, Y., Fan, Y., Ermagun, A., Cao, X., Wang, W., & Das, K. (2017). Public bicycle as a feeder mode to rail transit in China: The role of gender, age, income, trip purpose, and bicycle theft experience. International Journal of Sustainable Transportation, 11(4), 308–317.

Jin, M., Gong, L., Cao, Y., Zhang, P., Gong, Y., & Liu, Y. (2021). Identifying borders of activity spaces and quantifying border effects on intra-urban travel through spatial interaction network. Computers, Environment and Urban Systems, 87, 101625.

Ke, X., Men, H., Zhou, T., Li, Z., & Zhu, F. (2021). Variance of the impact of urban green space on the urban heat island effect among different urban functional zones: A case study in Wuhan. Urban Forestry & Urban Greening, 62, 127159.

Kutner, M. H., Nachtsheim, C. J., Neter, J., & Wasserman, W. (2004). Applied linear regression models, Vol. 4 (pp. 563-568). New York: McGraw-Hill/Irwin.

Li, W., Chen, S., Dong, J., & Wu, J. (2021). Exploring the spatial variations of transfer distances between dockless bike-sharing systems and metros. Journal of Transport Geography, 92, 103032.

Li, X., Du, M., & Yang, J. (2020). Factors influencing the access duration of free-floating bike sharing as a feeder mode to the metro in Shenzhen. Journal of Cleaner Production, 277, 123273.

Li, Y., Zhu, Z., & Guo, X. (2019). Operating characteristics of dockless bike-sharing systems near metro stations: Case study in Nanjing City, China. Sustainability, 11(8), 2256.

Lin, J. J., Zhao, P., Takada, K., Li, S., Yai, T., & Chen, C. H. (2018). Built environment and public bike usage for metro access: A comparison of neighborhoods in Beijing, Taipei, and Tokyo. Transportation Research Part D: Transport and Environment, 63, 209–221.

Liu, H. C., & Lin, J. J. (2019). Associations of built environments with spatiotemporal patterns of public bicycle use. Journal of Transport Geography, 74, 299–312.

Liu, Y., Ji, Y., Feng, T., & Timmermans, H. (2020). Understanding the determinants of young commuters’ metro-bikeshare usage frequency using big data. Travel Behavior and Society, 21, 121–130.

Liu, Y., Wang, R., Xiao, Y., Huang, B., Chen, H., & Li, Z. (2019). Exploring the linkage between greenness exposure and depression among Chinese people: Mediating roles of physical activity, stress and social cohesion and moderating role of urbanicity. Health & Place, 58, 102168.

Lu, Y. (2019). Using Google Street View to investigate the association between street greenery and physical activity. Landscape and Urban Planning, 191, 103435.

Lu, Y., Yang, Y., Sun, G., & Gou, Z. (2019). Associations between overhead-view and eye-level urban greenness and cycling behaviors. Cities, 88, 10–18.

Ma, X., Ji, Y., Yuan, Y., Van Oort, N., Jin, Y., & Hoogendoorn, S. (2020). A comparison in travel patterns and determinants of user demand between docked and dockless bike-sharing systems using multi-sourced data. Transportation Research Part A: Policy and Practice, 139, 148–173.

Ma, X., Ma, C., Wu, C., Xi, Y., Yang, R., Peng, N., … & Ren, F. (2021). Measuring human perceptions of streetscapes to better inform urban renewal: A perspective of scene semantic parsing. Cities, 110, 103086.

Maas, S., Attard, M., & Caruana, M. A. (2020). Assessing spatial and social dimensions of shared bicycle use in a Southern European island context: The case of Las Palmas de Gran Canaria. Transportation Research Part A: Policy and Practice, 140, 81–97.

Mateo-Babiano, I., Bean, R., Corcoran, J., & Pojani, D. (2016). How does our natural and built environment affect the use of bicycle sharing? Transportation Research Part A: Policy and Practice, 94, 295–307.

Meng, C., Song, Y., Ji, J., Jia, Z., Zhou, Z., Gao, P., & Liu, S. (2022). Automatic classification of rural building characteristics using deep learning methods on oblique photography. Building Simulation, 15(6), 1161–1174.

Ni, Y., & Chen, J. (2020). Exploring the effects of the built environment on two transfer modes for metros: Dockless bike sharing and taxis. Sustainability, 12(5), 2034.

Sanche, S., Lin, Y.T., Xu, C., Romero-Severson, E., Hengartner, N.W., & Ke, R. (2020). The novel coronavirus, 2019-nCoV, is highly contagious and more infectious than initially estimated (arXiv preprint). Retrieved from https://arxiv.org/abs/2002.03268

Song, Y., Chen, B., Ho, H. C., Kwan, M. P., Liu, D., Wang, F., … & Xu, Y. (2021). Observed inequality in urban greenspace exposure in China. Environment International, 156, 106778.

Tang, J., & Long, Y. (2019). Measuring visual quality of street space and its temporal variation: Methodology and its application in the Hutong area in Beijing. Landscape and Urban Planning, 191, 103436.

Tran, P. T. M., Zhao, M., Yamamoto, K., Minet, L., Nguyen, T., & Balasubramanian, R. (2020). Cyclists’ personal exposure to traffic-related air pollution and its influence on bikeability. Transportation Research Part D: Transport and Environment, 88, 102563.

Vansteenkiste, P., Zeuwts, L., van Maarseveen, M., Cardon, G., Savelsbergh, G., & Lenoir, M. (2017). The implications of low-quality bicycle paths on the gaze behavior of young learner cyclists. Transportation Research Part F: Traffic Psychology and Behavior, 48, 52–60.

Wang, K., & Chen, Y. J. (2020). Joint analysis of the impacts of built environment on bikeshare station capacity and trip attractions. Journal of Transport Geography, 82, 102603.

Wang, R., Feng, Z., Pearce, J., Yao, Y., Li, X., & Liu, Y. (2021). The distribution of greenspace quantity and quality and their association with neighborhood socioeconomic conditions in Guangzhou, China: A new approach using deep learning method and street view images. Sustainable Cities and Society, 66, 102664.

Wang, R., Liu, Y., Lu, Y., Zhang, J., Liu, P., Yao, Y., & Grekousis, G. (2019). Perceptions of built environment and health outcomes for older Chinese in Beijing: A big data approach with street view images and deep learning technique. Computers, Environment and Urban Systems, 78, 101386.

Wang, R., Lu, Y., Wu, X., Liu, Y., & Yao, Y. (2020). Relationship between eye-level greenness and cycling frequency around metro stations in Shenzhen, China: A big data approach. Sustainable Cities and Society, 59, 102201.

Wang, Z., Cheng, L., Li, Y., & Li, Z. (2020). Spatiotemporal characteristics of bike-sharing usage around rail transit stations: Evidence from Beijing, China. Sustainability 12, 1299.

Weliwitiya, H., Rose, G., & Johnson, M. (2019). Bicycle train intermodality: Effects of demography, station characteristics and the built environment. Journal of Transport Geography, 74, 395–404.

Wu, C., Chung, H., Liu, Z., & Kim, I. (2021). Examining the effects of the built environment on topological properties of the bike-sharing network in Suzhou, China. International Journal of Sustainable Transportation, 15(SI1), 338–350.

Wu, C., Kim, I., & Chung, H. (2021). The effects of built environment spatial variation on bike-sharing usage: A case study of Suzhou, China. Cities, 110, 103063.

Wu, X., Lu, Y., Gong, Y., Kang, Y., Yang, L., & Gou, Z. (2021). The impacts of the built environment on bicycle-metro transfer trips: A new method to delineate metro catchment area based on people’s actual cycling space. Journal of Transport Geography, 97, 103215.

Wu, X., Lu, Y., Lin, Y., & Yang, Y. (2019). Measuring the destination accessibility of cycling transfer trips in metro station areas: A big data approach. International Journal of Environmental Research and Public Health, 16(15), 2641.

Xu, Y., Chan, F. K. S., Johnson, M., Stanton, T., He, J., Jia, T., … & Yang, J. (2021). Microplastic pollution in Chinese urban rivers: The influence of urban factors. Resources, Conservation and Recycling, 173, 105686.

Yang, L., Liu, J., Lu, Y., Ao, Y., Guo, Y., Huang, … & Wang, R. (2020). Global and local associations between urban greenery and travel propensity of older adults in Hong Kong. Sustainable Cities and Society, 63, 102442.

Yang, Y., Guo, J., & Sun, S. (2021). Tourism demand forecasting and tourists’ search behavior: Evidence from segmented Baidu search volume. Data Science and Management, 4, 1–9.

Zhang, H., Zhuge, C., Jia, J., Shi, B., & Wang, W. (2021). Green travel mobility of dockless bike-sharing based on trip data in big cities: A spatial network analysis. Journal of Cleaner Production, 313, 127930.

Zhang, S., Zhang, W., Wang, Y., Zhao, X., Song, P., Tian, G., & Mayer, A. L. (2020). Comparing human activity density and green space supply using the Baidu heat map in Zhengzhou, China. Sustainability, 12(17), 7075.

Zhang, X., Shen, Y., & Zhao, J. (2021). The mobility pattern of dockless bike sharing: A four-month study in Singapore. Transportation Research Part D: Transport and Environment, 98, 102961.

Zhang, Y., Thomas, T., Brussel, M., & van Maarseveen, M. (2017). Exploring the impact of built-environment factors on the use of public bikes at bike stations: Case study in Zhongshan, China. Journal of Transport Geography, 58, 59–70.

Zhao, D., Ong, G. P., Wang, W., & Zhou, W. (2021). Estimating public bicycle trip characteristics with consideration of built environment data. Sustainability, 13(2), 500.

Zhao, P., & Li, S. (2017). Bicycle-metro integration in a growing city: The determinants of cycling as a transfer mode in metro station areas in Beijing. Transportation Research Part A: Policy and Practice, 99, 46–60.

Zuo, T., Wei, H., & Rohne, A. (2018). Determining transit service coverage by non-motorized accessibility to transit: Case study of applying GPS data in Cincinnati metropolitan area. Journal of Transport Geography, 67, 1–11.