Zeyin Chen , Renlu Qiao , Siying Li , Shiqi Zhou , Xiuning Zhang , Zhiqiang Wu , Tao Wu
{"title":"Heat and mobility: Machine learning perspectives on bike-sharing resilience in Shanghai","authors":"Zeyin Chen , Renlu Qiao , Siying Li , Shiqi Zhou , Xiuning Zhang , Zhiqiang Wu , Tao Wu","doi":"10.1016/j.trd.2025.104692","DOIUrl":null,"url":null,"abstract":"<div><div>Global climate change has increased extreme heat events, impacting urban mobility, particularly bike-sharing. This study examines the urban mobility resilience (UMR) of bike-sharing to extreme heat in Shanghai’s urban center, analyzing how the built environment and other factors influence UMR through machine learning. The model has an explanatory power of 73.5% and 63.7% on weekdays and weekends. Results indicate that extreme heat has a stronger effect on weekends. Key factors like development intensity, public transportation accessibility, and functional diversity positively affect resilience, with building density increases from 0 to 0.3 promoting UMR by nearly 0.1 (out of 1). Proximity to metro stations (within 1,000–1,500 m) also promotes resilience. The reasonable aggregation of socio-economic factors can also effectively enhance resilience. However, greening and road density sometimes play a negative role. The research provides more references for urban planners and managers to customize strategies to enhance UMR in the context of climate change.</div></div>","PeriodicalId":23277,"journal":{"name":"Transportation Research Part D-transport and Environment","volume":"142 ","pages":"Article 104692"},"PeriodicalIF":7.3000,"publicationDate":"2025-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Transportation Research Part D-transport and Environment","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1361920925001026","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENVIRONMENTAL STUDIES","Score":null,"Total":0}
引用次数: 0
Abstract
Global climate change has increased extreme heat events, impacting urban mobility, particularly bike-sharing. This study examines the urban mobility resilience (UMR) of bike-sharing to extreme heat in Shanghai’s urban center, analyzing how the built environment and other factors influence UMR through machine learning. The model has an explanatory power of 73.5% and 63.7% on weekdays and weekends. Results indicate that extreme heat has a stronger effect on weekends. Key factors like development intensity, public transportation accessibility, and functional diversity positively affect resilience, with building density increases from 0 to 0.3 promoting UMR by nearly 0.1 (out of 1). Proximity to metro stations (within 1,000–1,500 m) also promotes resilience. The reasonable aggregation of socio-economic factors can also effectively enhance resilience. However, greening and road density sometimes play a negative role. The research provides more references for urban planners and managers to customize strategies to enhance UMR in the context of climate change.
期刊介绍:
Transportation Research Part D: Transport and Environment focuses on original research exploring the environmental impacts of transportation, policy responses to these impacts, and their implications for transportation system design, planning, and management. The journal comprehensively covers the interaction between transportation and the environment, ranging from local effects on specific geographical areas to global implications such as natural resource depletion and atmospheric pollution.
We welcome research papers across all transportation modes, including maritime, air, and land transportation, assessing their environmental impacts broadly. Papers addressing both mobile aspects and transportation infrastructure are considered. The journal prioritizes empirical findings and policy responses of regulatory, planning, technical, or fiscal nature. Articles are policy-driven, accessible, and applicable to readers from diverse disciplines, emphasizing relevance and practicality. We encourage interdisciplinary submissions and welcome contributions from economically developing and advanced countries alike, reflecting our international orientation.