Understanding nonlinear and synergistic effects of the built environment on urban vibrancy in metro station areas

被引:0
|
作者
Peng J. [1 ]
Hu Y. [1 ]
Liang C. [2 ]
Wan Q. [1 ]
Dai Q. [3 ]
Yang H. [1 ]
机构
[1] School of Urban Design, Wuhan University, Wuhan
[2] Guangdong Guodi Institute of Resources and Environment, Guangzhou
[3] Wuhan Planning & Design Institute (Wuhan Transportation Development Strategy Institute), Wuhan
来源
关键词
Built environment; Different times; Gradient boosting decision tree; Nonlinear effects; Synergistic effects; TOD; Urban vibrancy;
D O I
10.1186/s44147-023-00182-z
中图分类号
学科分类号
摘要
Transit-oriented development (TOD) has long been recognized as a significant model for prospering urban vibrancy. However, most studies on TOD and urban vibrancy do not consider temporal differences or the nonlinear effects involved. This study applies the gradient boosting decision tree (GBDT) model to metro station areas in Wuhan to explore the nonlinear and synergistic effects of the built-environment features on urban vibrancy during different times. The results show that (1) the effects of the built-environment features on the vibrancy around metro stations differ over time; (2) the most critical features affecting vibrancy are leisure facilities, floor area ratio, commercial facilities, and enterprises; (3) there are approximately linear or complex nonlinear relationships between the built-environment features and the vibrancy; and (4) the synergistic effects suggest that multimodal is more effective at leisure-dominated stations, high-density development is more effective at commercial-dominated stations, and mixed development is more effective at employment-oriented stations. The findings suggest improved planning recommendations for the organization of rail transport to improve the vibrancy of metro station areas. © 2023, The Author(s).
引用
收藏
相关论文
共 50 条
  • [31] Exploring the Spatiotemporal Effects of the Built Environment on the Nonlinear Impacts of Metro Ridership: Evidence from Xi'an, China
    Xi, Yafei
    Hou, Quanhua
    Duan, Yaqiong
    Lei, Kexin
    Wu, Yan
    Cheng, Qianyu
    ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION, 2024, 13 (03)
  • [32] Investigating the spatiotemporal pattern between the built environment and urban vibrancy using big data in Shenzhen, China
    Chen, Long
    Zhao, Lingyu
    Xiao, Yang
    Lu, Yi
    COMPUTERS ENVIRONMENT AND URBAN SYSTEMS, 2022, 95
  • [33] Understanding the impact of built environment on metro ridership using open source in Shanghai
    An, Dadi
    Tong, Xin
    Liu, Kun
    Chan, Edwin H. W.
    CITIES, 2019, 93 : 177 - 187
  • [34] Examining Built Environment Effects on Metro Ridership at Station-to-Station Level considering Circle Heterogeneity: A Case Study from Xi'an, China
    Zhang, Siyi
    Li, Ziwei
    Liu, Zixuan
    JOURNAL OF ADVANCED TRANSPORTATION, 2023, 2023
  • [35] The Relationship between Urban Vibrancy and Built Environment: An Empirical Study from an Emerging City in an Arid Region
    Fu, Runde
    Zhang, Xinhuan
    Yang, Degang
    Cai, Tianyi
    Zhang, Yufang
    INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH, 2021, 18 (02) : 1 - 21
  • [36] Revitalizing historic districts: Identifying built environment predictors for street vibrancy based on urban sensor data
    Li, Miaoyi
    Liu, Jixiang
    Lin, Yifei
    Xiao, Longzhu
    Zhou, Jiangping
    CITIES, 2021, 117
  • [37] Nonlinear impacts of urban built environment on freight emissions
    Peng, Tao
    Gan, Mi
    Yao, Zhu
    Yang, Xiaoyuan
    Liu, Xiaobo
    TRANSPORTATION RESEARCH PART D-TRANSPORT AND ENVIRONMENT, 2024, 134
  • [38] Understanding the spatio-temporally heterogeneous effects of built environment on urban travel emissions
    Zhao, Chuyun
    Tang, Jinjun
    Zeng, Yu
    Li, Zhitao
    Gao, Fan
    JOURNAL OF TRANSPORT GEOGRAPHY, 2023, 112
  • [39] Nonlinear and threshold effects of the built environment, road vehicles and air pollution on urban vitality
    Doan, Quang Cuong
    Ma, Jun
    Chen, Shuting
    Zhang, Xiaohu
    LANDSCAPE AND URBAN PLANNING, 2025, 253
  • [40] Nonlinear effects of built environment features on metro ridership: An integrated exploration with machine learning considering spatial heterogeneity
    Liu, Mengyang
    Liu, Yuxuan
    Ye, Yu
    SUSTAINABLE CITIES AND SOCIETY, 2023, 95