地理科学进展 ›› 2022, Vol. 41 ›› Issue (2): 251-263.doi: 10.18306/dlkxjz.2022.02.006

• 研究论文 • 上一篇    下一篇

建成环境与青少年步行通学的非线性关系——基于极限梯度提升模型的研究

刘吉祥1(), 肖龙珠2,*(), 周江评1, 郭源园3, 杨林川4   

  1. 1.香港大学建筑学院,香港 999077
    2.香港城市大学工学院,香港 999077
    3.天津大学建筑学院,天津 300072
    4.西南交通大学建筑学院,成都 611756
  • 收稿日期:2021-02-07 修回日期:2021-05-25 出版日期:2022-02-28 发布日期:2022-04-28
  • 通讯作者: *肖龙珠(1988— ),女,福建莆田人,博士生,主要从事交通出行行为与轨道交通导向发展(TOD)研究。E-mail: xiaolongzhuu@163.com
  • 作者简介:刘吉祥(1989— ),男,湖南娄底人,博士生,主要从事城市健康地理与交通出行研究。E-mail: u3004679@connect.hku.hk
  • 基金资助:
    国家社会科学基金重大项目(20ZDA036);四川省儿童保护与发展研究中心2021年重点科研项目(ETBH2021-ZD001)

Non-linear relationships between the built environment and walking to school: Applying extreme gradient boosting method

LIU Jixiang1(), XIAO Longzhu2,*(), ZHOU Jiangping1, GUO Yuanyuan3, YANG Linchuan4   

  1. 1. Faculty of Architecture, The University of Hong Kong, Hong Kong 999077, China
    2. College of Engineering, City University of Hong Kong, Hong Kong 999077, China
    3. School of Architecture, Tianjin University, Tianjin 300072, China
    4. School of Architecture, Southwest Jiaotong University, Chengdu 611756, China
  • Received:2021-02-07 Revised:2021-05-25 Online:2022-02-28 Published:2022-04-28
  • Supported by:
    Major Program of the National Social Science Fund of China(20ZDA036);Key Program of the Center on Child Protection and Development (Sichuan)(ETBH2021-ZD001)

摘要:

步行不仅是一种原始、便捷的交通方式,同时也是体力活动的重要组成部分,对于提升公共健康、改善交通拥堵和减轻污染排放等均有重要的积极意义。然而,包括青少年在内的城市居民步行比例持续下降,体力活动水平日益降低。青少年正处于身心发育的关键时期,体力活动的缺乏将导致肥胖等慢性非传染病,为其将来发展埋下巨大的健康隐患。如何通过对建成环境进行干预,提高青少年步行通学比例,从而提高其体力活动水平,引起了不少学者的关注,取得了较为丰硕的研究成果。然而,既有研究存在以下不足:第一,大部分已有研究以西方城市为案例,很少研究关注中国城市;第二,绝大部分既有研究基于线性或广义线性的假设考察建成环境对步行通学的影响,很少研究关注两者之间的非线性关系。鉴于此,论文以厦门岛为案例,基于极限梯度提升模型,考察青少年家和学校建成环境对其步行通学的影响。研究发现:① 通学距离是影响青少年步行通学最重要的因素,其相对贡献接近4成(39.99%);② 建成环境(以5Ds模型表征)作用显著,家、校建成环境相对贡献合计达36.28%,超过社会经济属性(23.73%),离市中心的距离和道路交叉口密度等变量具有重要作用;③ 全部建成环境变量和主要社会经济属性变量均与青少年步行上学存在非线性关系,且存在明显的阈值效应。研究为城市决策者关于提高青少年步行通学倾向提供了丰富的政策启示。

关键词: 建成环境, 步行通学, 非线性, 梯度提升决策树, 机器学习, 厦门岛

Abstract:

Walking is not only a primitive and convenient transport mode but also an important integrant of physical activity, which is beneficial for the promotion of public health, alleviation of traffic congestion, and mitigation of transportation-induced pollution. In modern China, cities are expanding rapidly, people are enjoying a dramatic improvement in living standards, and the pace of life is accelerating. As a result, urban people, including adolescents, tend to travel in motorized modes increasingly more and walk less. The prevalence of physical inactivity among adolescents has brought about a series of health issues, such as deterioration of physical fitness, obesity, and some non-communicable diseases (for example, diabetes and hypertension). Travel to school is among the most important routine travels for adolescents. Promoting adolescents' propensity of walking to school can effectively help them integrate physical activity into daily life and thus enhance their overall physical activity level. Hence, scholars from diverse disciplines (for example, geography, urban planning, and public health) have been drawn to examine the relationships between the built environment and walking to school. However, the current research is insufficient in the following two aspects. First, the existing research is mainly based on the Western context, whereas few studies have been conducted in China. Second, the majority of existing studies assumed a linear or generalized linear (for example, log-linear) relationship between the built environment and walking to school, and no studies, to the best of our knowledge, have examined the non-linear relationships between them. Therefore, this study, taking Xiamen, China as the case and employing its large-scale travel behavior survey dataset in 2015, explored the non-linear effects of the built environment on adolescents' propensity of walking to school. We applied a state-of-the-art machine learning method, namely extreme gradient boosting method (XGBoost), to fit the model, and interpreted the model with relative importance and partial dependence plots. The results show that: 1) Distance from home to school is the most important factor influencing walking to school, with the relative importance of 39.99%. 2) The built environment, which is characterized by the 5Ds (density, diversity, design, destination accessibility, and distance to transit) model, is an important contributor, and relative contributions of the built environment variables at home and school collectively contributed 36.28% of the model's explanatory power, only second to distance to school, much higher than that of sociodemographic variables (23.73%). Distance to city center and population density around both home and school contribute a great deal. 3) All the built environment variables at both ends of school trips and the key sociodemographic variables have non-linear effects on adolescents' propensity of walking to school, and there exist obvious threshold effects. This study can inform decision makers with nuanced policy insights for promoting adolescents' behavior of walking to school.

Key words: built environment, walking to school, non-linearity, gradient boosting decision tree, machine learning, Xiamen Island, China