建成环境对老年人活力出行的影响——基于极端梯度提升决策树的研究

Non-linear effects of the built environment on elderly’s active travel : An extreme gradient boosting approach

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

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Author(s)

Detail(s)

Original languageChinese (Simplified)
Pages (from-to)102-111
Journal / Publication科技导报
Volume39
Issue number8
Publication statusPublished - 2021

Abstract

活力出行与老年人移动能力、身心健康和生活质量息息相关。以厦门为案例, 采用极端梯度提升决策树模型, 探究建成环境和老年人活力出行之间的非线性关系。研究发现: 出行距离是影响老年人是否活力出行的最重要因素; 建成环境要素的相对重要性远高于社会经济属性; 全部建成环境变量与老年人活力出行之间均存在复杂的非线性关系和"阈值"效应; 出发地和目的地建成环境变量的影响模式存在异同。
The active travel (including walking and cycling) is closely related with elderly's mobility, physical and mental health, and quality of life. Hence, it is of great importance for urban and transportation planners and practitioners to examine the impacts of the built environment on elderly's active travel. Among the rich research findings, the existing research tends to focus on the built environment surrounding the living space (usually the departure place) of the elderly, while ignoring the built environment surrounding the destinations. Moreover, in prior studies, the associations between the built environment and the elderly's active travel are oftentimes assumed to be linear or log-linear. Against this backdrop, this study, taking Xiamen as an example, utilizes one of the latest machine learning method, i.e., the Extreme Gradient Boosting Decision Tree model (XGBoost) to disentangle the complex non-linear relationships between the built environment surrounding both departure places and destinations and elderly's active travel. It is found that (1) the trip distance is the most important factor that impacts elderly's propensity of the active travel; (2) the collective relative importance of the built environment variables is much higher than that of the socio-economic variables; (3) obviously, the associations between all built environment variables and elderly's active travel are non-linear and there exist “threshold” effects; (4) for some built environment variables, their impacts on elderly's active travel differ between the departure places and the destinations, while for the others, they are very similar. This study can provide a knowledge base and rich policy implications for the urban and transportation development and planning in China in the era of aging population.

Research Area(s)

  • built environment, the elderly, active travel, 建成环境, 老年人, 活力出行