Dong Xiaoyuan, Wang Lining, Du Sen, Qian Bicheng, Wang Jiaxin
School of Architecture and Urban Planning, Lanzhou Jiaotong University, Gansu, Lanzhou, China.
PLoS One. 2025 Jan 30;20(1):e0314050. doi: 10.1371/journal.pone.0314050. eCollection 2025.
The built environment is an important determinant of travel demand and mode choice. Studying the relationship between the built environment and transportation usage can support and assist traffic policy interventions. Previous studies often assumed that this relationship is linear; however, the impact of the built environment on non-motorized travel efficiency may be more complex than the typically modeled linear relationships. This paper focuses on the core area of Chengguan District in Lanzhou City, utilizing multi-source big data including POI, OpenStreetMap, street view images, and built environment data. Using ArcGIS spatial analysis tools combined with the Extreme Gradient Boosting (XGBoost) model, we analyze the non-linear influence mechanisms and threshold effects of the built environment on non-motorized travel efficiency and establish a ranking of the relative importance of all built environment factors. The results indicate that factors such as the branch road/street, land-use mix, land-use density, neighborhood entrance/exit density, bus station density, and dead-end-roads density are key influences on non-motorized travel efficiency. Additionally, based on the non-linear thresholds presented in the partial dependence plots for built environment factors, this paper proposes optimization strategies for small-scale road network patterns, mixed land use, and bus-friendly environments, providing effective threshold ranges and decision-making references for urban planning and traffic management.
建成环境是出行需求和出行方式选择的重要决定因素。研究建成环境与交通使用之间的关系有助于支持和辅助交通政策干预。以往的研究通常认为这种关系是线性的；然而，建成环境对非机动车出行效率的影响可能比典型的线性关系更为复杂。本文聚焦于兰州市城关区核心区域，利用包括兴趣点（POI）、开放街道地图（OpenStreetMap）、街景图像和建成环境数据在内的多源大数据。运用ArcGIS空间分析工具并结合极端梯度提升（XGBoost）模型，我们分析了建成环境对非机动车出行效率的非线性影响机制和阈值效应，并建立了所有建成环境因素相对重要性的排名。结果表明，支路/街道、土地利用混合度、土地利用密度、社区出入口密度、公交站点密度和断头路密度等因素对非机动车出行效率有关键影响。此外，基于建成环境因素的偏依赖图中呈现的非线性阈值，本文提出了小规模道路网络模式、混合土地利用和公交友好型环境的优化策略，为城市规划和交通管理提供了有效的阈值范围和决策参考。
