准确刻画建成环境与城市轨道交通客流间的作用关系是掌握客流需求的重要前提。针对站间OD研究数据不完备、多维稀疏的问题，提出一种基于车站组团的建成环境与客流间映射关系研究方法，以实现组团OD的精准分析。首先，基于自然地理特性“以团代点”，考虑客流去向特征，计算团间相似度，形成两层的组团划分方法，解决数据稀疏的问题；其次，从O/D组团的吸引能力、OD可达性特征两个维度构造建成环境指标体系及建成环境描述方法；然后，提出一种基于梯度提升回归树（GBDT）模型的刻画建成环境特征和客流之间关系的方法，分析单因素对于客流的影响强度及阈值；最后，以北京地铁为例验证。结果表明：建成环境与轨道交通车站组团间客流存在时空异质性、非线性特征及阈值效应；组团的研究视角有效解决了数据稀疏的问题；OD阻抗特征是影响客流的首要特征，解释度高达38.40%；人口经济特征是次要影响因素，且存在显著的阈值效应。因此，在城市轨道交通规划的过程中，首先要着重关注网络拓扑，优化交通可达性，进而深入考量区域经济活动的影响。研究结果为轨道交通规划者提供定量的分析工具，可以帮助规划者确定建成环境指标的有效范围、调整空间，为提升轨道交通运营效能提供参考。

Accurately characterizing the relationship between the built environment and urban rail transit ridership is an important prerequisite for understanding passenger demand. In response to the challenges of incomplete and high-dimensional sparse data in inter-station OD (origin-destination) studies, this paper proposed a research method of mapping relationship between built environment and ridership at the zone level. Firstly, a two-level station clustering method was developed by replacing individual stations with clusters (“cluster-over-point”) based on natural geographical characteristics and passenger flow destination features. Inter-cluster similarity was calculated to a-ddress the issue of data sparsity. Secondly, a built environment indicator system and corresponding description method were constructed from two dimensions: the attraction capacity of origin or destination clusters and OD acce-ssibility characteristics. Thirdly, a methodology based on the Gradient Boosting Decision Tree (GBDT) model was introduced to characterize the relationship between built environment features and passenger flow, delving into the influence intensity and threshold values of individual factors on passenger flow. Finally, the proposed method was validated using data from the Beijing Subway. Therefore, in the process of urban rail transit planning, priority should be given to optimizing network topology and improving transportation accessibility, followed by a deeper consideration of the impact of regional economic activities. The results show that the mapping relationship between built environment and passenger flow at zone-to-zone level has spatial and temporal heterogeneity, nonlinear characteristics and threshold effects. The zoning-based research perspective effectively addresses issues of data sparsity. OD impedance emerges as the primary feature influencing passenger flow, accounting for up to 38.40% of the explanatory power, while demographic and economic characteristics serve as secondary factors, exhibiting significant threshold effects. Therefore, in the process of urban rail transit planning, priority should be given to optimizing network topology and improving transportation accessibility, fo-llowed by a deeper consideration of the impact of regional economic activities. The research findings provide quantitative analytical tools for rail transit planners, assisting them in identifying the effective ranges of built environment indicators and adjusting spatial configurations. These insights offer valuable references for enhancing the operational efficiency of urban rail systems.