城市轨道交通站点影响范围内土地利用对客流影响具有时空分异特征且存在类型差异，为针对性探讨不同站点两者的复杂非线性关系，提出一种基于土地利用空间分布规律、对站点实际影响范围进行差异化识别的方法；并通过分时段多尺度地理加权回归，获取能够表征土地利用对客流影响时空变化特征的站点聚类指标，采用K-means++算法将研究区域内的站点划分为4类；进而基于改进的梯度提升决策树模型分类定量探讨不同类别下土地利用与轨道交通客流的复杂非线性关系。研究表明：通过捕捉不同站点土地利用与客流的时空分异特征对站点进行分类识别，可有效提升两者非线性关系模型的解释度。根据模型输出结果，发现不同类别站点影响轨道交通客流的关键土地利用要素不同，第1类中关键变量为相对重要性分别为61.35%和30.08%的公交站点数量和慢行密度；第4类的情况类似但相对数值有所变化，公交站点数量的相对重要性由61.35%下降至30.31%；建筑密度在第2类中以66.57%的相对重要度占据最大比例；但在第3类中仅占5.59%。此外，不同类别站点影响范围内土地利用与轨道交通客流的关系存在较为显著且各异的阈值效应。研究表明，对于不同类别站点的用地开发应各有侧重，且应结合实际将土地利用设计指标控制在相应的合理范围内。研究为差异化的站点周边土地利用开发策略的制定提供了理论支持和量化指导。

The impact of land use on passenger flow within the influence scope of urban rail transit stations has different spatiotemporal differentiation characteristics. To explore the complex nonlinear relationship between land use and passenger flow at different stations, this paper proposed a differentiation identification method based on the spatial distribution of land use variables, and through time-phased multiscale geographic weighted regression, station clustering indicators that can characterize the spatiotemporal changing characteristics of land use impact on passenger flow were obtained. K-means++ algorithm was used to divide the stations into four categories, and the complex nonlinear relationship between land use and railway passenger flow under different categories was explored based on the improved gradient boosting decision tree model. Research shows that the accuracy of nonlinear model can be effectively improved by capturing the spatiotemporal heterogeneity of the relationship between the land use and passenger flow and classifying the stations properly. According to the output results, the key factors are different for each category. For the first category, the bus station number and sidewalk density have top relative importance value of 61.35% and 30.08% respectively; the key factors are the same for the fourth, but with an importance value decreasing from 61.35% to 30.31% for the bus station number. For the second category, the building densityhas the greatest impact with a relative ratio of 66.57%, and on the contrary, which only accounts for 5.59% for the third one. Meanwhile, there are significant and varying threshold effects on the relationship between land use and rail transit passenger flow. The result shows that different types of stations should put different emphasis on land use development, and land use design indicators should be controlled within a reasonable range. This research will provide theoretical support and quantitative guidance for the formulation of differentiated land use development strategies around stations.