为响应北京地铁站周边用地一体化、打造轨道微中心的理念，本研究利用多源大数据，从公共客流、路网设计、人口密度和用地多样性等方面提取了23个影响因素，定量地刻画站点慢行影响区内的建成环境及出行特征，其中重点考虑了共享单车的接驳特征。为了弥补以往以出行者的步行时间确定轨道站点影响范围的不足，提出了融合主成分分析和K-均值聚类的站点分类模型去划定慢行影响区的范围。以北京市为例，站点影响区被分为4簇：接驳低效-连通度弱-居住主导型，接驳高效-连通度高-均衡型，接驳高效-连通度弱-混合型，接驳高效-连通度高-工作主导型。为了验证聚类的合理性，利用空间自相关的方法判断簇内指标的空间依赖性，结果显示簇1、3、4的空间分布与随机模式没有显著的差异，而簇2接驳高效-连通度高-均衡型站点在空间上存在一定的自相关特性。最后，基于聚类结果定义了轨道站点的慢行影响范围，分别为2 000、1 600、1 600、1 700 m。不同轨道站点类型慢行影响范围的明确，有助于城市规划者确定轨道微中心的建设范围，也可为以公共交通为主导的城市模式开发奠定基础。

In response to the concept of land-use integration and creating micro-center around metro station in Beijing, this study extracted 23 quantitative indicators from public passenger flow, road network design, population density and land diversity to quantitatively analyze the built environment and travel characteristics of the non-motorized influence area based on multi-source big data. The connection characteristics of shared bicycles were taken into particular consideration. In order to compensate for the shortcomings of determining the influence range of metro stations by the traveler’s walking time, a classification model incorporating principal component analysis and K-means clustering was proposed to define the non-motorized influence area. Taking Beijing as an example, the study divided the metro stations into 4 clusters: inefficient connection-weak connectivity-residence oriented, efficient connection-high connectivity-balanced, efficient connection-weak connectivity-mixed, and efficient connection-high connectivity-work oriented. In order to verify the rationality of the clustering, the spatial auto-correlation was used to judge the spatial dependence of indicators. The results show that the spatial distributions of clusters 1, 3 and 4 do not differ significantly from the random model, while cluster 2 efficient connection-high connectivity-balanced stations has auto-correlation characteristics in space. Finally, based on the clustering results, the non-motorized influence areas of the metro stations were delineated as 2 000, 1 600, 1 600, and 1 700 m, respectively. The clarification of the non-motorized influence range of different metro station types can help urban planners determine the scope of micro-center construction and also lay the foundation for transport-oriented development of urban in the future.