基于客流特征的北京地铁站点类型识别

地铁站点是城市各种社会经济活动的关键节点,不同类型的地铁站点在城市中的区域条件、交通功能、土地利用类型等方面均存在差异,科学的站点分类有助于了解城市功能分区及评价轨道交通基础设施建设状况。本文基于2013年3月份14天工作日地铁刷卡客流量数据,运用引入客流特征的时间序列聚类方法,对北京市195个地铁站点进行分类。研究表明：①地铁站点客流量存在时空差异,也是城市功能分区时空差异的表现之一。②通过引入客流特征的时间序列方法,将地铁站点分为居住导向型、就业导向型、职住错位型、错位偏居住型、错位偏就业型、混合型、综合型及其他型8种不同类型。③利用地铁站点客流量数据,是将空间行为和实体空间进行关联比较的有效途径。

Classification of subway stations in Beijing based on passenger flow characteristics

In cities there is a high concentration of social and economic activities at subway stations. Different types of subway stations have different functions, as reflected in their regional characteristics, traffic function, and land use. Meaningful station classification helps to understand urban functional partition and evaluate rail transportation infrastructure development. Based on the usage data of subway passes, this study classified the subway stations with time series clustering. The result shows that (1) subway station passenger flows have clear temporal and spatial differences. It reflects the temporal and spatial differences of urban functional partitions; (2) this study uses a time series clustering method. By considering passenger flow characteristics, subway stations can be divided into residential-oriented stations, employment-oriented stations, spatial mismatched stations, mixed mainly residential-oriented stations, mixed mainly employment-oriented stations, mixed type stations, commerce- and attraction-oriented stations, and other stations; (3) Using traffic data at subway stations is an effective way to compare spatial behavior and physical space.