Identifying metro station types based on transfer purposes: An application of bike‐sharing data in Xiamen, China

Abstract

AbstractWith the networking of urban rail transit and the large‐scale development of bike‐sharing, metro and bike‐sharing connection has become the preferred way of daily travel for residents of Xiamen. Current studies mainly identify metro station types based on node and place orientation, lacking behaviour‐based investigation. To fill this gap, this study aims to explore the classification of metro stations based on transfer purposes by combining bike‐sharing and point of interest data in Xiamen, using buffer analysis, kernel density estimation, and DBSCAN clustering algorithm comprehensively. The results indicate the following. (1) Distinct transfer purposes have significant agglomeration characteristics and present poly‐centric spatial pattern, an authentic portrayal of Xiamen's land use function. (2) The heterogeneity of connection flow between different transfer purposes and metro stations is apparent. The distribution of flow and flow direction within the same transfer purpose is also in non‐equilibrium. (3) Based on traffic connection analysis, metro stations are divided into seven types: transportation hub, employment‐oriented, residence‐oriented, job‐housing balance, school‐oriented, traffic‐tourism integration, and business connection types. The obtained results assist in improving the transportation connection environment, perfecting urban land use planning, and enhancing low‐carbon and green travel.