With the expansion of the service scope, the complexity of the subway network continues to increase. The most obvious feature is the increase in the number of stations. Therefore, understanding the similarity of land use around subway stations and the development degree of surrounding areas and the distribution of supporting facilities are of great significance to the study of the future planning and construction of stations. POI data is an important basis for analyzing land use around subway stations. This paper proposes a method for quantifying the POI indicators of stations based on the TF-IDF algorithm, and on this basis, performs cluster analysis to find stations with similar land use properties. Finally, taking the Beijing subway network as an example, the classification results of different types of stations are explained.

CICTP