As one of the most important modes of public transportation, subway plays a key role in people's travel activities. Because of population, road, car ownership and other factors, the subway passenger flow is increasing day by day. The analysis of influencing factors of subway passenger flow has become a necessary research issue. In this paper, using the data of subway card swipe and Baidu POI, the spatio-temporal relationship between urban subway passenger volume and surrounding building environment is explored. In this study, the relationship between weekend passenger flow, weekend passenger flow and building environment is compared and analyzed by using GTWR model. Firstly, we test the spatial nonstationarity of sample data, and find that compared with the traditional GWR and least squares (OLS) model, GTWR model has better fitting effect because it considers both spatial and temporal factors. In addition, the subway passenger flow is divided into weekend passenger flow and weekend passenger flow, and the space-time relationship between them and the building environment is analyzed and compared. The results obtained by weighted regression of space-time and geography enhance the understanding of station-level passenger flow and surrounding building environment, which is of great significance to urban metro planning.

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