<p>The COVID-19 pandemic has had a tremendous impact on the lives and travel of all humans, which to some extent has changed human travel behavior of the metro. Therefore, the primary objective of this study was to investigate the spatial-temporal evolutionary characteristics of metro travel behavior in the pre, peri, and post-COVID-19 pandemic periods. Firstly, the stations were categorized into four groups based on passenger flow characteristics, using the K-means algorithm, and the functionality of each category was defined. Secondly, the change between origin-destination (OD) passenger flow and average travel distance of passengers (ATDP) in different COVID-19 periods was analyzed using metro smart card data. Thirdly, the study quantitatively analyzed the relationship between the changes in ATPD of subway passengers and the surrounding land use using the Multiscale Geographically Weighted Regression (MGWR) method and examined the spatial distribution heterogeneity of the local influencing variables. The results demonstrate that the ATDP for all stations decreased dramatically in the peri-COVID-19. Meanwhile, the distribution of OD passenger flows shows the least fluctuation between residential-oriented stations and the fastest recovery of OD passenger flows in the post-COVID-19 period. The analysis results of these changes provide valuable theoretical and empirical support for the implementation of effective epidemic control measures in the post-COVID-19 era and for addressing potential future public health crises in the metro system.</p>