With the continuous development of urban construction in China, major cities have gradually formed relatively well-developed transportation networks. These well-developed networks have increased the frequency of resident travel, while resident Points of Interest (POI) can, to some extent, reflect passenger flow patterns. Consequently, the application of POI data in urban rail transit research has become more extensive, providing a novel perspective for revealing the functional characteristics surrounding stations and the influencing factors on passenger flow. This study selected 289 subway stations in Shanghai as research subjects. By establishing three-tiered buffer zones—1 km (core area), 1.5 km (primary buffer), and 2 km (secondary buffer)—the correlation between the quantity of eight types of POI and rail transit passenger flow was analyzed. The Spearman correlation coefficient was used to verify the strength of the correlation between facility density and passenger flow within different radial distances. Grouped tests were conducted based on station operational characteristics (terminal stations, major transfer stations, ordinary stations) and passenger flow periods (weekdays/holidays). To address the non-linear characteristics of the relationship between POI and passenger flow, Locally Weighted Scatterplot Smoothing (LOWESS) was introduced to analyze the trend of marginal effects on passenger flow as the quantity of different POI types increases. Finally, correlation analyses for terminal stations, major transfer stations, and ordinary stations revealed that the associations between passenger flow and POI primarily exhibit the following characteristic distribution patterns: a ‘U-shaped’ pattern, threshold effects, and the law of diminishing marginal effects.