Rail transportation plays a crucial role in improving travel efficiency and reducing traffic congestion. Due to the concentration of resources, Dongcheng and Xicheng districts in Beijing City face serious traffic congestion, a higher working population compared to residents, and significant commuting pressure which makes green commuting through rail transportation becoming essential for daily life. The convenience and user-friendliness of slow mobility systems around rail stations influence the travel experience and comfort of people on the move. It is also an important aspect of the current urban renewal and rail transportation upgrades in Beijing. Therefore, this study focuses on evaluating the slow mobility systems around rail stations for Dongcheng and Xicheng. This paper utilizes internet and spatial big data to establish a slow mobility evaluation framework, including indicators such as station vitality, population coverage, surrounding environment, accessibility, and detour coefficient by using developed program, FME, GIS network built and analysis methods.