This paper addresses the problem of mismatch with the surrounding urban renewal when applying the TOD stationcity integrated development model to domestic rail transit stations. Based on the classic nodeplace (NP) model and the introduced nodeplaceridership (NPR) model with passenger flow, this study takes Xi'an Metro Line 3 as an example. Relying on spatiotemporal big data, passenger flow data within 24 hours for six consecutive months are selected to calculate the basic indicators of 26 stations, which are classified into six categories: placeahead and low ridership, deficient and low ridership, matching and midlow ridership, nodeahead and midhigh ridership, nodeahead and midlow ridership, and saturated nodeahead and high ridership. This results indicate that Xi'an Metro Line 3 has the characteristics of a relatively higher node value and a lower place value. Given the identification of the same characteristics across the six station types, we propose precise matching strategies for placeahead, coordinated, and ahead type stations. Specifically, placeahead stations should prioritize connection with other transportation modes and pedestrian accessibility, coordinated stations should optimize supporting facilities and explore the potential of place features on this basis, and ahead stations should integrate resources to form railway microcenters. These three processoriented transformation measures can be applied to other regions and contribute to improved station function and service.

urban rail transit  /  node-place mode  /  TOD strategy  /  station-city integrated development  /  node-place-ridership