Exploring the catchment area of an urban railway station by using transit card data: Case study in Seoul
place - asia, place - urban, mode - rail, mode - bus, mode - subway/metro, land use - planning, land use - transit oriented development, technology - ticketing systems, technology - passenger information, ridership - behaviour
Automated fare collection, Transit card data, Station catchment area, Transfer pattern, Visualization, Bigdata
To enhance transit ridership, Seoul introduced a transfer discount fare scheme that uses an automated fare collection system in Seoul 2004. The transfer discount fare system records all transfer information between rail and buses in transit smartcard data, which enabled us to explore an urban railway station's catchment area. In this study, we examined the geographic distribution of rail-to-bus transfer trips and their characteristics by using transit smartcard data. Mokdong station in Seoul was used as a case study to demonstrate the benefits of data mining for the depiction and easy evaluation of a station's catchment area. The results showed that the average transfer passenger traveled 1.7 km with five bus stops after boarding to access the business district during the morning peak hour. The cumulative distribution of alighting passengers by bus route helped with inferring the shape and size of the urban railway station's catchment area in each direction and depending on the time of day. We found that reliable transfer travel data constitute valuable information for evaluating an urban railway station's catchment area with respect to the type of land use and will help transit agencies with providing better transit services in terms of enhanced accessibility by changing bus headways and routes, as well as land use planners with evaluating transit-oriented development based on the expanded concept of a metro station's catchment area.
Permission to publish the abstract has been given by Elsevier, copyright remains with them.
Eom, J.K., Choi, J., Park, M.S., & Heo, T. (2019). Exploring the catchment area of an urban railway station by using transit card data: Case study in Seoul. Cities, Vol. 95.