For a none technical overview of the tool setting it in context, see the following article in the October 2020 issue of Railwatch magazine:
- Railfuture (2020, October). Essential tool to aid rail campaigners and politicians to reverse Beeching. Railwatch, 165, 12-13.
The following conference paper gives a useful overview of the SDFT and the underlying station choice and trip end model (note that the web interface discussed in this paper is not part of the open source code):
- Young, M., Blainey, S., Gowland, T., & Nagella, S. (2019). An automated online tool to forecast demand for new railway stations and analyse potential abstraction effects. Paper presented at The 17th Annual Transport Practitioners' Meeting, Oxford, United Kingdom.
Final version | Presentation | Demonstration video
For detailed information about the research underpinning the SDFT, please consult the following PhD dissertation:
- Young, M. (2019). Modelling railway station choice: can probabilistic catchments improve demand forecasts for new stations?. University of Southampton (Transportation Research Group).
To read more about the development of station choice models to improve the definition of station catchments, see the following journal paper:
- Young, M., & Blainey, S. (2018). Development of railway station choice models to improve the representation of station catchments in rail demand models. Transportation Planning and Technology, 41(1), 80-103.