This dashboard provides a visualization of the transportation-based typologies for 2384 cities worldwide inferred from a training/test data set and Wikipedia using the sentence-BERT natural language processing model.

The original typologies of the 283 training/test data set used is from a study by Oke et al:
Oke, J.B., Aboutaleb, Y.M., Akkinepally, A., Azevedo, C.L., Han, Y., Zegras, P.C., Ferreira, J. and Ben-Akiva, M.E., 2019. A novel global urban typology framework for sustainable mobility futures. Environmental Research Letters, 14(9), p.095006.

The NLP methodology for inferring typology probabilities and the predicted values were developed as part of a C2SMART project shown here:
Rath, S. and Chow, J.Y., 2022. Worldwide city transport typology prediction with sentence-BERT based supervised learning via Wikipedia. Transportation Research Part C: Emerging Technologies, 139, p.103661.

The data is open access and can be downloaded in original form from:
https://zenodo.org/record/6011886/export/json