This dataset describes counterfactual public transport networks that were simulated for 36 world cities, and the aggregate data discussed in the paper in which these data are published.
UNIT OF MEASURE: Meters of network length.
RESOLUTION: 1:1000000.
COMPLETENESS: 100%.
POLICY CONTEXT: Regional and urban policies.
METHODOLOGY: Network expansion modelling.
DATA SOURCES: FUA boundaries and population sizes according to 1km GHSL population grids (release 2019).
LEVEL OF AGGREGATION: cities defined on population density clusters.
UNCERTAINTY AND LIMITATIONS: Data based on simulation exercise with the explicit aim of creating counterfactual networks.
Jacobs Crisioni Chris,Kucas Andrius, Dijkstra Lewis (2026): Simulated world-city public transport networks. European Commission, Joint Research Centre [Dataset] doi: 10.2905/JRC.06BCN0G PID: http://data.europa.eu/89h/eb8e348f-dc93-415a-9998-fb10f1787ba2
Network analysisTransport network simulationWorld cities
The downloadable file is a zip file containing an ESRI shapefile and also an excel file with the main results of the analysis.
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One argument for containing urban densities is that cities need a critical population density to sustain sufficiently available public transportation. However, the question of whether denser cities foster shorter public transport networks empirically is problematic because real-world transport nets are a product of many additional factors presumably not related to urban form. This paper adopts a network expansion simulation approach to generate and analyze counterfactual data on network lengths for 36 world cities, in which all networks are generated with similar expansion restrictions and objectives. Denser cities are found to have shorter simulated public transport networks, regardless of the tested model parameters. This provides additional proof that densities are needed to facilitate the provision of proximate public transport infrastructure, with potentially self-reinforcing effects.
| From date | To date |
|---|---|
| 2019-01-01 | 2019-12-31 |
