10-01, 12:00–12:30 (Europe/London), Create 1
This talk shows how TfL Cycle Hire data and the Mapbox Directions API can be used to estimate shared bike journeys. With H3 spatial aggregation and visualisation in QGIS and Tableau Public, the analysis reveals common routes, hotspots, and infrastructure needs.
In the open data and urban mobility ecosystem, GPS traces are often unavailable or difficult to access. This talk introduces a reproducible workflow that addresses this limitation by inferring realistic cycling routes from trip origins and destinations using the Mapbox Directions API.
The workflow is developed in Python and covers data preparation, API integration, and geometry transformation. It produces both estimated routes and spatial aggregations with H3 indexing. Results are then visualised in QGIS and Tableau Public for interactive exploration. The project demonstrates how combining open data and accessible tools can generate actionable insights for city planners, policymakers, and researchers interested in sustainable transport.
Yuchi Lai is a Transportation Policy and Analytics Associate at Lime, dedicated to understanding and improving how people move through cities. She earned an MSc in Urban Data Science and Analytics from the University of Leeds, where she developed expertise in spatial analysis, urban systems, and applied data science.