Mapping cycling patterns and trends using Strava Metro data in the city of Johannesburg, South Africa

Abstract

Plans for smart mobility through cycling are often hampered by lack of information on cycling patterns and trends, particularly in cities of the developing world such as Johannesburg. Similarly, traditional methods of data collection such as bicycle counts are often expensive, cover a limited spatial extent and not up-to-date. Consequently, the dataset presented in this paper illustrates the spatial and temporal coverage of cycling patterns and trends in Johannesburg for the year 2014 derived from the geolocation based mobile application Strava. To the best knowledge of the authors, there is little or no comprehensive dataset that describes cycling patterns in Johannesburg. Perhaps this dataset is a tool that will support evidence based transportation planning and smart mobility.

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