THE POTENTIAL OF STRAVA DATA TO CONTRIBUTE IN NON-MOTORISED TRANSPORT (NMT) PLANNING IN JOHANNESBURG

11 citations as recorded by crossref.

1. Using bicycle app data to develop Safety Performance Functions (SPFs) for bicyclists at intersections: A generic framework C. Chen et al. 10.1016/j.tra.2019.12.034
2. Characteristics of cyclists using fitness tracker apps and its implications for planning of bicycle transport systems K. Kwayu et al. 10.1016/j.cstp.2021.06.004
3. Synergic effects of meteorological factors on urban form-outdoor exercise relationship: A study with crowdsourced data Y. Tian et al. 10.1007/s10109-023-00424-x
4. Understanding Potential Exposure of Bicyclists on Roadways to Traffic-Related Air Pollution: Findings from El Paso, Texas, Using Strava Metro Data K. Lee & I. Sener 10.3390/ijerph16030371
5. Situated data analysis: a new method for analysing encoded power relationships in social media platforms and apps J. Rettberg 10.1057/s41599-020-0495-3
6. A review of factors and benefits of non-motorized transport: a way forward for developing countries U. Mansoor et al. 10.1007/s10668-021-01531-9
7. Examining Associations of Environmental Characteristics with Recreational Cycling Behaviour by Street-Level Strava Data Y. Sun et al. 10.3390/ijerph14060644
8. Crowdsourced cycling data applications to estimate noise pollution exposure during urban cycling R. Wogan & J. Kennedy 10.1016/j.heliyon.2024.e27918
9. Assessing the integration between motorised and non-motorised transport systems: experiences of the Ekurhuleni Municipality, South Africa K. Lawrence et al. 10.1080/21650020.2024.2354905
10. Spatial Integration of Non-Motorized Transport and Urban Public Transport Infrastructure: A Case of Johannesburg B. Risimati et al. 10.3390/su132011461
11. The Spatial Geographies of Women Urban Runners S. Radford & K. Davidson 10.1080/08111146.2024.2401012