211
Views
0
CrossRef citations to date
0
Altmetric
Articles

Comparison of cycling path characteristics in South Florida and North Holland among three GPS fitness tracker apps

ORCID Icon, ORCID Icon, ORCID Icon & ORCID Icon
Pages 804-819 | Received 15 Jun 2020, Accepted 09 Jun 2021, Published online: 20 Jul 2021

References

  • Bikemap. (2020). https://www.bikemap.net/en/about-bikemap/
  • Aldred, R., Goodman, A., Gulliver, J., & Woodcock, J. (2018). Cycling injury risk in London: A case-control study exploring the impact of cycle volumes, motor vehicle volumes, and road characteristics including speed limits. Accident; Analysis and Prevention, 117, 75–84. https://doi.org/10.1016/j.aap.2018.03.003
  • Alivand, M., Hochmair, H. H., & Srinivasan, S. (2015). Analyzing how travelers choose scenic routes using route choice models. Computers, Environment and Urban Systems, 50, 41–52. https://doi.org/10.1016/j.compenvurbsys.2014.10.004
  • Bigazzi, A. Y., & Gehrke, S. R. (2018). Joint consideration of energy expenditure, air quality, and safety by cyclists. Transportation Research Part F: Traffic Psychology and Behaviour, 58, 652–664. https://doi.org/10.1016/j.trf.2018.07.005
  • Blanc, B., Figliozzi, M., & Clifton, K. (2016). How representative of bicycling populations are smartphone application surveys of travel behavior? Transportation Research Record: Journal of the Transportation Research Board, 2587(1), 78–89. https://doi.org/10.3141/2587-10
  • Chen, P., Shen, Q., & Childress, S. (2018). A GPS data-based analysis of built environment influences on bicyclist route preferences. International Journal of Sustainable Transportation, 12(3), 218–231. https://doi.org/10.1080/15568318.2017.1349222
  • Chen, Z., Shen, H. T., & Zhou, X. (2011). Discovering popular routes from trajectories. 2011 IEEE 27th International Conference on Data Engineering, Hannover, Germany (pp. 900–911). https://doi.org/10.1109/ICDE.2011.5767890
  • Dill, J., & Carr, T. (2003). Bicycle commuting and facilities in major U.S. cities: If you build them, commuters will use them. Transportation Research Record: Journal of the Transportation Research Board, 1828(1), 116–123. https://doi.org/10.3141/1828-14
  • Endomondo. (2020). Retrieved March 23, 2020 from https://www.endomondo.com/files/press/Facts_EN.pdf
  • Faskunger, J. (2013). Promoting active living in healthy cities of Europe. Journal of Urban Health, 90(S1), 142–153. https://doi.org/10.1007/s11524-011-9645-7
  • Garber, M. D., Watkins, K. E., & Kramer, M. R. (2019). Comparing bicyclists who use smartphone apps to record rides with those who do not: Implications for representativeness and selection bias. Journal of Transport & Health, 15, 100661. https://doi.org/10.1016/j.jth.2019.100661
  • Goodchild, M. F. (2007). Citizens as voluntary sensors: Spatial data infrastructure in the world of web 2.0. International Journal of Spatial Data Infrastructures Research, 2(2), 24–32. https://doi.org/10.2902/
  • Gotschi, T. (2011). Costs and benefits of bicycling investments in Portland, Oregon. Journal of Physical Activity and Health, 8(s1), S49–S58. https://doi.org/10.1123/jpah.8.s1.s49
  • Griffin, G. P., & Jiao, J. (2015). Where does bicycling for health happen? Analysing volunteered geographic information through place and plexus. Journal of Transport & Health, 2(2), 238–247. https://doi.org/10.1016/j.jth.2014.12.001
  • Handy, S. L., & Xing, Y. (2011). Factors correlated with bicycle commuting: A study in six small U.S. cities. International Journal of Sustainable Transportation, 5(2), 91–110. https://doi.org/10.1080/15568310903514789
  • Haustein, S., Koglin, T., Nielsen, T. A. S., & Svensson, Å. (2020). A comparison of cycling cultures in Stockholm and Copenhagen. International Journal of Sustainable Transportation, 14(4), 280–293. https://doi.org/10.1080/15568318.2018.1547463
  • Heesch, K. C., & Langdon, M. (2016). The usefulness of GPS bicycle tracking data for evaluating the impact of infrastructure change on cycling behaviour: GPS bicycle tracking data in evaluating cycling behaviour. Health Promotion Journal of Australia : Official Journal of Australian Association of Health Promotion Professionals, 27(3), 222–229. https://doi.org/10.1071/HE16032
  • Hochmair, H. H. (2010). Spatial association of geotagged photos with scenic locations. In A. Car, G. Griesebner, & J. Strobl (Eds.), Geospatial Crossroads@GI_Forum ’10 Proceedings of the Geoinformatics Forum (pp. 91–100). Wichmann.
  • Jestico, B., Nelson, T., & Winters, M. (2016). Mapping ridership using crowdsourced cycling data. Journal of Transport Geography, 52, 90–97. https://doi.org/10.1016/j.jtrangeo.2016.03.006
  • Kamargianni, M. (2015). Investigating next generation’s cycling ridership to promote sustainable mobility in different types of cities. Research in Transportation Economics, 53(C), 45–55. https://doi.org/10.1016/j.retrec.2015.10.018
  • Khatri, R., Cherry, C. R., Nambisan, S. S., & Han, L. D. (2016). Modeling route choice of utilitarian bikeshare users with GPS data. Transportation Research Record: Journal of the Transportation Research Board, 2587(1), 141–149. https://doi.org/10.3141/2587-17[Mismatch]
  • Larsen, J., & El-Geneidy, A. (2011). A travel behavior analysis of urban cycling facilities in Montréal, Canada. Transportation Research Part D: Transport and Environment, 16(2), 172–177. https://doi.org/10.1016/j.trd.2010.07.011
  • Lißner, S., Huber, S., Lindemann, P., Anke, J., & Francke, A. (2020). GPS-data in bicycle planning: “Which cyclist leaves what kind of traces?” Results of a representative user study in Germany. Transportation Research Interdisciplinary Perspectives, 7, 100192. https://doi.org/10.1016/j.trip.2020.100192
  • MacFarland, T. W., & Yates, J. M. (2016). Introduction to nonparametric statistics for the biological sciences using R. Springer International Publishing. https://doi.org/10.1007/978-3-319-30634-6
  • MapMyFitness. (2021). Under armour. https://blog.mapmyrun.com/about/about-mapmyfitness/
  • McArthur, D. P., & Hong, J. (2019). Visualising where commuting cyclists travel using crowdsourced data. Journal of Transport Geography, 74, 233–241. https://doi.org/10.1016/j.jtrangeo.2018.11.018
  • Møller, M., & Hels, T. (2008). Cyclists' perception of risk in roundabouts. Accident; Analysis and Prevention, 40(3), 1055–1062. https://doi.org/10.1016/j.aap.2007.10.013
  • Norman, P., & Pickering, C. M. (2017). Using volunteered geographic information to assess park visitation: Comparing three on-line platforms. Applied Geography, 89, 163–172. https://doi.org/10.1016/j.apgeog.2017.11.001
  • Norman, P., & Pickering, C. M. (2019). Factors influencing park popularity for mountain bikers, walkers and runners as indicated by social media route data. Journal of Environmental Management, 249, 109413. https://doi.org/10.1016/j.jenvman.2019.109413
  • Nowrouzian, R., & Srinivasan, S. (2012). Empirical analysis of spatial transferability of tour-generation models. Transportation Research Record: Journal of the Transportation Research Board, 2302(1), 14–22. https://doi.org/10.3141/2302-02
  • Owuor, I., & Hochmair, H. H. (2020). An overview of social media apps and their potential role in geospatial research. ISPRS International Journal of Geo-Information, 9(9), 526. https://doi.org/10.3390/ijgi9090526
  • Pew Research. (2019). Demographics of mobile device ownership and adoption in the United States. Pew Research Center: Internet, Science & Tech. https://www.pewinternet.org/fact-sheet/mobile/
  • Pritchard, R. (2018). Revealed preference methods for studying bicycle route choice—A systematic review. International Journal of Environmental Research and Public Health, 15(3), 470. https://doi.org/10.3390/ijerph15030470
  • Pucher, J., & Buehler, R. (2008). Making cycling irresistible: Lessons from the Netherlands, Denmark and Germany. Transport Reviews, 28(4), 495–528. https://doi.org/10.1080/01441640701806612
  • Romanillos, G., Austwick, M. Z., Ettema, D., & Kruijf, J. D. (2016). Big data and cycling. Transport Reviews, 36(1), 114–133. https://doi.org/10.1080/01441647.2015.1084067
  • Rupi, F., Poliziani, C., & Schweizer, J. (2019). Data-driven bicycle network analysis based on traditional counting methods and GPS traces from smartphone. ISPRS International Journal of Geo-Information, 8(8), 322. https://doi.org/10.3390/ijgi8080322
  • Schepers, P., Twisk, D., Fishman, E., Fyhri, A., & Jensen, A. (2017). The Dutch road to a high level of cycling safety. Safety Science, 92, 264–273. https://doi.org/10.1016/j.ssci.2015.06.005
  • Straub, M., & Graser, A. (2015). Learning from experts: Inferring road popularity from GPS trajectories. GI_Forum, 1, 41–50. https://doi.org/10.1553/giscience2015s41
  • Strelnikova, D. (2017). Comparing the Suitability of Strava and Endomondo GPS Tracking Data for Bicycle Travel Pattern Analysis [B.S.]. Department of Geoinformation & Environmental Technologies, Carinthia University of Applied Sciences.
  • Sun, Y., Fan, H., Bakillah, M., & Zipf, A. (2015). Road-based travel recommendation using geo-tagged images. Computers, Environment and Urban Systems, 53, 110–122. https://doi.org/10.1016/j.compenvurbsys.2013.07.006
  • Watkins, K., Ammanamanchi, R., LaMondia, J., & Le Dantec, C. A. (2016). Comparison of smartphone-based cyclist GPS data sources [Paper presentation]. Transportation Research Board - 95th Annual Meeting, Washington, D.C., Article, No. 16-5309. https://trid.trb.org/view/1393960

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.