Literature DB >> 27596689

The usefulness of GPS bicycle tracking data for evaluating the impact of infrastructure change on cycling behaviour.

Kristiann C Heesch1, Michael Langdon2.   

Abstract

Issue addressed A key strategy to increase active travel is the construction of bicycle infrastructure. Tools to evaluate this strategy are limited. This study assessed the usefulness of a smartphone GPS tracking system for evaluating the impact of this strategy on cycling behaviour. Methods Cycling usage data were collected from Queenslanders who used a GPS tracking app on their smartphone from 2013-2014. 'Heat' and volume maps of the data were reviewed, and GPS bicycle counts were compared with surveillance data and bicycle counts from automatic traffic-monitoring devices. Results Heat maps broadly indicated that changes in cycling occurred near infrastructure improvements. Volume maps provided changes in counts of cyclists due to these improvements although errors were noted in geographic information system (GIS) geo-coding of some GPS data. Large variations were evident in the number of cyclists using the app in different locations. These variations limited the usefulness of GPS data for assessing differences in cycling across locations. Conclusion Smartphone GPS data are useful in evaluating the impact of improved bicycle infrastructure in one location. Using GPS data to evaluate differential changes in cycling across multiple locations is problematic when there is insufficient traffic-monitoring devices available to triangulate GPS data with bicycle traffic count data. So what? The use of smartphone GPS data with other data sources is recommended for assessing how infrastructure improvements influence cycling behaviour.

Mesh:

Year:  2016        PMID: 27596689     DOI: 10.1071/HE16032

Source DB:  PubMed          Journal:  Health Promot J Austr        ISSN: 1036-1073


  5 in total

1.  Comparing bicyclists who use smartphone apps to record rides with those who do not: implications for representativeness and selection bias.

Authors:  Michael D Garber; Kari E Watkins; Michael R Kramer
Journal:  J Transp Health       Date:  2019-10-25

Review 2.  How has big data contributed to obesity research? A review of the literature.

Authors:  Kate A Timmins; Mark A Green; Duncan Radley; Michelle A Morris; Jamie Pearce
Journal:  Int J Obes (Lond)       Date:  2018-07-18       Impact factor: 5.095

Review 3.  Built Environment Interventions to Increase Active Travel: a Critical Review and Discussion.

Authors:  Rachel Aldred
Journal:  Curr Environ Health Rep       Date:  2019-12

Review 4.  Objectively measuring the association between the built environment and physical activity: a systematic review and reporting framework.

Authors:  Francesca L Pontin; Victoria L Jenneson; Michelle A Morris; Graham P Clarke; Nik M Lomax
Journal:  Int J Behav Nutr Phys Act       Date:  2022-09-14       Impact factor: 8.915

Review 5.  Can big data solve a big problem? Reporting the obesity data landscape in line with the Foresight obesity system map.

Authors:  Michelle A Morris; Emma Wilkins; Kate A Timmins; Maria Bryant; Mark Birkin; Claire Griffiths
Journal:  Int J Obes (Lond)       Date:  2018-09-21       Impact factor: 5.095

  5 in total

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