Evaluation of the Veloway 1: A natural experiment of new bicycle infrastructure in Brisbane, Australia

Heesch, Kristiann C.; James, B; Washington, Tracy L.; Zuniga, Kelly Draper; Burke, Matthew

doi:10.1016/j.jth.2016.06.006

Cited by 44 publications

(50 citation statements)

References 32 publications

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“…Intercept surveys are brief surveys administered to cyclists at events or by stopping them while they are cycling. Recent work 41 suggests that combining Strava data with intercept survey data results in a more rigorous evaluation of the impact of infrastructure improvements on cycling behaviour than would the use of either data source alone. Intercept surveys are useful for capturing individual demographic and trip details (e.g.…”

Section: Discussionmentioning

confidence: 99%

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

Heesch

Langdon

2016

Health Prom J of Aust

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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.

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Section: Discussionmentioning

confidence: 99%

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

Heesch

Langdon

2016

Health Prom J of Aust

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“…GPS-enabled mobile devices, such as smartphones, allow individuals to track and map their cycling routes [13,14,15,16]. More recently, crowdsourced cycling data are used to analyze cycling behavior [13,17] and make associations between cycling and health [9]. Strava is a popular website used to track users’ cycling and running activity via GPS-enabled devices, such as smart phones and smart watches.…”

Section: Introductionmentioning

confidence: 99%

“…For instance, knowing where people like to cycle could help policymakers to improve cycling infrastructure more effectively (e.g., availability of cycle parking in areas of high demand) and promote road safety by giving priority to roads where there are more cycling trips. In several recent studies, Strava data has been used to map ridership over a city [13], evaluate the impact of bicycle infrastructure on cycling behavior [17], and investigate impacts of residential and employment density, land use diversity, cycling facilities and terrain on cycling behavior [9]. …”

Section: Introductionmentioning

confidence: 99%

Utilizing Crowdsourced Data for Studies of Cycling and Air Pollution Exposure: A Case Study Using Strava Data

Sun

Mobasheri

2017

IJERPH

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With the development of information and communications technology, user-generated content and crowdsourced data are playing a large role in studies of transport and public health. Recently, Strava, a popular website and mobile app dedicated to tracking athletic activity (cycling and running), began offering a data service called Strava Metro, designed to help transportation researchers and urban planners to improve infrastructure for cyclists and pedestrians. Strava Metro data has the potential to promote studies of cycling and health by indicating where commuting and non-commuting cycling activities are at a large spatial scale (street level and intersection level). The assessment of spatially varying effects of air pollution during active travel (cycling or walking) might benefit from Strava Metro data, as a variation in air pollution levels within a city would be expected. In this paper, to explore the potential of Strava Metro data in research of active travel and health, we investigate spatial patterns of non-commuting cycling activities and associations between cycling purpose (commuting and non-commuting) and air pollution exposure at a large scale. Additionally, we attempt to estimate the number of non-commuting cycling trips according to environmental characteristics that may help identify cycling behavior. Researchers who are undertaking studies relating to cycling purpose could benefit from this approach in their use of cycling trip data sets that lack trip purpose. We use the Strava Metro Nodes data from Glasgow, United Kingdom in an empirical study. Empirical results reveal some findings that (1) when compared with commuting cycling activities, non-commuting cycling activities are more likely to be located in outskirts of the city; (2) spatially speaking, cyclists riding for recreation and other purposes are more likely to be exposed to relatively low levels of air pollution than cyclists riding for commuting; and (3) the method for estimating of the number of non-commuting cycling activities works well in this study. The results highlight: (1) a need for policymakers to consider how to improve cycling infrastructure and road safety in outskirts of cities; and (2) a possible way of estimating the number of non-commuting cycling activities when the trip purpose of cycling data is unknown.

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“…To protect user privacy, Strava Metro anonymized and aggregated users' traces to streets of each city. Strava Metro data is of high potential in a wide range of applications, including mapping cycling activities over cities (Jesticoa et al, 2016), assessing effects of environmental factors on cycling behavior (Griffin and Jiao, 2015;Heesch et al, 2016) and assessing air pollution during cycling (Sun and Mobasheri, 2017). Moreover, by comparing cyclist counts between Strava data and manual count data in count stations, some studies have revealed that Strava Metro data is a good representation of cycling population (Jesticoa et al, 2016;Herrero, 2016).…”

Section: Introductionmentioning

confidence: 99%

Exploring Potential of Crowdsourced Geographic Information in Studies of Active Travel and Health: Strava Data and Cycling Behaviour

Sun¹

2017

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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In development of sustainable transportation and green city, policymakers encourage people to commute by cycling and walking instead of motor vehicles in cities. One the one hand, cycling and walking enables decrease in air pollution emissions. On the other hand, cycling and walking offer health benefits by increasing people's physical activity. Earlier studies on investigating spatial patterns of active travel (cycling and walking) are limited by lacks of spatially fine-grained data. In recent years, with the development of information and communications technology, GPS-enabled devices are popular and portable. With smart phones or smart watches, people are able to record their cycling or walking GPS traces when they are moving. A large number of cyclists and pedestrians upload their GPS traces to sport social media to share their historical traces with other people. Those sport social media thus become a potential source for spatially fine-grained cycling and walking data. Very recently, Strava Metro offer aggregated cycling and walking data with high spatial granularity. Strava Metro aggregated a large amount of cycling and walking GPS traces of Strava users to streets or intersections across a city. Accordingly, as a kind of crowdsourced geographic information, the aggregated data is useful for investigating spatial patterns of cycling and walking activities, and thus is of high potential in understanding cycling or walking behavior at a large spatial scale. This study is a start of demonstrating usefulness of Strava Metro data for exploring cycling or walking patterns at a large scale.

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Evaluation of the Veloway 1: A natural experiment of new bicycle infrastructure in Brisbane, Australia

Cited by 44 publications

References 32 publications

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

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

Utilizing Crowdsourced Data for Studies of Cycling and Air Pollution Exposure: A Case Study Using Strava Data

Exploring Potential of Crowdsourced Geographic Information in Studies of Active Travel and Health: Strava Data and Cycling Behaviour

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