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Assessing regression methods to estimate network-wide bicycle traffic volumes based on crowdsourced GPS and permanent counter data
16 references·1 citing·52 second hop
Assessing regression methods to estimate network-wide bicycle traffic volumes based on crowdsourced GPS and permanent counter data (2025)Assessing regression methods to estimate …Bikeability and the induced demand for cycling (2023)Bikeability and the induced d…Generalized model for mapping bicycle ridership with crowdsourced data (2021)Generalized model for mapping…Predicting bicycling and walking traffic using street view imagery and destination data (2020)Predicting bicycling and walk…The evaluation of large cycling infrastructure investments in Glasgow using crowdsourced cycle data (2019)The evaluation of large cycli…Estimating bicycle trip volume for Miami-Dade county from Strava tracking data (2019)Estimating bicycle trip volum…Correcting Bias in Crowdsourced Data to Map Bicycle Ridership of All Bicyclists (2019)Correcting Bias in Crowdsourc…Comparing bicyclists who use smartphone apps to record rides with those who do not: Implications for representativeness and selection bias (2019)Comparing bicyclists who use …Comparing spatial patterns of crowdsourced and conventional bicycling datasets (2018)Comparing spatial patterns of…How Do People Cycle in Amsterdam, Netherlands?: Estimating Cyclists’ Route Choice Determinants with GPS Data from an Urban Area (2017)How Do People Cycle in Amster…A GPS data-based analysis of built environment influences on bicyclist route preferences (2017)A GPS data-based analysis of …Mapping ridership using crowdsourced cycling data (2016)Mapping ridership using crowd…Big Data and Cycling (2015)Big Data and CyclingEstimating Annual Average Daily Bicyclists (2013)Estimating Annual Average Dai…Estimating use of non-motorized infrastructure: Models of bicycle and pedestrian traffic in Minneapolis, MN (2012)Estimating use of non-motoriz…Sustainable Transport in Freiburg: Lessons from Germany's Environmental Capital (2010)Sustainable Transport in Frei…Biketastic (2010)BiketasticUsing citizen observatory GPS data to trace changes in cycling practices: prospects and limitations (2025)Using citizen observatory GPS…Obesity relationships with community design, physical activity, and time spent in cars (2004)Active commuting and cardiovascular risk: A meta-analytic review (2007)Infrastructure, programs, and policies to increase bicycling: An international review (2009)Built environment determinants of bicycle volume: A longitudinal analysis (2017)Providing quantified evidence to policy makers for promoting bike-sharing in heavily air-polluted cities: A mode choice model and policy simulation for Taiyuan-China (2018)Social Justice and the City (1975)Walking, Cycling, and Obesity Rates in Europe, North America, and Australia (2008)Social Justice and the City (2009)Active Travel in Germany and the U.S. (2011)Urban Space Distribution and Sustainable Transport (2016)Transport energy consumption and environmental quality: Does urbanization matter? 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A multilevel regression model using smartphone GPS data (2018)Route choice of bike share users: Leveraging GPS data to derive choice sets (2020)The overreliance on statistical goodness-of-fit and under-reliance on model validation in discrete choice models: A review of validation practices in the transportation academic literature (2020)Environmental correlates of walking and cycling: Findings from the transportation, urban design, and planning literatures (2003)Role of Built Environments in Physical Activity, Obesity, and Cardiovascular Disease (2012)Jupyter Notebooks – a publishing format for reproducible computational workflows (2016)Estimation of Average Annual Daily Bicycle Counts using Crowdsourced Strava Data (2020)Mapping bicycling exposure and safety risk using Strava Metro (2021)Linking objectively measured physical activity with objectively measured urban form (2005)Do the Health Benefits of Cycling Outweigh the Risks? (2010)Travel and the Built Environment (2010)Examining the influence of neighborhood and street-level built environment on fitness jogging in Chengdu, China: A massive GPS trajectory data analysis (2023)Mode choice and the first-/last-mile burden: The moderating effect of street-level walkability (2023)Street view environments are associated with the walking duration of pedestrians: The case of Amsterdam, the Netherlands (2023)Development of Daily Adjustment Factors for Bicycle Traffic (2013)A sinusoidal model for seasonal bicycle demand estimation (2016)
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References

  • 2010Sustainable Transport in Freiburg: Lessons from Germany's Environmental Capital199 cited
  • 2016Mapping ridership using crowdsourced cycling data189 cited
  • 2010Biketastic162 cited
  • 2015Big Data and Cycling160 cited
  • 2012Estimating use of non-motorized infrastructure: Models of bicycle and pedestrian traffic in Minneapolis, MN129 cited
  • 2017A GPS data-based analysis of built environment influences on bicyclist route preferences122 cited
  • 2019Estimating bicycle trip volume for Miami-Dade county from Strava tracking data100 cited
  • 2013Estimating Annual Average Daily Bicyclists91 cited
  • 2020Predicting bicycling and walking traffic using street view imagery and destination data83 cited
  • 2019Correcting Bias in Crowdsourced Data to Map Bicycle Ridership of All Bicyclists78 cited
  • 2021Generalized model for mapping bicycle ridership with crowdsourced data68 cited
  • 2023Bikeability and the induced demand for cycling68 cited
  • 2017How Do People Cycle in Amsterdam, Netherlands?: Estimating Cyclists’ Route Choice Determinants with GPS Data from an Urban Area66 cited
  • 2018Comparing spatial patterns of crowdsourced and conventional bicycling datasets65 cited
  • 2019The evaluation of large cycling infrastructure investments in Glasgow using crowdsourced cycle data

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63 cited
  • 2019Comparing bicyclists who use smartphone apps to record rides with those who do not: Implications for representativeness and selection bias62 cited
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    • 2025Using citizen observatory GPS data to trace changes in cycling practices: prospects and limitations2 cited