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Crowdsourcing Bicycle Volumes: Exploring the role of volunteered geographic information and established monitoring methods
1 references·16 citing·46 second hop
Crowdsourcing Bicycle Volumes: Exploring the role of volunteered geographic information and established monitoring methods (2019)Crowdsourcing Bicycle Volumes: Exploring …Prospects for VGI Research and the Emerging Fourth Paradigm (2012)Prospects for VGI Research an…A review of bike volume prediction studies (2024)A review of bike volume predi…Estimating daily bicycle counts with Strava data in rural and urban locations (2023)Estimating daily bicycle coun…Leveraging the spatial-temporal resolution of crowdsourced cycling data to improve the estimation of hourly bicycle volume (2022)Leveraging the spatial-tempor…Exploring Data Fusion Techniques to Estimate Network-Wide Bicycle Volumes (2022)Exploring Data Fusion Techniq…Changes in the Representativeness of Strava Bicycling Data during COVID-19 (2022)Changes in the Representative…Sources and Applications of Emerging Active Travel Data: A Review of the Literature (2021)Sources and Applications of E…Public participation geographic information system (PPGIS) as a method for active travel data acquisition (2021)Public participation geograph…Challenges and Opportunities of Emerging Data Sources to Estimate Network-Wide Bike Counts (2021)Challenges and Opportunities …Random parameter models for estimating statewide daily bicycle counts using crowdsourced data (2020)Random parameter models for e…Modeling bicycle volume using crowdsourced data from Strava smartphone application (2020)Modeling bicycle volume using…Mitigating Bias in Big Data for Transportation (2020)Mitigating Bias in Big Data f…GPS-data in bicycle planning: “Which cyclist leaves what kind of traces?” Results of a representative user study in Germany (2020)GPS-data in bicycle planning:…Digital Platform/Mobile App to Boost Cycling for the Promotion of Sustainable Mobility in Mid-Sized Starter Cycling Cities (2020)Digital Platform/Mobile App t…Characterizing cycling traffic fluency using big mobile activity tracking data (2020)Characterizing cycling traffi…What can volunteered geographic information tell us about the different ways mountain bikers, runners and walkers use urban reserves? (2019)What can volunteered geograph…Bicycle choice modeling: A study of university trips in a small Colombian city (2018)Bicycle choice modeling: A st…A Computer Movie Simulating Urban Growth in the Detroit Region (1970)Citizens as sensors: the world of volunteered geography (2007)Big data: The next frontier for innovation, competition, and productivity (2011)L ocation B ased S ocial N etworks – Definition, Current State of the Art and Research Agenda (2013)Models of direct editing of government spatial data: challenges and constraints to the acceptance of contributed data (2016)Assessing VGI Data Quality (2017)Discrete Choice Methods with Simulation (2003)The Mixed Logit model: The state of practice (2003)Making Cycling Irresistible: Lessons from The Netherlands, Denmark and Germany (2008)Analisis Pemilihan Moda Transportasi Dengan Metode Discrete Choice Model (Studi Kasus: Bandara Internasional Soekarno Hatta) (2019)Ride to the hills, ride to your school: Physical effort and mode choice (2021)Natural area tourism: ecology, impacts and management (2013)Using social media to quantify nature-based tourism and recreation (2013)Meta-analysis on Associations Between the Built Environment and Mobile Physical Activity Using Volunteered Geographic Information (2024)Applied Thematic Analysis (2012)The Uncertain Geographic Context Problem (2012)Conducting Semi‐Structured Interviews (2015)Climate Change, Environmental Disasters, and Health Inequities: The Underlying Role of Structural Inequalities (2022)Promoting transportation cycling for women: The role of bicycle infrastructure (2007)Bike-sharing: History, Impacts, Models of Provision, and Future (2009)Promoting Cycling for Transport: Research Needs and Challenges (2014)Mobile Technology and Studies on Transport Behavior: A Literature Analysis, Integrated Research Model, and Future Research Agenda (2021)Using environmental audits and photo-journeys to compare objective attributes and bicyclists’ perceptions of bicycle routes (2021)The influence of personal and public health and smart applications on biking behavior in South Korea (2022)A GPS-based bicycle route choice model for San Francisco, California (2011)Crowdsourcing, citizen sensing and sensor web technologies for public and environmental health surveillance and crisis management: trends, OGC standards and application examples (2011)Where do cyclists ride? A route choice model developed with revealed preference GPS data (2012)A systematic scoping review of methods for estimating link-level bicycling volumes (2022)Estimation of daily bicycle traffic using machine and deep learning techniques (2022)The use of crowdsourced mobile data in estimating pedestrian and bicycle traffic: A systematic review (2024)Big Data and Cycling (2015)Mapping ridership using crowdsourced cycling data (2016)The world’s user-generated road map is more than 80% complete (2017)Four Types of Cyclists? (2013)Modelling bicycle route choice in German cities using open data, MNL and the bikeSim web-app (2021)Cyclist’s waiting time estimation at intersections, a case study with GPS traces from Bologna (2022)Collecting population-representative bike-riding GPS data to understand bike-riding activity and patterns using smartphones and Bluetooth beacons (2024)Bikeshare: A Review of Recent Literature (2015)The effect of COVID-19 and subsequent social distancing on travel behavior (2020)Complex interventions to reduce car use and change travel behaviour: An umbrella review. (2023)Pedestrian street and its effect on economic sustainability of a historical Middle Eastern city: The case of Chaharbagh Abbasi in Isfahan, Iran (2023)Strava Metro Data (2024)Environment and Planning b: Planning and Design (1998)Developing a framework for assessment of the environmental determinants of walking and cycling (2003)Evaluating the Potential of Crowdsourced Data to Estimate Network-Wide Bicycle Volumes (2023)Using emerging mobility data to advocate equitable micromobility infrastructure in underserved communities (2023)
this work references cited by second hop

References

  • 2012Prospects for VGI Research and the Emerging Fourth Paradigm100 cited

Cited by

  • 2019What can volunteered geographic information tell us about the different ways mountain bikers, runners and walkers use urban reserves?77 cited
  • 2020Mitigating Bias in Big Data for Transportation42 cited
  • 2020Modeling bicycle volume using crowdsourced data from Strava smartphone application33 cited
  • 2021Sources and Applications of Emerging Active Travel Data: A Review of the Literature28 cited
  • 2020Digital Platform/Mobile App to Boost Cycling for the Promotion of Sustainable Mobility in Mid-Sized Starter Cycling Cities27 cited
  • 2020Random parameter models for estimating statewide daily bicycle counts using crowdsourced data27 cited
  • 2020GPS-data in bicycle planning: “Which cyclist leaves what kind of traces?” Results of a representative user study in Germany26 cited
  • 2018Bicycle choice modeling: A study of university trips in a small Colombian city20 cited
  • 2022Exploring Data Fusion Techniques to Estimate Network-Wide Bicycle Volumes19 cited
  • 2021Challenges and Opportunities of Emerging Data Sources to Estimate Network-Wide Bike Counts17 cited
  • 2023Estimating daily bicycle counts with Strava data in rural and urban locations16 cited
  • 2020Characterizing cycling traffic fluency using big mobile activity tracking data16 cited

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  • 2021Public participation geographic information system (PPGIS) as a method for active travel data acquisition16 cited
  • 2022Changes in the Representativeness of Strava Bicycling Data during COVID-1914 cited
  • 2022Leveraging the spatial-temporal resolution of crowdsourced cycling data to improve the estimation of hourly bicycle volume14 cited
  • 2024A review of bike volume prediction studies14 cited