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Metropolitan Planning Organizations’ Uses of and Needs for Big Data
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References

  • 2015Origin–destination trips by purpose and time of day inferred from mobile phone data637 cited
  • 2016The promises of big data and small data for travel behavior (aka human mobility) analysis580 cited
  • 2014Development of origin–destination matrices using mobile phone call data508 cited
  • 2016A Big Data Analytics Method for Tourist Behaviour Analysis392 cited
  • 2011A GPS/GIS method for travel mode detection in New York City293 cited
  • 2020Disaster resilience through big data: Way to environmental sustainability197 cited
  • 2013Using Data From the Web to Predict Public Transport Arrivals Under Special Events Scenarios109 cited
  • 2020Emerging data for pedestrian and bicycle monitoring: Sources and applications97 cited
  • 2017Quantifying and visualizing jobs-housing balance with big data: A case study of Shanghai94 cited
  • 2018Spatial variation of self-containment and jobs-housing balance in Shenzhen using cellphone big data91 cited
  • 2020A Review of Big Data Applications in Urban Transit Systems79 cited
  • 2020Exploring new ways of visitor tracking using big data sources: Opportunities and limits of passive mobile data for tourism71 cited
  • 2017Inferring social influence in transport mode choice using mobile phone data70 cited
  • 2014Building a validation measure for activity-based transportation models based on mobile phone data

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58 cited
  • 2020Mobile phone data in urban bicycle-sharing: Market-oriented sub-area division and spatial analysis on emission reduction potentials58 cited
  • 2021A data-driven travel mode share estimation framework based on mobile device location data44 cited
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