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Determination of Urban Traveling Patterns With High Spatial and Temporal Resolution by Using GPS Cell Phone Data
16 references·0 citing·34 second hop
Determination of Urban Traveling Patterns With High Spatial and Temporal Resolution by Using GPS Cell Phone Data (2024)Determination of Urban Traveling Patterns…A data-driven approach for origin–destination matrix construction from cellular network signalling data: a case study of Lyon region (France) (2020)A data-driven approach for or…Mobile phone records to feed activity-based travel demand models: MATSim for studying a cordon toll policy in Barcelona (2019)Mobile phone records to feed …Applying mobile phone data to travel behaviour research: A literature review (2017)Applying mobile phone data to…Transportation Planning Handbook (2016)Transportation Planning Handb…Activity-Based Human Mobility Patterns Inferred from Mobile Phone Data: A Case Study of Singapore (2016)Activity-Based Human Mobility…Origin–destination trips by purpose and time of day inferred from mobile phone data (2015)Origin–destination trips by p…Quantifying travel behavior for infectious disease research: a comparison of data from surveys and mobile phones (2014)Quantifying travel behavior f…From traces to trajectories: How well can we guess activity locations from mobile phone traces? (2014)From traces to trajectories: …Development of origin–destination matrices using mobile phone call data (2014)Development of origin–destina…Estimating Origin-Destination Flows Using Mobile Phone Location Data (2011)Estimating Origin-Destination…Real-Time Urban Monitoring Using Cell Phones: A Case Study in Rome (2010)Real-Time Urban Monitoring Us…Generating Trajectories from Mobile Phone Data (2010)Generating Trajectories from …Processing Raw Data from Global Positioning Systems without Additional Information (2009)Processing Raw Data from Glob…Understanding individual human mobility patterns (2008)Understanding individual huma…Cellular-Based Data-Extracting Method for Trip Distribution (2006)Cellular-Based Data-Extractin…Applications of New Technologies in Travel Surveys (2006)Applications of New Technolog…The origin of bursts and heavy tails in human dynamics (2005)The scaling laws of human travel (2006)Friendship and mobility (2011)A Theoretical Foundation for the Gravity Equation. (1979)Understanding individual mobility patterns from urban sensing data: A mobile phone trace example (2012)A new insight into land use classification based on aggregated mobile phone data (2014)Nonresponse Rates and Nonresponse Bias in Household Surveys (2006)A universal model for mobility and migration patterns (2012)The promises of big data and small data for travel behavior (aka human mobility) analysis (2016)WHAT ABOUT PEOPLE IN REGIONAL SCIENCE? (1970)Limits of Predictability in Human Mobility (2010)Measures of Human Mobility Using Mobile Phone Records Enhanced with GIS Data (2015)A data driven method for OD matrix estimation (2019)The impact of COVID-19 pandemic on public transport usage and route choice: Evidences from a long-term tracking study in urban area (2021)Modelling the scaling properties of human mobility (2010)Unravelling daily human mobility motifs (2013)The path most traveled: Travel demand estimation using big data resources (2015)Elimination of the Travel Diary: Experiment to Derive Trip Purpose from Global Positioning System Travel Data (2001)Learning transportation mode from raw gps data for geographic applications on the web (2008)Route choice of cyclists in Zurich (2010)A GPS/GIS method for travel mode detection in New York City (2011)Using Global Positioning Systems in Health Research (2011)Travel and the Built Environment (2010)On data processing required to derive mobility patterns from passively-generated mobile phone data (2017)Human mobility and socioeconomic status: Analysis of Singapore and Boston (2018)Measuring inequality in community resilience to natural disasters using large-scale mobility data (2021)Big data: The next frontier for innovation, competition, and productivity (2011)Transport mode detection based on mobile phone network data: A systematic review (2019)An investigation of information alignment and collaboration as complements to supply chain agility in humanitarian supply chain (2020)Exploring the spatiotemporal patterns and correlates of urban vitality: Temporal and spatial heterogeneity (2023)Quantifying seasonal population fluxes driving rubella transmission dynamics using mobile phone data (2015)Using Google Location History data to quantify fine-scale human mobility (2018)Computational socioeconomics (2019)A survey of results on mobile phone datasets analysis (2015)
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References

  • 2008Understanding individual human mobility patterns6,071 cited
  • 2015Origin–destination trips by purpose and time of day inferred from mobile phone data637 cited
  • 2010Real-Time Urban Monitoring Using Cell Phones: A Case Study in Rome623 cited
  • 2011Estimating Origin-Destination Flows Using Mobile Phone Location Data511 cited
  • 2014Development of origin–destination matrices using mobile phone call data508 cited
  • 2016Activity-Based Human Mobility Patterns Inferred from Mobile Phone Data: A Case Study of Singapore472 cited
  • 2017Applying mobile phone data to travel behaviour research: A literature review368 cited
  • 2009Processing Raw Data from Global Positioning Systems without Additional Information326 cited
  • 2014From traces to trajectories: How well can we guess activity locations from mobile phone traces?164 cited
  • 2014Quantifying travel behavior for infectious disease research: a comparison of data from surveys and mobile phones142 cited
  • 2006Applications of New Technologies in Travel Surveys134 cited
  • 2016Transportation Planning Handbook125 cited
  • 2019Mobile phone records to feed activity-based travel demand models: MATSim for studying a cordon toll policy in Barcelona69 cited
  • 2020A data-driven approach for origin–destination matrix construction from cellular network signalling data: a case study of Lyon region (France)

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68 cited
  • 2006Cellular-Based Data-Extracting Method for Trip Distribution63 cited
  • 2010Generating Trajectories from Mobile Phone Data60 cited
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