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Pattern analysis of Japanese long-distance travel change under the COVID-19 pandemic
15 references·3 citing·46 second hop
Pattern analysis of Japanese long-distance travel change under the COVID-19 pandemic (2023)Pattern analysis of Japanese long-distanc…Japanese travel behavior trends and change under COVID-19 state-of-emergency declaration: Nationwide observation by mobile phone location data (2020)Japanese travel behavior tren…How COVID-19 and the Dutch ‘intelligent lockdown’ change activities, work and travel behaviour: Evidence from longitudinal data in the Netherlands (2020)How COVID-19 and the Dutch ‘i…Detection of base travel groups with different sensitivities to new high-speed rail services: Non-negative tensor decomposition approach (2020)Detection of base travel grou…Changes in urban mobility in Sapporo city, Japan due to the Covid-19 emergency declarations (2020)Changes in urban mobility in …Closer to the total? Long-distance travel of French mobile phone users (2017)Closer to the total? Long-dis…Applying mobile phone data to travel behaviour research: A literature review (2017)Applying mobile phone data to…Estimating long-distance travel demand with mobile phone billing data (2016)Estimating long-distance trav…Origin–destination trips by purpose and time of day inferred from mobile phone data (2015)Origin–destination trips by p…From traces to trajectories: How well can we guess activity locations from mobile phone traces? (2014)From traces to trajectories: …An Analysis of Travel Demand in Japan's Intercity Market Empirical Estimation and Policy Simulation (2014)An Analysis of Travel Demand …Deriving Rules for Trip Purpose Identification from GPS Travel Survey Data and Land Use Data: A Machine Learning Approach (2010)Deriving Rules for Trip Purpo…Deriving and validating trip purposes and travel modes for multi-day GPS-based travel surveys: A large-scale application in the Netherlands (2009)Deriving and validating trip …Understanding individual human mobility patterns (2008)Understanding individual huma…Search for a global positioning system device to measure person travel (2007)Search for a global positioni…A study of an integrated intercity travel demand model (2005)A study of an integrated inte…Spatiotemporal Analysis of Human Mobility in Greater Tokyo Area Using Hourly 500 m Mobile Spatial Statistics from 2019 to 2021 (2025)Spatiotemporal Analysis of Hu…Railway-station-area vitality in response to COVID-19: A case study of diverse Japanese cities (2025)Railway-station-area vitality…A comprehensive methodological review of human mobility simulation and modelling: Current trends, challenges, and future directions (2025)A comprehensive methodologica…Elimination of the Travel Diary: Experiment to Derive Trip Purpose from Global Positioning System Travel Data (2001)Evaluating the feasibility of a passive travel survey collection in a complex urban environment: Lessons learned from the New York City case study (2010)Using Geographic Information Systems (GIS) to assess the role of the built environment in influencing obesity: a glossary (2011)Transportation mode-based segmentation and classification of movement trajectories (2012)Collective Choice and Social Welfare (1972)Discrete Choice Analysis: Theory and Application to Travel Demand. (1987)Discrete choice analysis: Theory and application to travel demand (1988)Efficient stated choice experiments for estimating nested logit models (2008)Forecasting passenger travel demand for air and high-speed rail integration service: A case study of Beijing-Guangzhou corridor, China (2016)Impacts of COVID-19 on tourists' destination preferences: Evidence from China (2021)The origin of bursts and heavy tails in human dynamics (2005)The scaling laws of human travel (2006)Friendship and mobility (2011)A universal model for mobility and migration patterns (2012)Can Land-use Policy Really Affect Travel Behaviour? A Study of the Link between Non-work Travel and Land-use Characteristics (1998)GPS tracking in neighborhood and health studies: A step forward for environmental exposure assessment, a step backward for causal inference? (2013)Review of GPS Travel Survey and GPS Data-Processing Methods (2014)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)Activity-Based Human Mobility Patterns Inferred from Mobile Phone Data: A Case Study of Singapore (2016)Travel and the Built Environment (2010)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)The theory of planned behavior (1991)Reconsidering Political and Popular Understandings of the Digital Divide (2004)Transport and social exclusion: Where are we now? (2012)Exploring the impacts of COVID-19 on travel behavior and mode preferences (2020)Public transport planning adaption under the COVID-19 pandemic crisis: literature review of research needs and directions (2020)Modal share changes due to COVID-19: The case of Budapest (2020)The effect of COVID-19 and subsequent social distancing on travel behavior (2020)Impacts of COVID-19 on transportation: Summary and synthesis of interdisciplinary research (2021)Impacts of COVID-19 on urban rail transit ridership using the Synthetic Control Method (2021)How is COVID-19 reshaping activity-travel behavior? Evidence from a comprehensive survey in Chicago (2020)Impacts of COVID-19 on public transport ridership in Sweden: Analysis of ticket validations, sales and passenger counts (2020)Abrupt changes, institutional reactions, and adaptive behaviors: An exploratory study of COVID-19 and related events' impacts on Hong Kong's metro riders (2021)Characterization of COVID-19’s Impact on Mobility and Short-Term Prediction of Public Transport Demand in a Mid-Size City in Spain (2021)Unraveling the dynamic impacts of COVID-19 on metro ridership: An empirical analysis of Beijing and Shanghai, China (2022)
this work references cited by second hop

References

  • 2008Understanding individual human mobility patterns6,071 cited
  • 2020How COVID-19 and the Dutch ‘intelligent lockdown’ change activities, work and travel behaviour: Evidence from longitudinal data in the Netherlands734 cited
  • 2015Origin–destination trips by purpose and time of day inferred from mobile phone data637 cited
  • 2009Deriving and validating trip purposes and travel modes for multi-day GPS-based travel surveys: A large-scale application in the Netherlands501 cited
  • 2017Applying mobile phone data to travel behaviour research: A literature review368 cited
  • 2007Search for a global positioning system device to measure person travel246 cited
  • 2014From traces to trajectories: How well can we guess activity locations from mobile phone traces?164 cited
  • 2005A study of an integrated intercity travel demand model134 cited
  • 2020Changes in urban mobility in Sapporo city, Japan due to the Covid-19 emergency declarations115 cited
  • 2020Japanese travel behavior trends and change under COVID-19 state-of-emergency declaration: Nationwide observation by mobile phone location data83 cited
  • 2014An Analysis of Travel Demand in Japan's Intercity Market Empirical Estimation and Policy Simulation77 cited
  • 2017Closer to the total? Long-distance travel of French mobile phone users71 cited
  • 2010Deriving Rules for Trip Purpose Identification from GPS Travel Survey Data and Land Use Data: A Machine Learning Approach

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57 cited
  • 2020Detection of base travel groups with different sensitivities to new high-speed rail services: Non-negative tensor decomposition approach13 cited
  • 2016Estimating long-distance travel demand with mobile phone billing data12 cited
  • Cited by

    • 2025A comprehensive methodological review of human mobility simulation and modelling: Current trends, challenges, and future directions9 cited
    • 2025Spatiotemporal Analysis of Human Mobility in Greater Tokyo Area Using Hourly 500 m Mobile Spatial Statistics from 2019 to 20214 cited
    • 2025Railway-station-area vitality in response to COVID-19: A case study of diverse Japanese cities4 cited