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Do human mobility network analyses produced from different location-based data sources yield similar results across scales?
16 references·3 citing·43 second hop
Do human mobility network analyses produced from different location-based data sources yield similar results across scales? (2023)Do human mobility network analyses produc…The universal visitation law of human mobility (2021)The universal visitation law …Using Mobile Device Data to Estimate Visitation in Parks and Protected Areas: An Example from the Nature Reserve of Orange County, California (2019)Using Mobile Device Data to E…Extracting trips from multi-sourced data for mobility pattern analysis: An app-based data example (2019)Extracting trips from multi-s…A Data Science Framework for Movement (2019)A Data Science Framework for …Correlation Coefficients: Appropriate Use and Interpretation (2018)Correlation Coefficients: App…Analyzing large-scale human mobility data: a survey of machine learning methods and applications (2018)Analyzing large-scale human m…Accessibility Inequality in Houston (2018)Accessibility Inequality in H…Understanding the Representativeness of Mobile Phone Location Data in Characterizing Human Mobility Indicators (2017)Understanding the Representat…Activity-Based Human Mobility Patterns Inferred from Mobile Phone Data: A Case Study of Singapore (2016)Activity-Based Human Mobility…Understanding aggregate human mobility patterns using passive mobile phone location data: a home-based approach (2015)Understanding aggregate human…Uncovering urban human mobility from large scale taxi GPS data (2015)Uncovering urban human mobili…Uncovering the spatial structure of mobility networks (2015)Uncovering the spatial struct…Estimating human trajectories and hotspots through mobile phone data (2014)Estimating human trajectories…Unravelling daily human mobility motifs (2013)Unravelling daily human mobil…Modelling the scaling properties of human mobility (2010)Modelling the scaling propert…Understanding individual human mobility patterns (2008)Understanding individual huma…From biases to opportunities: leveraging Location-Based-Service (LBS) data for next-generation transportation planning (2025)From biases to opportunities:…Comparative analysis of human mobility patterns: utilizing taxi and mobile (SafeGraph) data to investigate neighbourhood-scale mobility in New York City (2025)Comparative analysis of human…A Comparison of Tourists’ Spatial–Temporal Behaviors Between Location-Based Service Data and Onsite GPS Tracks (2025)A Comparison of Tourists’ Spa…Reality mining: sensing complex social systems (2005)Limits of Predictability in Human Mobility (2010)Origin–destination trips by purpose and time of day inferred from mobile phone data (2015)Returners and explorers dichotomy in human mobility (2015)The promises of big data and small data for travel behavior (aka human mobility) analysis (2016)Modelling Transport (2011)A Tale of Many Cities: Universal Patterns in Human Urban Mobility (2012)Comparing and modelling land use organization in cities (2015)Understanding individual routing behaviour (2016)The statistical physics of cities (2019)WHAT ABOUT PEOPLE IN REGIONAL SCIENCE? (1970)What about people in Regional Science? (1970)Data from mobile phone operators: A tool for smarter cities? (2014)Traffic zone division based on big data from mobile phone base stations (2015)Urban magnetism through the lens of geo-tagged photography (2015)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)Place and Placelessness (1978)Understanding the bias of call detail records in human mobility research (2016)Improving automobile insurance ratemaking using telematics: incorporating mileage and driver behaviour data (2018)Evaluating spatial accessibility to healthcare services under travel time uncertainty: A reliability-based floating catchment area approach (2020)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)STATISTICAL METHODS FOR ASSESSING AGREEMENT BETWEEN TWO METHODS OF CLINICAL MEASUREMENT (1986)Thirteen Ways to Look at the Correlation Coefficient (1988)Statistics corner: A guide to appropriate use of correlation coefficient in medical research. (2012)Sensitivity analysis methods in the biomedical sciences (2020)Conducting correlation analysis: important limitations and pitfalls (2021)Statistics From A (Agreement) to Z (z Score): A Guide to Interpreting Common Measures of Association, Agreement, Diagnostic Accuracy, Effect Size, Heterogeneity, and Reliability in Medical Research (2021)Growth in Cities (1992)The Spatial Economy (1999)Future directions in human mobility science (2023)Human mobility networks reveal increased segregation in large cities (2023)Resilience patterns of human mobility in response to extreme urban floods (2023)A survey of results on mobile phone datasets analysis (2015)Human mobility: Models and applications (2018)Exploring Human Mobility Patterns in Urban Scenarios: A Trajectory Data Perspective (2018)Spatiotemporal distribution characteristics and mechanism analysis of urban population density: A case of Xi'an, Shaanxi, China (2018)Spatial-temporal distribution of carbon emissions by daily travel and its response to urban form: A case study of Hangzhou, China (2020)
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References

  • 2018Correlation Coefficients: Appropriate Use and Interpretation10,949 cited
  • 2008Understanding individual human mobility patterns6,071 cited
  • 2010Modelling the scaling properties of human mobility1,286 cited
  • 2013Unravelling daily human mobility motifs584 cited
  • 2016Activity-Based Human Mobility Patterns Inferred from Mobile Phone Data: A Case Study of Singapore472 cited
  • 2021The universal visitation law of human mobility428 cited
  • 2015Uncovering urban human mobility from large scale taxi GPS data280 cited
  • 2014Estimating human trajectories and hotspots through mobile phone data212 cited
  • 2015Uncovering the spatial structure of mobility networks200 cited
  • 2015Understanding aggregate human mobility patterns using passive mobile phone location data: a home-based approach189 cited
  • 2018Analyzing large-scale human mobility data: a survey of machine learning methods and applications167 cited
  • 2019Extracting trips from multi-sourced data for mobility pattern analysis: An app-based data example81 cited
  • 2017Understanding the Representativeness of Mobile Phone Location Data in Characterizing Human Mobility Indicators55 cited
  • 2019Using Mobile Device Data to Estimate Visitation in Parks and Protected Areas: An Example from the Nature Reserve of Orange County, California

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53 cited
  • 2019A Data Science Framework for Movement47 cited
  • 2018Accessibility Inequality in Houston18 cited
  • Cited by

    • 2025A Comparison of Tourists’ Spatial–Temporal Behaviors Between Location-Based Service Data and Onsite GPS Tracks13 cited
    • 2025From biases to opportunities: leveraging Location-Based-Service (LBS) data for next-generation transportation planning10 cited
    • 2025Comparative analysis of human mobility patterns: utilizing taxi and mobile (SafeGraph) data to investigate neighbourhood-scale mobility in New York City4 cited