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Simulating human mobility patterns in urban areas
9 references·11 citing·32 second hop
Simulating human mobility patterns in urban areas (2016)Simulating human mobility patterns in urb…Understanding intra-urban trip patterns from taxi trajectory data (2012)Understanding intra-urban tri…Spatiotemporal Patterns of Urban Human Mobility (2012)Spatiotemporal Patterns of Ur…Exploring the mobility of mobile phone users (2012)Exploring the mobility of mob…An empirical study on human mobility and its agent-based modeling (2012)An empirical study on human m…A universal model for mobility and migration patterns (2012)A universal model for mobilit…A Tale of Many Cities: Universal Patterns in Human Urban Mobility (2012)A Tale of Many Cities: Univer…Identifying Important Places in People’s Lives from Cellular Network Data (2011)Identifying Important Places …Understanding individual human mobility patterns (2008)Understanding individual huma…The scaling laws of human travel (2006)The scaling laws of human tra…Examining the impact of urban-rural spatial structure on mobility networks: A case study of taxis (2023)Examining the impact of urban…Understanding mobility dynamics using urban functions during the COVID-19 pandemic: comparison of pre-and post-new normal eras (2022)Understanding mobility dynami…Exploring built environment factors on e-bike travel behavior in urban China: A case study of Jinan (2022)Exploring built environment f…Analysis and Implementation of Human Mobility Behavior Using Similarity Analysis Based on Co-Occurrence Matrix (2022)Analysis and Implementation o…Group travel behavior in metro system and its relationship with house price (2021)Group travel behavior in metr…Prediction of Intra-Urban Human Mobility by Integrating Regional Functions and Trip Intentions (2020)Prediction of Intra-Urban Hum…Identifying Human Mobility Patterns in the Rio de Janeiro Metropolitan Area using Call Detail Records (2020)Identifying Human Mobility Pa…Urban human activity density spatiotemporal variations and the relationship with geographical factors: An exploratory Baidu heatmaps‐based analysis of Wuhan, China (2019)Urban human activity density …A methodology for obtaining objective measurements of population obesogenic behaviors in relation to the environment (2019)A methodology for obtaining o…Detecting and Reducing Biases in Cellular-Based Mobility Data Sets (2018)Detecting and Reducing Biases…There's a Path for Everyone: A Data-Driven Personal Model Reproducing Mobility Agendas (2017)There's a Path for Everyone: …Using GPS to learn significant locations and predict movement across multiple users (2003)Limits of Predictability in Human Mobility (2010)The Mobile Data Challenge: Big Data for Mobile Computing Research (2012)Measuring Large-Scale Social Networks with High Resolution (2014)Urban Sensing Using Mobile Phone Network Data: A Survey of Research (2014)The origin of bursts and heavy tails in human dynamics (2005)Friendship and mobility (2011)Power-Law Distributions in Empirical Data (2009)A survey of results on mobile phone datasets analysis (2015)Understanding Human Mobility from Twitter (2015)The promises of big data and small data for travel behavior (aka human mobility) analysis (2016)Power-law distributions in empirical data (2018)Growth, innovation, scaling, and the pace of life in cities (2007)Geo-located Twitter as proxy for global mobility patterns (2014)Human mobility: Models and applications (2018)Local Indicators of Spatial Association—LISA (1995)Travel demand and the 3Ds: Density, diversity, and design (1997)Travel and the Built Environment (2010)Planning bikeway network for urban commute based on mobile phone data: A case study of Beijing (2023)Deciphering urban cycling: Analyzing the nonlinear impact of street environments on cycling volume using crowdsourced tracker data and machine learning (2025)Spatiotemporal variations of private e-bike trips with explainable data-driven technologies (2025)Uncovering urban human mobility from large scale taxi GPS data (2015)Delineating urban functional areas with building-level social media data: A dynamic time warping (DTW) distance based k-medoids method (2016)Multiscale dynamic human mobility flow dataset in the U.S. during the COVID-19 epidemic (2020)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)Spatiotemporal distribution characteristics and mechanism analysis of urban population density: A case of Xi'an, Shaanxi, China (2018)Correlations and Scaling Laws in Human Mobility (2014)Rich do not rise early: spatio-temporal patterns in the mobility networks of different socio-economic classes (2016)Exploring the heterogeneity of human urban movements using geo-tagged tweets (2020)A review of urban computing for mobile phone traces (2013)The TimeGeo modeling framework for urban mobility without travel surveys (2016)
this work references cited by second hop

References

  • 2008Understanding individual human mobility patterns6,071 cited
  • 2006The scaling laws of human travel2,207 cited
  • 2012A universal model for mobility and migration patterns1,509 cited
  • 2012A Tale of Many Cities: Universal Patterns in Human Urban Mobility628 cited
  • 2011Identifying Important Places in People’s Lives from Cellular Network Data401 cited
  • 2012Understanding intra-urban trip patterns from taxi trajectory data327 cited
  • 2012Spatiotemporal Patterns of Urban Human Mobility282 cited
  • 2012Exploring the mobility of mobile phone users239 cited
  • 2012An empirical study on human mobility and its agent-based modeling57 cited

Cited by

  • 2022Exploring built environment factors on e-bike travel behavior in urban China: A case study of Jinan35 cited
  • 2019Urban human activity density spatiotemporal variations and the relationship with geographical factors: An exploratory Baidu heatmaps‐based analysis of Wuhan, China32 cited
  • 2021Group travel behavior in metro system and its relationship with house price20 cited
  • 2023Examining the impact of urban-rural spatial structure on mobility networks: A case study of taxis14 cited
  • 2017There's a Path for Everyone: A Data-Driven Personal Model Reproducing Mobility Agendas14 cited

Only edges whose both ends are imported exist here. Widen the year window, or show the whole map. Back to the work

  • 2020Identifying Human Mobility Patterns in the Rio de Janeiro Metropolitan Area using Call Detail Records14 cited
  • 2019A methodology for obtaining objective measurements of population obesogenic behaviors in relation to the environment13 cited
  • 2018Detecting and Reducing Biases in Cellular-Based Mobility Data Sets13 cited
  • 2020Prediction of Intra-Urban Human Mobility by Integrating Regional Functions and Trip Intentions10 cited
  • 2022Analysis and Implementation of Human Mobility Behavior Using Similarity Analysis Based on Co-Occurrence Matrix7 cited
  • 2022Understanding mobility dynamics using urban functions during the COVID-19 pandemic: comparison of pre-and post-new normal eras6 cited