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Understanding pedestrian movement using urban sensing technologies: the promise of audio-based sensors
5 references·1 citing·24 second hop
Understanding pedestrian movement using urban sensing technologies: the promise of audio-based sensors (2024)Understanding pedestrian movement using u…Mobile phone data for informing public health actions across the COVID-19 pandemic life cycle (2020)Mobile phone data for informi…Activity-Based Human Mobility Patterns Inferred from Mobile Phone Data: A Case Study of Singapore (2016)Activity-Based Human Mobility…Methods and Technologies for Pedestrian and Bicycle Volume Data Collection (2014)Methods and Technologies for …Understanding individual human mobility patterns (2008)Understanding individual huma…Mobile Landscapes: Using Location Data from Cell Phones for Urban Analysis (2006)Mobile Landscapes: Using Loca…Analysis of Spatial Aggregation and Activity of the Urban Population of Almaty Based on Cluster Analysis (2025)Analysis of Spatial Aggregati…The origin of bursts and heavy tails in human dynamics (2005)The scaling laws of human travel (2006)Limits of Predictability in Human Mobility (2010)Friendship and mobility (2011)A universal model for mobility and migration patterns (2012)Me++ (2003)Me++: The Cyborg Self and the Networked City (2003)Dynamic population mapping using mobile phone data (2014)A survey of results on mobile phone datasets analysis (2015)Human mobility: Models and applications (2018)WHAT ABOUT PEOPLE IN REGIONAL SCIENCE? (1970)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)Extracting Dynamic Urban Mobility Patterns from Mobile Phone Data (2012)High resolution population estimates from telecommunications data (2015)Understanding aggregate human mobility patterns using passive mobile phone location data: a home-based approach (2015)Performance Evaluation and Correction Functions for Automated Pedestrian and Bicycle Counting Technologies (2016)Random parameter models for estimating statewide daily bicycle counts using crowdsourced data (2020)Sources and Applications of Emerging Active Travel Data: A Review of the Literature (2021)Evaluating the effect of demographic factors, socioeconomic factors, and risk aversion on mobility during the COVID-19 epidemic in France under lockdown: a population-based study (2020)Emerging COVID-19 impacts, responses, and lessons for building resilience in the seafood system (2021)A survey on deep learning for human mobility (2023)
this work references cited by second hop

References

  • 2008Understanding individual human mobility patterns6,071 cited
  • 2006Mobile Landscapes: Using Location Data from Cell Phones for Urban Analysis865 cited
  • 2020Mobile phone data for informing public health actions across the COVID-19 pandemic life cycle630 cited
  • 2016Activity-Based Human Mobility Patterns Inferred from Mobile Phone Data: A Case Study of Singapore472 cited
  • 2014Methods and Technologies for Pedestrian and Bicycle Volume Data Collection35 cited

Cited by

  • 2025Analysis of Spatial Aggregation and Activity of the Urban Population of Almaty Based on Cluster Analysis5 cited

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