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Using Cellphone Trace Big Data to Analyze Travel Patterns and Behaviors in Urban and Rural Areas in Fresno, California
6 references·0 citing·26 second hop
Using Cellphone Trace Big Data to Analyze Travel Patterns and Behaviors in Urban and Rural Areas in Fresno, California (2022)Using Cellphone Trace Big Data to Analyze…New and emerging data forms in transportation planning and policy: Opportunities and challenges for “Track and Trace” data (2020)New and emerging data forms i…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…Updating origin–destination matrices with aggregated data of GPS traces (2016)Updating origin–destination m…The promises of big data and small data for travel behavior (aka human mobility) analysis (2016)The promises of big data and …Understanding individual mobility patterns from urban sensing data: A mobile phone trace example (2012)Understanding individual mobi…INSIDE THE BLACKBOX: MAKING TRANSPORTATION MODELS WORK FOR LIVABLE COMMUNITIES (1996)INSIDE THE BLACKBOX: MAKING T…Examining the impacts of residential self-selection on travel behavior: A focus on methodologies (2007)Understanding individual human mobility patterns (2008)Real-Time Urban Monitoring Using Cell Phones: A Case Study in Rome (2010)Development of origin–destination matrices using mobile phone call data (2014)The universal visitation law of human mobility (2021)Prospect Theory: An Analysis of Decision under Risk (1979)Prospect theory: An analysis of decision under risk (1988)The theory of planned behavior (1991)Applying mobile phone data to travel behaviour research: A literature review (2017)Coupling mobile phone and social media data: a new approach to understanding urban functions and diurnal patterns (2017)Big data and analytics in hospitality and tourism: a systematic literature review (2021)Nonresponse Rates and Nonresponse Bias in Household Surveys (2006)A spatial econometric model for travel flow analysis and real-world applications with massive mobile phone data (2017)Measuring spatio-temporal accessibility to emergency medical services through big GPS data (2019)Business Dynamics: Systems Thinking and Modeling for a Complex World (2000)Agent-based modeling: Methods and techniques for simulating human systems (2002)CRITICAL QUESTIONS FOR BIG DATA (2012)Mobile Phone Data in Urban Commuting: A Network Community Detection-Based Framework to Unveil the Spatial Structure of Commuting Demand (2020)Review of Transit Data Sources: Potentials, Challenges and Complementarity (2021)The Use of Mobile Assessments for Monitoring Mental Health in Youth: Umbrella Review (2023)A Case Study in Digital Government (2004)Integrating Land Use Issues into Transportation Planning: Scenario Planning (2005)Dynamic modeling to support an integrated analysis among land use change, accessibility and gentrification (2020)Understanding drivers of change in park visitation during the COVID-19 pandemic: A spatial application of Big data (2020)Assessing the validity of mobile device data for estimating visitor demographics and visitation patterns in Yellowstone National Park (2022)Evaluation of GNSS-based Volunteered Geographic Information for assessing visitor spatial distribution within protected areas: A case study of the Bavarian Forest National Park, Germany (2022)
this work references cited by second hop

References

  • 2012Understanding individual mobility patterns from urban sensing data: A mobile phone trace example645 cited
  • 2016The promises of big data and small data for travel behavior (aka human mobility) analysis580 cited
  • 2016Updating origin–destination matrices with aggregated data of GPS traces99 cited
  • 2020New and emerging data forms in transportation planning and policy: Opportunities and challenges for “Track and Trace” data85 cited
  • 2019Using Mobile Device Data to Estimate Visitation in Parks and Protected Areas: An Example from the Nature Reserve of Orange County, California53 cited
  • 1996INSIDE THE BLACKBOX: MAKING TRANSPORTATION MODELS WORK FOR LIVABLE COMMUNITIES35 cited

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