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Enhancing spatial accuracy of mobile phone data using multi-temporal dasymetric interpolation
16 references·16 citing·35 second hopsampled
Enhancing spatial accuracy of mobile phone data using multi-temporal dasymetric interpolation (2017)Enhancing spatial accuracy of mobile phon…Predicting poverty and wealth from mobile phone metadata (2015)Predicting poverty and wealth…The Data Revolution: Big Data, Open Data, Data Infrastructures & Their Consequences (2014)The Data Revolution: Big Data…The Data Revolution : Big Data, Open Data, Data Infrastructures and Their Consequences (2014)The Data Revolution : Big Dat…Proceedings of the 11th International ISCRAM Conference (2014)Proceedings of the 11th Inter…From mobile phone data to the spatial structure of cities (2014)From mobile phone data to the…Dynamic population mapping using mobile phone data (2014)Dynamic population mapping us…Development of origin–destination matrices using mobile phone call data (2014)Development of origin–destina…A new insight into land use classification based on aggregated mobile phone data (2014)A new insight into land use c…Understanding individual mobility patterns from urban sensing data: A mobile phone trace example (2012)Understanding individual mobi…Understanding individual human mobility patterns (2008)Understanding individual huma…Uncovering individual and collective human dynamics from mobile phone records (2008)Uncovering individual and col…The New Mobilities Paradigm (2006)The New Mobilities ParadigmMobile Landscapes: Using Location Data from Cell Phones for Urban Analysis (2006)Mobile Landscapes: Using Loca…Dasymetric Mapping and Areal Interpolation: Implementation and Evaluation (2001)Dasymetric Mapping and Areal …What about people in Regional Science? (1970)What about people in Regional…WHAT ABOUT PEOPLE IN REGIONAL SCIENCE? (1970)WHAT ABOUT PEOPLE IN REGIONAL…Assessing veracity of big data: An in-depth evaluation process from the comparison of Mobile phone traces and groundtruth data in traffic monitoring (2024)Assessing veracity of big dat…Mobile Phone Data: A Survey of Techniques, Features, and Applications (2023)Mobile Phone Data: A Survey o…A Systematic Review of Mobile Phone Data in Crime Applications: A Coherent Taxonomy Based on Data Types and Analysis Perspectives, Challenges, and Future Research Directions (2023)A Systematic Review of Mobile…New avenues for second home tourism research using big data: prospects and challenges (2022)New avenues for second home t…A 24-hour population distribution dataset based on mobile phone data from Helsinki Metropolitan Area, Finland (2022)A 24-hour population distribu…Spatial interpolation of mobile positioning data for population statistics (2021)Spatial interpolation of mobi…Semantic Enhancement of Human Urban Activity Chain Construction Using Mobile Phone Signaling Data (2021)Semantic Enhancement of Human…Quantifying and Characterizing Urban Leisure Activities by Merging Multiple Sensing Big Data: A Case Study of Nanjing, China (2021)Quantifying and Characterizin…Identifying home locations in human mobility data: an open-source R package for comparison and reproducibility (2021)Identifying home locations in…Probabilistic positioning in mobile phone network and its consequences for the privacy of mobility data (2020)Probabilistic positioning in …Fine-Scale Dasymetric Population Mapping with Mobile Phone and Building Use Data Based on Grid Voronoi Method (2020)Fine-Scale Dasymetric Populat…Exploring Temporal Activity Patterns of Urban Areas Using Aggregated Network-driven Mobile Phone Data: A Case Study of Wuhu, China (2020)Exploring Temporal Activity P…The effect of temporal sampling intervals on typical human mobility indicators obtained from mobile phone location data (2019)The effect of temporal sampli…Data-driven approach to characterize urban vitality: how spatiotemporal context dynamically defines Seoul’s nighttime (2019)Data-driven approach to chara…Population distribution modelling at fine spatio-temporal scale based on mobile phone data (2018)Population distribution model…Analysing spatiotemporal patterns of tourism in Europe at high-resolution with conventional and big data sources (2018)Analysing spatiotemporal patt…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)Computational Social Science (2009)Limits of Predictability in Human Mobility (2010)A survey of results on mobile phone datasets analysis (2015)Human development report 2015: work for human development (2015)Me++ (2003)Me++: The Cyborg Self and the Networked City (2003)Human mobility: Models and applications (2018)Examining the impacts of residential self-selection on travel behavior: A focus on methodologies (2007)Real-Time Urban Monitoring Using Cell Phones: A Case Study in Rome (2010)The promises of big data and small data for travel behavior (aka human mobility) analysis (2016)The universal visitation law of human mobility (2021)Modernity at Large: Cultural Dimensions of Globalization. (1998)Editorial: Mobilities, Immobilities and Moorings (2006)Towards a Politics of Mobility (2010)The Location of Culture (2012)Transport and social exclusion: Where are we now? (2012)The Cultural Politics of Emotion (2014)Estimating wealth effects without expenditure data—or tears: An application to educational enrollments in states of India (2001)Using deep learning and Google Street View to estimate the demographic makeup of neighborhoods across the United States (2017)Economic Growth and Income Inequality (2019)Social physics (2022)International Encyclopedia of Unified Science (1937)Accessibility, equity and health care: review and research directions for transport geographers (2015)Geographical and Temporal Weighted Regression (GTWR) (2015)Space‐Time and Integral Measures of Individual Accessibility: A Comparative Analysis Using a Point‐based Framework (1998)Accessibility evaluation of land-use and transport strategies: review and research directions (2003)Digital turn, digital geographies? (2016)Thinking critically about and researching algorithms (2016)Platformisation (2019)The social power of algorithms (2016)When data is capital: Datafication, accumulation, and extraction (2019)
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References

  • 2008Understanding individual human mobility patterns6,071 cited
  • 2006The New Mobilities Paradigm5,633 cited
  • 1970WHAT ABOUT PEOPLE IN REGIONAL SCIENCE?3,414 cited
  • 1970What about people in Regional Science?1,584 cited
  • 2014The Data Revolution: Big Data, Open Data, Data Infrastructures & Their Consequences1,463 cited
  • 2014Dynamic population mapping using mobile phone data908 cited
  • 2006Mobile Landscapes: Using Location Data from Cell Phones for Urban Analysis865 cited
  • 2015Predicting poverty and wealth from mobile phone metadata700 cited
  • 2012Understanding individual mobility patterns from urban sensing data: A mobile phone trace example645 cited
  • 2014The Data Revolution : Big Data, Open Data, Data Infrastructures and Their Consequences608 cited
  • 2008Uncovering individual and collective human dynamics from mobile phone records606 cited
  • 2014Proceedings of the 11th International ISCRAM Conference544 cited
  • 2001Dasymetric Mapping and Areal Interpolation: Implementation and Evaluation516 cited
  • 2014Development of origin–destination matrices using mobile phone call data508 cited
  • 2014From mobile phone data to the spatial structure of cities

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458 cited
  • 2014A new insight into land use classification based on aggregated mobile phone data399 cited
  • Cited by

    • 2018Analysing spatiotemporal patterns of tourism in Europe at high-resolution with conventional and big data sources232 cited
    • 2022A 24-hour population distribution dataset based on mobile phone data from Helsinki Metropolitan Area, Finland65 cited
    • 2019Data-driven approach to characterize urban vitality: how spatiotemporal context dynamically defines Seoul’s nighttime64 cited
    • 2018Population distribution modelling at fine spatio-temporal scale based on mobile phone data46 cited
    • 2019The effect of temporal sampling intervals on typical human mobility indicators obtained from mobile phone location data43 cited
    • 2021Identifying home locations in human mobility data: an open-source R package for comparison and reproducibility41 cited
    • 2023Mobile Phone Data: A Survey of Techniques, Features, and Applications34 cited
    • 2023A Systematic Review of Mobile Phone Data in Crime Applications: A Coherent Taxonomy Based on Data Types and Analysis Perspectives, Challenges, and Future Research Directions33 cited
    • 2021Semantic Enhancement of Human Urban Activity Chain Construction Using Mobile Phone Signaling Data22 cited
    • 2024Assessing veracity of big data: An in-depth evaluation process from the comparison of Mobile phone traces and groundtruth data in traffic monitoring20 cited
    • 2021Spatial interpolation of mobile positioning data for population statistics19 cited
    • 2020Fine-Scale Dasymetric Population Mapping with Mobile Phone and Building Use Data Based on Grid Voronoi Method19 cited
    • 2020Exploring Temporal Activity Patterns of Urban Areas Using Aggregated Network-driven Mobile Phone Data: A Case Study of Wuhu, China18 cited
    • 2020Probabilistic positioning in mobile phone network and its consequences for the privacy of mobility data18 cited
    • 2021Quantifying and Characterizing Urban Leisure Activities by Merging Multiple Sensing Big Data: A Case Study of Nanjing, China18 cited
    • 2022New avenues for second home tourism research using big data: prospects and challenges17 cited