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The impact of scale on extracting urban mobility patterns using texture analysis
16 references·2 citing·43 second hop
The impact of scale on extracting urban mobility patterns using texture analysis (2023)The impact of scale on extracting urban m…A survey on deep learning for human mobility (2023)A survey on deep learning for…The promises of big data and small data for travel behavior (aka human mobility) analysis (2016)The promises of big data and …Exploring the capacity of social media data for modelling travel behaviour: Opportunities and challenges (2016)Exploring the capacity of soc…Annals of the American association of geographers (2016)Annals of the American associ…Social Sensing: A New Approach to Understanding Our Socioeconomic Environments (2015)Social Sensing: A New Approac…Revealing travel patterns and city structure with taxi trip data (2015)Revealing travel patterns and…Rethinking big data: A review on the data quality and usage issues (2015)Rethinking big data: A review…A new insight into land use classification based on aggregated mobile phone data (2014)A new insight into land use c…From taxi GPS traces to social and community dynamics (2013)From taxi GPS traces to socia…A universal model for mobility and migration patterns (2012)A universal model for mobilit…Friendship and mobility (2011)Friendship and mobilityLimits of Predictability in Human Mobility (2010)Limits of Predictability in H…The scaling laws of human travel (2006)The scaling laws of human tra…On the Issues of Scale, Resolution, and Fractal Analysis in the Mapping Sciences* (1992)On the Issues of Scale, Resol…The gravity model in transportation analysis : theory and extensions (1990)The gravity model in transpor…The P 1 P 2 D Hypothesis: On the Intercity Movement of Persons (1946)The P 1 P 2 D Hypothesis: On …Geospatial Analytics of Urban Bus Network Evolution Based on Multi-Source Spatiotemporal Data Fusion: A Case Study of Beijing, China (2025)Geospatial Analytics of Urban…The Impact of Scale on Extracting Individual Mobility Patterns from Location-Based Social Media (2024)The Impact of Scale on Extrac…Reality mining: sensing complex social systems (2005)The origin of bursts and heavy tails in human dynamics (2005)Understanding individual human mobility patterns (2008)Explanation in Geography (1969)Explanation in Geography (1970)Scale, Sovereignty, and Strategy in Environmental Governance (2005)There’s nothing inherent about scale: political ecology, the local trap, and the politics of development in the Brazilian Amazon (2005)Scale in GIS: An overview (2010)Modifiable Areal Unit Problem (2017)Growth, innovation, scaling, and the pace of life in cities (2007)Geo-located Twitter as proxy for global mobility patterns (2014)A survey of results on mobile phone datasets analysis (2015)Human mobility: Models and applications (2018)Modelling the scaling properties of human mobility (2010)Incorporating spatial interaction patterns in classifying and understanding urban land use (2015)Uncovering urban human mobility from large scale taxi GPS data (2015)Spatial-temporal distribution of carbon emissions by daily travel and its response to urban form: A case study of Hangzhou, China (2020)Birds of a Feather: Homophily in Social Networks (2001)Power-Law Distributions in Empirical Data (2009)Modeling User Activity Preference by Leveraging User Spatial Temporal Characteristics in LBSNs (2014)Predicting the Next Location: A Recurrent Model with Spatial and Temporal Contexts (2016)DeepMove (2018)Power-law distributions in empirical data (2018)Space and Place: The Perspective of Experience. (1978)Citizens as sensors: the world of volunteered geography (2007)Crowdsourcing geographic information for disaster response: a research frontier (2010)Measuring human perceptions of a large-scale urban region using machine learning (2018)GeoAI: spatially explicit artificial intelligence techniques for geographic knowledge discovery and beyond (2019)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)The Production of Space (1992)Local Indicators of Spatial Association—LISA (1995)Decolonization is not a metaphor (2012)Digital turn, digital geographies? (2016)What is data justice? The case for connecting digital rights and freedoms globally (2017)From extractivism to global extractivism: the evolution of an organizing concept (2022)Push-Pull Migration Laws (1983)Global labor flow network reveals the hierarchical organization and dynamics of geo-industrial clusters (2019)Social physics (2022)
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References

  • 2010Limits of Predictability in Human Mobility3,230 cited
  • 2011Friendship and mobility2,912 cited
  • 2006The scaling laws of human travel2,207 cited
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  • 1946The P 1 P 2 D Hypothesis: On the Intercity Movement of Persons1,033 cited
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  • 2016Annals of the American association of geographers762 cited
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  • 2015Revealing travel patterns and city structure with taxi trip data408 cited
  • 1992On the Issues of Scale, Resolution, and Fractal Analysis in the Mapping Sciences*404 cited
  • 2014A new insight into land use classification based on aggregated mobile phone data399 cited
  • 1990The gravity model in transportation analysis : theory and extensions354 cited
  • 2023A survey on deep learning for human mobility282 cited
  • 2013From taxi GPS traces to social and community dynamics253 cited
  • 2016Exploring the capacity of social media data for modelling travel behaviour: Opportunities and challenges

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253 cited
  • 2015Rethinking big data: A review on the data quality and usage issues236 cited
  • Cited by

    • 2024The Impact of Scale on Extracting Individual Mobility Patterns from Location-Based Social Media4 cited
    • 2025Geospatial Analytics of Urban Bus Network Evolution Based on Multi-Source Spatiotemporal Data Fusion: A Case Study of Beijing, China4 cited