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Automatic Identification of the Social Functions of Areas of Interest (AOIs) Using the Standard Hour-Day-Spectrum Approach
16 references·2 citing·45 second hop
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References

  • 1970A Computer Movie Simulating Urban Growth in the Detroit Region9,754 cited
  • 2008Understanding individual human mobility patterns6,071 cited
  • 1995Local Spatial Autocorrelation Statistics: Distributional Issues and an Application3,672 cited
  • 2006The scaling laws of human travel2,207 cited
  • 2012Assuring the quality of volunteered geographic information773 cited
  • 2018Land-use changes and land policies evolution in China’s urbanization processes446 cited
  • 2015Extracting and understanding urban areas of interest using geotagged photos310 cited
  • 2012Land-Use Classification Using Taxi GPS Traces290 cited
  • 2011The scaling of human mobility by taxis is exponential239 cited
  • 2014Inequalities in the London bicycle sharing system revisited: impacts of extending the scheme to poorer areas but then doubling prices210 cited
  • 2018Spatiotemporal patterns of urban land use change in the rapidly growing city of Lusaka, Zambia: Implications for sustainable urban development143 cited
  • 2017The propensity to cycle tool: An open source online system for sustainable transport planning121 cited
  • 2015Geo-temporal Twitter demographics112 cited
  • 2019Understanding Human Mobility Patterns in a Developing Country Using Mobile Phone Data51 cited

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2019
A multi‐modal transportation data‐driven approach to identify urban functional zones: An exploration based on Hangzhou City, China
49 cited
  • 2017Discovering spatial and temporal patterns from taxi-based Floating Car Data: a case study from Nanjing48 cited
  • Cited by

    • 2021Identifying Urban Functional Areas in China’s Changchun City from Sentinel-2 Images and Social Sensing Data17 cited
    • 2021Recurrent origin–destination network for exploration of human periodic collective dynamics7 cited