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The Dynamic Heterogeneous Relationship between Urban Population Distribution and Built Environment in Xi’an, China: A Case Study
16 references·0 citing·45 second hop
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References

  • 2017Multiscale Geographically Weighted Regression (MGWR)1,381 cited
  • 2012Discovering regions of different functions in a city using human mobility and POIs1,136 cited
  • 2014Dynamic population mapping using mobile phone data908 cited
  • 2015Social Sensing: A New Approach to Understanding Our Socioeconomic Environments804 cited
  • 2018Check-in behaviour and spatio-temporal vibrancy: An exploratory analysis in Shenzhen, China341 cited
  • 2015Automated identification and characterization of parcels with OpenStreetMap and points of interest300 cited
  • 2019Portraying the spatial dynamics of urban vibrancy using multisource urban big data262 cited
  • 2018Spatiotemporal distribution characteristics and mechanism analysis of urban population density: A case of Xi'an, Shaanxi, China203 cited
  • 2019Identifying urban spatial structure and urban vibrancy in highly dense cities using georeferenced social media data196 cited
  • 2021Analytics of location-based big data for smart cities: Opportunities, challenges, and future directions135 cited
  • 2016Editorial: human dynamics in the mobile and big data era132 cited
  • 2022Investigating the spatiotemporal pattern between the built environment and urban vibrancy using big data in Shenzhen, China120 cited
  • 2020Validating activity, time, and space diversity as essential components of urban vitality107 cited

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2022
Investigating the spatiotemporal pattern of urban vibrancy and its determinants: Spatial big data analyses in Beijing, China
105 cited
  • 2021Understanding the pattern and mechanism of spatial concentration of urban land use, population and economic activities: a case study in Wuhan, China92 cited
  • 2020Big spatial data for urban and environmental sustainability86 cited
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