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Sensing the Nighttime Economy–Housing Imbalance from a Mobile Phone Data Perspective: A Case Study in Shanghai
16 references·1 citing·48 second hop
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References

  • 1970A Computer Movie Simulating Urban Growth in the Detroit Region9,754 cited
  • 1996Geographically Weighted Regression: A Method for Exploring Spatial Nonstationarity3,562 cited
  • 2020The Geography of Transport Systems2,981 cited
  • 1967The Data Model Concept in Statistical Mapping2,115 cited
  • 2011Comparison of Values of Pearson's and Spearman's Correlation Coefficients on the Same Sets of Data1,987 cited
  • 2012The Uncertain Geographic Context Problem1,406 cited
  • 2003Spatial autocorrelation and red herrings in geographical ecology1,067 cited
  • 2011Income Inequality and Income Segregation1,061 cited
  • 2005Multicollinearity and correlation among local regression coefficients in geographically weighted regression807 cited
  • 1993Is the Journey to Work Explained by Urban Structure?647 cited
  • 2019The Moran scatterplot as an ESDA tool to assess local instability in spatial association564 cited
  • 2013Comparing measures of urban land use mix409 cited
  • 2017Twitter and Facebook are not representative of the general population: Political attitudes and demographics of British social media users397 cited
  • 2018Check-in behaviour and spatio-temporal vibrancy: An exploratory analysis in Shenzhen, China341 cited
  • 1997

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The Jobs-Housing Balance and Urban Commuting
326 cited
  • 2017Coupling mobile phone and social media data: a new approach to understanding urban functions and diurnal patterns298 cited
  • Cited by

    • 2024Identifying the Hierarchical Structure of Nighttime Economic Agglomerations Based on the Fusion of Multisource Data5 cited