• DocumentCode
    2706902
  • Title

    Spatial correlation analysis between impervious surface, green space and urban heat island

  • Author

    Zhang, Xiaoping ; Zhang, Mingxi ; Zhang, Jun ; Yang, Yingbao

  • Author_Institution
    Dept. of Geomatics, Hohai Univ., Nanjing, China
  • fYear
    2011
  • fDate
    24-26 June 2011
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    The objective of this research is to explore the spatial correlation between impervious surface, green space and urban heat island based on a case study of Nanjing, China. The Landsat TM image was used to retrieve land surface temperature. According to the impervious surface area (ISA) and the fractional vegetation cover (Fr) having an inversely relation in urban built-up areas, the spatial pattern of the impervious surface area was obtained. By calculating of the three optimum bands, the image was classified and urban green space was extracted. And then we researched the relationship between impervious surface area, the area of green space, the shape index of green space and land surface temperature in urban built-up area. In addition, through multivariable linear regression, the comprehensive regression was gained.
  • Keywords
    atmospheric boundary layer; atmospheric techniques; geophysical image processing; image classification; land surface temperature; China; Landsat TM image; Nanjing; fractional vegetation cover; green space; image classification; impervious surface area; land surface temperature; multivariable linear regression; spatial correlation analysis; spatial pattern; urban heat island; Cities and towns; Correlation; Green products; Land surface; Land surface temperature; Remote sensing; Vegetation mapping; correlation analysis; green space; impervious surface area; multiple linear regression; urban heat island;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Geoinformatics, 2011 19th International Conference on
  • Conference_Location
    Shanghai
  • ISSN
    2161-024X
  • Print_ISBN
    978-1-61284-849-5
  • Type

    conf

  • DOI
    10.1109/GeoInformatics.2011.5980744
  • Filename
    5980744