• DocumentCode
    2322485
  • Title

    Estimating the energy consumption with nighttime city light from the DMSP/OLS imagery

  • Author

    Letu, Husi ; Hara, Masanao ; Yagi, Hiroshi ; Tana, Gegen ; Nishio, Fumihiko

  • Author_Institution
    Grad. Schools of Sci. & Technol., Chiba Univ., Chiba
  • fYear
    2009
  • fDate
    20-22 May 2009
  • Firstpage
    1
  • Lastpage
    7
  • Abstract
    A methodology is presented to accurately estimate electric power consumption from saturated nighttime DMSP/OLS imagery using a stable light correction. An area correction for the stable light image of DMSP/OLS for the year 1999 was performed and the building area rate data were used to clarify the intensity distribution characteristics of the stable light. Based on the spatial distribution characteristics of the stable light, the saturation light of the electric power supply area of Japan was corrected using a cubic regression equation. The regression between the correction calculations by the cubic regression equation and the statistical electric power consumption data was applied not only in Japan but also in China, India and 10 other Asian countries. Then, the correction method was evaluated. This study confirms that the electric power consumption can be estimated with high precision from the stable light.
  • Keywords
    feature extraction; geophysical techniques; image processing; power consumption; remote sensing; AD 1999; China; India; Japan; building area rate data; cubic regression equation; nighttime city light; saturated nighttime DMSP-OLS imagery; spatial distribution characteristics; stable light correction; stable light intensity distribution; statistical electric power consumption data; Cities and towns; Clouds; Data mining; Energy consumption; Equations; Fossil fuels; Global warming; Humans; Remote monitoring; Remote sensing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Urban Remote Sensing Event, 2009 Joint
  • Conference_Location
    Shanghai
  • Print_ISBN
    978-1-4244-3460-2
  • Electronic_ISBN
    978-1-4244-3461-9
  • Type

    conf

  • DOI
    10.1109/URS.2009.5137699
  • Filename
    5137699