• DocumentCode
    2194968
  • Title

    Aerosol optical depth retrieval over China from NOAA AVHRR data

  • Author

    Yingjie Li ; Yong Xue ; Tingting Hou ; Leiku Yang ; Chi Li ; Jia Liu

  • Author_Institution
    State Key Lab. of Remote Sensing Sci., Beijing Normal Univ., Beijing, China
  • fYear
    2012
  • fDate
    22-27 July 2012
  • Firstpage
    3658
  • Lastpage
    3661
  • Abstract
    A new algorithm for Land Aerosol property and Bidirectional reflectance Inversion by Time Series technique (LABITS) is presented and applied to National Oceanic and Atmospheric Administration Advanced Very High Resolution Radiometer (NOAA AVHRR) data over China. Based on the assumptions that the surface bidirectional reflective property are not varying during one day and aerosol characteristics are constant in 0.1° × 0.1° window, we inverse the aerosol optical depth (AOD) and bidirectional reflectance distribution function (BRDF) parameters. Preliminary AOD validation with Aerosol Robotic Network (AERONET) data shows that the correlation coefficient, R2, is 0.79, the root-mean-square error, RMSE, is 0.13 and the uncertainty is Δτ= ±0.05 ± 0.20Δ. Comparing with MODIS AOD product, it is found that both the AOD results are consistent very well. The R2 is 0.80 and RMSE is 0.10. The algorithm is flexible and appropriate for aerosol retrieval over both dark and bright land surface. It is potential to retrieve long term global AOD over land from NOAA AVHRR data since 1980s and to study aerosol climatology and global climate change well.
  • Keywords
    aerosols; atmospheric optics; atmospheric techniques; time series; AERONET data; Aerosol Robotic Network; China; LABITS; NOAA AVHRR data; aerosol optical depth retrieval; bidirectional reflectance distribution function; bidirectional reflectance inversion; land aerosol property; time series; Aerosols; MODIS; Optical reflection; Optical sensors; Remote sensing; Satellites; US Government agencies; Advanced Very High Resolution Radiometer (AVHRR); aerosol optical depth (AOD); remote sensing inversion; surface bidirectional reflectance; time series;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Geoscience and Remote Sensing Symposium (IGARSS), 2012 IEEE International
  • Conference_Location
    Munich
  • ISSN
    2153-6996
  • Print_ISBN
    978-1-4673-1160-1
  • Electronic_ISBN
    2153-6996
  • Type

    conf

  • DOI
    10.1109/IGARSS.2012.6350623
  • Filename
    6350623