• DocumentCode
    2203401
  • Title

    An improved mosaic method considering atmospheric diffusion in aerosol optical depth retrieval case

  • Author

    Jia Liu ; Yong Xue ; Hui Xu ; Yingjie Li ; Jie Guang ; Chi Li ; Leiku Yang

  • Author_Institution
    State Key Lab. of Remote Sensing Sci., Beijing Normal Univ., Beijing, China
  • fYear
    2012
  • fDate
    22-27 July 2012
  • Firstpage
    2308
  • Lastpage
    2311
  • Abstract
    Aerosol optical depth (AOD) is a key parameter reflecting aerosol properties, and it is inevitable to mosaic multi-orbit data while making AOD datasets in some situations due to the limitation in scanning width of various instruments. This article summarizes some conventional methods eliminating seams of mosaic images, and introduces the idea of combining the Gaussian dispersion model into mosaic process in the AOD retrieval case. In this article, we elaborate the principle of the Gauss plume model and put forward the improved method. Based on the AOD products from the Synergetic Retrieval of Aerosol Properties (SRAP) model from the Moderate Resolution Imaging Spectroradiometer (MODIS) data, we conduct experiments on improved methods, and evaluate the processing effect.
  • Keywords
    Gaussian processes; aerosols; atmospheric movements; atmospheric techniques; data acquisition; AOD datasets; Gauss plume model; Gaussian dispersion model; MODIS data; Moderate Resolution Imaging Spectroradiometer; SRAP model; Synergetic Retrieval of Aerosol Properties; aerosol optical depth retrieval case; aerosol properties; atmospheric diffusion; improved mosaic method; mosaic images; mosaic process; multi-orbit data mosaic; processing effect; scanning width; Aerosols; Atmospheric modeling; Dispersion; MODIS; Meteorology; Optical imaging; Optical sensors; Aerosol Optical Depth (AOD); Gaussian dispersion model; mosaic; seams;
  • 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.2012.6351033
  • Filename
    6351033