• DocumentCode
    575833
  • Title

    Clouds discrimination and surface classification for the sea ice albedo retrieval from MODIS data

  • Author

    Istomina, Larysa ; Heygster, Georg

  • Author_Institution
    Inst. of Environ. Phys., Univ. of Bremen, Bremen, Germany
  • fYear
    2012
  • fDate
    22-27 July 2012
  • Firstpage
    4481
  • Lastpage
    4484
  • Abstract
    The effect of Arctic sea ice on the radiative budget is of disproportional importance relative to its areal coverage. High albedo of sea ice is the driving force for a number of climatic feedbacks in the Arctic. In order to retrieve sea ice albedo from satellite and assess the state of the Arctic climate, important preparation steps are needed. They are the surface type classification and cloud clearing of the satellite scene. The MODIS sensor features spectral channels which can be used to distinguish all kinds of surfaces from snow-like surfaces, and further - separate snow, melting snow and ice, melt ponds and leads. In situ data is used to derive threshold values characterizing each family of surface types for MODIS bands 4 and 5. Separation of all the above mentioned snow-like surfaces from clouds is not a trivial task; MODIS bands 4, 5 and 6 are used to enhance the atmospheric reflectance in the NIR and screen out clouds from snow or ice-covered scene.
  • Keywords
    albedo; clouds; geophysical image processing; geophysical techniques; image classification; oceanographic regions; radiometry; remote sensing; sea ice; Arctic climate; Arctic sea ice; MODIS data; MODIS sensor; climatic feedbacks; cloud discrimination; melt ponds; radiative budget; satellite scene cloud clearing; sea ice albedo retrieval; snow melting; snow-like surfaces; spectral channels; surface type classification; Clouds; MODIS; Ocean temperature; Sea ice; Sea surface; Snow; Arctic; MODIS; Sea ice;
  • 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.2012.6350476
  • Filename
    6350476