• DocumentCode
    2930123
  • Title

    Automatic detection of oil spills in ENVISAT, Radarsat and ERS SAR images

  • Author

    Solberg, Anne H S ; Dokken, Sverre Thune ; Solberg, Rune

  • Author_Institution
    Dept. of Stat. Anal., Image Anal. & Pattern Recognition, Norwegian Comput. Center, Oslo, Norway
  • Volume
    4
  • fYear
    2003
  • fDate
    21-25 July 2003
  • Firstpage
    2747
  • Abstract
    We present a framework for automatic detection of oil spills in SAR images. Multi incident angle and multi polarization SAR data are ingested into the framework in order to optimize revisit times and thereby the temporal and spatial coverage. Dark spots in the images are primarily detected by adaptive thresholding. For each of them a number of features are computed in order to classify the slick as either an oil slick or a ´look-alike´ (other oceanographic phenomena which resemble oil slicks). A classification scheme is utilized based on statistical modeling. A data set of about 100 images from each of the sensors ERS, Radarsat and ENVISAT is or will soon be available to train and test the algorithm. In this paper, only results from ERS and Radarsat are reported because the access of ENVISAT images has been delayed.
  • Keywords
    oceanographic techniques; oils; radar detection; radar imaging; remote sensing by radar; synthetic aperture radar; water pollution measurement; ENVISAT; ERS SAR images; ERS sensors; adaptive thresholding; automatic detection; multipolarization SAR data; oil slick; oil spills; radarsat; spatial coverage; statistical modeling; temporal coverage; Backscatter; Detection algorithms; Humans; Image analysis; Inspection; Pattern recognition; Petroleum; Shape; Statistical analysis; Wind;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Geoscience and Remote Sensing Symposium, 2003. IGARSS '03. Proceedings. 2003 IEEE International
  • Print_ISBN
    0-7803-7929-2
  • Type

    conf

  • DOI
    10.1109/IGARSS.2003.1294572
  • Filename
    1294572