• DocumentCode
    2204190
  • Title

    Background subtraction and dust storm detection

  • Author

    Liu, Chenyi ; Fieguth, Paul ; Garbe, Christoph

  • Author_Institution
    Syst. Design Eng., Univ. of Waterloo, Waterloo, ON, Canada
  • fYear
    2012
  • fDate
    22-27 July 2012
  • Firstpage
    2179
  • Lastpage
    2181
  • Abstract
    Mineral dust aerosols can influence the Earth´s climate system to a significant degree and have a strong effect on terrestrial and oceanic biogeochemical cycles. As one step in quantifying dust sources, sinks, and transport, this paper seeks to quantify the presence of dust storms in the Sahara desert, which is the most active worldwide source of dust. Our work is based on the SEVIRI infrared imager on-board the geostationary Meteosat-8 satellite, providing three separate channels at a 3km by 3km resolution. The significant challenge is that the infrared channels are highly influenced by the presence of water clouds and surface temperatures, which complicate the identification of dust-cloud anomalies. This paper develops a method of spatio-temporal background estimation from sparse data as a way of recovering dust images and presents results on real data.
  • Keywords
    atmospheric techniques; dust; geophysical image processing; image resolution; infrared imaging; land surface temperature; minerals; spatiotemporal phenomena; storms; Earth climate system; SEVIRI infrared imager; Sahara desert; dust image analysis; dust sources; dust storm detection; dust-cloud anomalies; geostationary Meteosat-8 satellite; infrared channels; mineral dust aerosols; oceanic biogeochemical cycles; spatio-temporal background estimation; surface temperatures; water clouds; Atmospheric modeling; Clouds; Computational modeling; Estimation; Image segmentation; Satellites; Background Estimation; Dust Cloud Identification;
  • 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.2012.6351070
  • Filename
    6351070