• Di Vittorio, A., , and Emery W. , 2002: An automated, dynamic threshold cloud-masking algorithm for daytime AVHRR images over land. IEEE Trans. Geosci. Remote Sens., 40, 16841694.

    • Search Google Scholar
    • Export Citation
  • Dybbroe, A., 2001: The retrieval of the SAFNWC cloud mask and cloud type from AVHRR and SEVIRI at high latitudes. 2nd ed. SMHI SAFNWC Action PT06-04 November 2, 28 pp.

    • Search Google Scholar
    • Export Citation
  • Dybbroe, A., , Karlsson K.-G. , , and Thoss A. , 2005: NWCSAF AVHRR cloud detection and analysis using dynamic thresholds and radiative transfer modeling. Part I: Algorithm description. J. Appl. Meteor., 44, 3954.

    • Search Google Scholar
    • Export Citation
  • Hagihara, Y., , Okamoto H. , , and Yoshida R. , 2010: Development of a combined CloudSat–CALIPSO cloud mask to show global cloud distribution. J. Geophys. Res., 115, D00H33, doi:10.1029/2009JD012344.

    • Search Google Scholar
    • Export Citation
  • Karlsson, K.-G., 2003: A 10 year cloud climatology over Scandinavia derived from NOAA Advanced Very High Resolution Radiometer imagery. Int. J. Climatol., 23, 10231044.

    • Search Google Scholar
    • Export Citation
  • Karner, O., , and Di Girolamo L. , 2001: On automatic cloud detection over ocean. Int. J. Remote Sens., 22, 30473052.

  • Kowalewski, M., , and Krezel A. , 2004: System of automatic registration and geometric correction of AVHRR data (in Polish). Arch. Fotogram. Kartogr. Teledetek.,XIIIb, 397–407.

    • Search Google Scholar
    • Export Citation
  • Krezel, A., , Kozlowski L. , , and Paszkuta M. , 2008: A simple model of light transmission through the atmosphere over the Baltic Sea utilising satellite data. Oceanologia, 50 (2), 125146.

    • Search Google Scholar
    • Export Citation
  • Kriebel, K., , Gesell G. , , Kaestner M. , , and Mannstein H. , 2003: The cloud analysis tool Apollo: Improvements and validations. Int. J. Remote Sens., 24, 23892408.

    • Search Google Scholar
    • Export Citation
  • Saunders, R., , and Kriebel T. , 1988: An improved method for detecting clear sky radiances from AVHRR data. Int. J. Remote Sens., 9, 123150.

    • Search Google Scholar
    • Export Citation
  • Stowe, L. L., , Davis P. A. , , and McClain E. P. , 1999: Scientific basis and initial evaluation of the CLAVR-1 global clear/cloud classification algorithm for the Advanced Very High Resolution Radiometer. J. Atmos. Oceanic Technol., 16, 656681.

    • Search Google Scholar
    • Export Citation
  • Turner, J., , Marshall G. , , and Ladkin R. , 2001: An operational, real-time cloud detection scheme for use in the Antarctic based on AVHRR data. Int. J. Remote Sens., 22, 30273046.

    • Search Google Scholar
    • Export Citation
  • Xiong, X., , Li W. , , Lubin D. , , and Stamnes K. , 2002: Evaluating the principles of cloud remote sensing with AVHRR and MAS imagery over SHEBA. J. Geophys. Res., 107, 8036, doi:10.1029/2000JC000424.

    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 37 37 5
PDF Downloads 9 9 2

Automatic Detection of Cloud Cover over the Baltic Sea

View More View Less
  • 1 Institute of Oceanography, University of Gdansk, Gdynia, Poland
© Get Permissions
Restricted access

Abstract

A simple detection method was proposed to increase the efficiency of automatic classification of a satellite image cell (clear/cloudy). A method is described on the basis of the Advanced Very High Resolution Radiometer (AVHRR) data, with a focus on highly active and highly reflecting targets (i.e., the Baltic Sea). Radiation input conditions and the dynamic threshold were used to reduce geometric influences of any daily scene supplied by the NOAA-17 and NOAA-18 platforms. They were carried out from statistic and histogram sequences of albedo and temperature maps. The presented approach is intended to primarily serve the activation of a nonsupervised system for oceanographic analyses (mainly SST), based on an accurate cloud mask.

Corresponding author address: Adam Krężel, Institute of Oceanography, University of Gdansk, Al. Marszalka Pilsudskiego 46, 81-378 Gdynia, Poland. E-mail: oceak@univ.gda.pl

Abstract

A simple detection method was proposed to increase the efficiency of automatic classification of a satellite image cell (clear/cloudy). A method is described on the basis of the Advanced Very High Resolution Radiometer (AVHRR) data, with a focus on highly active and highly reflecting targets (i.e., the Baltic Sea). Radiation input conditions and the dynamic threshold were used to reduce geometric influences of any daily scene supplied by the NOAA-17 and NOAA-18 platforms. They were carried out from statistic and histogram sequences of albedo and temperature maps. The presented approach is intended to primarily serve the activation of a nonsupervised system for oceanographic analyses (mainly SST), based on an accurate cloud mask.

Corresponding author address: Adam Krężel, Institute of Oceanography, University of Gdansk, Al. Marszalka Pilsudskiego 46, 81-378 Gdynia, Poland. E-mail: oceak@univ.gda.pl
Save