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Night-time cloud detection for FY-3A/VIRR using multispectral thresholds.

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Bibliographic Details
Title: Night-time cloud detection for FY-3A/VIRR using multispectral thresholds.
Authors: He, Quanjun1,2,3 (AUTHOR) hequanjunsx@163.com
Source: International Journal of Remote Sensing. Apr2013, Vol. 34 Issue 8, p2876-2887. 12p. 3 Color Photographs, 1 Diagram, 2 Charts, 1 Graph.
Subjects: Telecommunication satellites, Spectrophotometers, Satellite meteorology, Brightness temperature, Spectroradiometer
Abstract: Night-time cloud detection using satellite data is a challenging area of research. This article presents a night-time cloud detection algorithm based on multispectral thresholds for the Visible and Infrared Radiometer (VIRR). VIRR is one of the keystone instruments on board the Chinese Feng Yun 3 (FY-3) polar-orbiting meteorological satellite. In this algorithm, three thermal infrared channels and other ancillary data are used to test for the presence of clouds according to different underlying surface types, and the four levels of possible cloud confidence are used to report whether a pixel is cloudy or clear. This algorithm strengthens the ability of identification of low cloud using the brightness temperature difference between the 3.7 and 12 μm channels. The comparisons of a new cloud mask with the official VIRR cloud mask product and with the official Moderate Resolution Imaging Spectroradiometer (MODIS) cloud mask product are shown to illustrate and validate the effect of this new algorithm. In addition, this algorithm is applied to FY-3B/VIRR data to test the validity and accuracy of cloud detection. [ABSTRACT FROM PUBLISHER]
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Database: Engineering Source
Description
Abstract:Night-time cloud detection using satellite data is a challenging area of research. This article presents a night-time cloud detection algorithm based on multispectral thresholds for the Visible and Infrared Radiometer (VIRR). VIRR is one of the keystone instruments on board the Chinese Feng Yun 3 (FY-3) polar-orbiting meteorological satellite. In this algorithm, three thermal infrared channels and other ancillary data are used to test for the presence of clouds according to different underlying surface types, and the four levels of possible cloud confidence are used to report whether a pixel is cloudy or clear. This algorithm strengthens the ability of identification of low cloud using the brightness temperature difference between the 3.7 and 12 μm channels. The comparisons of a new cloud mask with the official VIRR cloud mask product and with the official Moderate Resolution Imaging Spectroradiometer (MODIS) cloud mask product are shown to illustrate and validate the effect of this new algorithm. In addition, this algorithm is applied to FY-3B/VIRR data to test the validity and accuracy of cloud detection. [ABSTRACT FROM PUBLISHER]
ISSN:01431161
DOI:10.1080/01431161.2012.755275