Automated satellite cloud analysis: a multispectral approach to the problem of snow/cloud discrimination

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Author
Allen, Robert C. Jr.
Date
1987-06Advisor
Durkee, Philip A.
Wash, Carlyle H.
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Show full item recordAbstract
An algorithm is developed and evaluated for discriminating among clouds, snow
cover and clear land. The multispectral technique uses daytime images of AVHRR
channels 1 (0.63^m). 3 (3.7jim) and 4 (11.0[im). Reflectance is derived for channel 3
by using the channel 4 emission temperature to estimate and remove the channel 3
thermal emission. Separation of clouds from snow and land is based primarily on this
derived channel 3 reflectance. Using this technique, observed reflectance in channel 3
is 2 to 4 percent for snow, 3 to 10 percent for land, 2 to 27 percent for ice clouds and 8
to 36 percent for liquid clouds. These values overlap for thin cirrus and snow, so the
routine then attempts analysis of cirrus based on its different transmissive properties
between channels 3 and 4. Six images were analyzed and the total cloud cover was
verified against a total of 1 10 conventional surface observations using the standard
categories of clear, scattered, broken and overcast. The routine was quite successful,
with the analyzed sky cover being within category for 55 percent of the stations, one
category different for 33 percent, 2 categories different for 9 percent and 3 categories
different for 3 percent of the stations. A major remaining problem is discrimination
between ice clouds and snow cover due to the great similarity of reflective properties of
these two surfaces.
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