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<article language="en">
	<journal>
		<journal_title>Atmospheric Measurement Techniques</journal_title>
		<journal_url>www.atmos-meas-tech.net</journal_url>
		<issn>1867-1381</issn>
		<eissn>1867-8548</eissn>
		<volume_number>3</volume_number>
		<issue_number>4</issue_number>
		<publication_year>2010</publication_year>
	</journal>
	<doi>10.5194/amt-3-1005-2010</doi>
	<article_url>http://www.atmos-meas-tech.net/3/1005/2010/</article_url>
	<abstract_html>http://www.atmos-meas-tech.net/3/1005/2010/amt-3-1005-2010.html</abstract_html>
	<fulltext_pdf>http://www.atmos-meas-tech.net/3/1005/2010/amt-3-1005-2010.pdf</fulltext_pdf>
	<start_page>1005</start_page>
	<end_page>1017</end_page>
	<publication_date>2010-08-03</publication_date>
	<article_title content_type="html">The detection of cloud-free snow-covered areas using  AATSR measurements</article_title>
	<authors>
		<author numeration="1" affiliations="1">
			<name>L. G. Istomina</name>
			<email>lora@iup.physik.uni-bremen.de</email>
		</author>
		<author numeration="2" affiliations="1">
			<name>W. von Hoyningen-Huene</name>
		</author>
		<author numeration="3" affiliations="1">
			<name>A. A. Kokhanovsky</name>
		</author>
		<author numeration="4" affiliations="1">
			<name>J. P. Burrows</name>
		</author>
	</authors>
	<affiliations>
		<affiliation numeration="1" content_type="html">Institute of Environmental Physics, University of Bremen, Bremen, Germany</affiliation>
	</affiliations>
	<abstract content_type="html">A new method to detect cloud-free snow-covered areas has been
developed using the measurements by the Advanced Along Track
Scanning Radiometer (AATSR) on board the ENVISAT satellite in order
to discriminate clear snow fields for the retrieval of aerosol
optical thickness or snow properties. The algorithm uses seven AATSR
channels from visible (VIS) to thermal infrared (TIR) and analyses
the spectral behaviour of each pixel in order to recognize the
spectral signature of snow. The algorithm includes a set of relative
thresholds and combines all seven channels into one flexible
criterion, which allows us to filter out all the pixels with
spectral behaviour similar to that of snow. The algorithm does not
use any kind of morphological criteria and does not require the
studied surface to have any special structure. The snow spectral
shape criterion was determined by a comprehensive theoretical study,
which included radiative transfer simulations for various
atmospheric conditions as well as studying existing models and
measurements of optical and physical properties of snow in different
spectral bands. The method has been optimized to detect cloud-free
snow-covered areas, and does not produce cloud/land/ocean/snow mask.
However, the algorithm can be extended and able to discriminate
various kinds of surfaces.
&lt;br&gt;&lt;br&gt;
The presented method has been validated against Micro Pulse Lidar
data and compared to Moderate Resolution Imaging Spectroradiometer
(MODIS) cloud mask over snow-covered areas, showing quite good
correspondence to each other.
&lt;br&gt;&lt;br&gt;
Comparison of both MODIS cloud mask and presented snow mask to AATSR
operational cloud mask showed that in some cases of snow surface the
accuracy of AATSR operational cloud mask is questionable.</abstract>
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</article>

