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| Titel |
Bayesian cloud detection for MERIS, AATSR, and their combination |
| VerfasserIn |
A. Hollstein, J. Fischer, C. Carbajal Henken, R. Preusker |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1867-1381
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| Digitales Dokument |
URL |
| Erschienen |
In: Atmospheric Measurement Techniques ; 8, no. 4 ; Nr. 8, no. 4 (2015-04-15), S.1757-1771 |
| Datensatznummer |
250116298
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| Publikation (Nr.) |
 copernicus.org/amt-8-1757-2015.pdf |
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| Zusammenfassung |
| A broad range of different of Bayesian cloud detection schemes is applied to
measurements from the Medium Resolution Imaging Spectrometer (MERIS), the
Advanced Along-Track Scanning Radiometer (AATSR), and their combination. The
cloud detection schemes were designed to be numerically efficient and suited
for the processing of large numbers of data. Results from the classical and
naive approach to Bayesian cloud masking are discussed for MERIS and AATSR as
well as for their combination. A sensitivity study on the resolution of
multidimensional histograms, which were post-processed by Gaussian smoothing,
shows how theoretically insufficient numbers of truth data can be used to set
up accurate classical Bayesian cloud masks. Sets of exploited features from
single and derived channels are numerically optimized and results for naive
and classical Bayesian cloud masks are presented. The application of the
Bayesian approach is discussed in terms of reproducing existing algorithms,
enhancing existing algorithms, increasing the robustness of existing
algorithms, and on setting up new classification schemes based on manually
classified scenes. |
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