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Identification of cloudy and clear sky areas in MSG SEVIRI images by analyzing spectral and temporal information
Reuter, Maximilian

HaupttitelIdentification of cloudy and clear sky areas in MSG SEVIRI images by analyzing spectral and temporal information
TitelvarianteIdentifizierung bewölkter und unbewölkter Bereiche in MSG SEVIRI Bildern mittels spektraler und zeitlicher Analyse
AutorReuter, Maximilian
Geburtsort: Berlin, Deutschland
GutachterProf. Dr. Jürgen Fischer
weitere GutachterProf. Dr. Uwe Ulbrich
Freie SchlagwörterMSG SEVIRI cloud detection masking time series analysis
DDC550 Geowissenschaften
ZusammenfassungA cloud detection algorithm for the SEVIRI instrument aboard the geostationary satellite MSG (METEOSAT second generation) has been established at the Institut für Weltraumwissenschaften, Freie Universität Berlin (FUB). It is based on the analysis of spectral and temporal information by neural networks. In particular, the assumed clear sky brightness temperature in the 10.8µm channel estimated from analyses of its temporal evolution is a central input parameter of the neural networks. The training dataset has been created by manual classifications. The cloud mask has been validated against more than one million European synoptical observations within a long-term validation period from July, 1st 2004 to December, 31st 2004. In a short-term validation period from June, 3rd 2004 to June, 8th 2004, the cloud mask has additionally been compared to the EUMETSAT cloud mask. The overall bias amounts to -0.0100 ± 0.0003 within the long-term validation period. Within the short-term validation period, the corresponding values for the FUB and the EUMETSAT cloud mask are -0.026 ± 0.002 and -0.075 ± 0.002, respectively. As overall statistical benchmark, the Kuipers skill score (KSS) has been chosen. Within the long-term validation phase, the KSS amounts to 0.724 ± 0.001. The overall KSS within the short-term validation phase amounts to 0.807 ± 0.004 for the FUB and 0.747 ± 0.005 for the EUMETSAT cloud mask. These values prove the high quality of the developed cloud detection algorithm.
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Fachbereich/EinrichtungFB Geowissenschaften
Erscheinungsjahr2005
Dokumententyp/-SammlungenDissertation
Medientyp/FormatText
SpracheEnglisch
RechteNutzungsbedingungen
Tag der Disputation13.07.2005
Erstellt am27.07.2005 - 00:00:00
Letzte Änderung19.02.2010 - 11:31:11
 
Alte Darwin URLhttp://www.diss.fu-berlin.de/2005/194/
Statische URLhttp://www.diss.fu-berlin.de/diss/receive/FUDISS_thesis_000000001661
URNurn:nbn:de:kobv:188-2005001940
Zugriffsstatistik