Fichtelmann, Bernd und Günther, Kurt P und Borg, Erik (2015) Adaption of a Self-Learning Algorithm for Dynamic Classification of Water Bodies to SPOT VEGETATION Data. In: 15th International Conference on Computational Science and Its Applications, ICCSA 2015, Seiten 177-192. Springer International Publishing Switzerland. 15th International Conference on Computational Science and its Applications - ICCSA 2015, 2015-06-22 - 2015-06-25, Banff, Canada. doi: 10.1007/978-3-319-21410-8_14. ISBN 978-3-319-21409-2 (Print) 978-3-319-21410-8 (Online).
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Offizielle URL: http://link.springer.com/chapter/10.1007/978-3-319-21410-8_14#
Kurzfassung
Within the ESA CCI “Fire Disturbance” project a dynamic self-learning water masking approach originally developed for AATSR data was modified for MERIS-FR(S) and MERIS-RR data and now for SPOT VEGETATION (VGT) data. The primary goal of the development was to apply for all sensors the same generic principles by combining static water masks on a global scale with a self-learning algorithm. Our approach results in the generation of a dynamic water mask which helps to distinguish dark burned area objects from other different types of dark areas (e.g. cloud or topographic shadows, coniferous forests). The use of static land-water masks includes the disadvantage that land-water masks represent only a temporal snapshot of the water bodies. Regional results demonstrate the quality of the dynamic water mask. In addition the advantages to conventional water masking algorithms are shown. Furthermore, the dynamic water masks of AATSR, MERIS and VGT for the same region are presented and discussed together with the use of more detailed static water masks.
elib-URL des Eintrags: | https://elib.dlr.de/96936/ | ||||||||||||||||||||||||||||||||||||
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Dokumentart: | Konferenzbeitrag (Vortrag) | ||||||||||||||||||||||||||||||||||||
Titel: | Adaption of a Self-Learning Algorithm for Dynamic Classification of Water Bodies to SPOT VEGETATION Data | ||||||||||||||||||||||||||||||||||||
Autoren: |
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Datum: | 25 Juni 2015 | ||||||||||||||||||||||||||||||||||||
Erschienen in: | 15th International Conference on Computational Science and Its Applications, ICCSA 2015 | ||||||||||||||||||||||||||||||||||||
Referierte Publikation: | Ja | ||||||||||||||||||||||||||||||||||||
Open Access: | Nein | ||||||||||||||||||||||||||||||||||||
Gold Open Access: | Nein | ||||||||||||||||||||||||||||||||||||
In SCOPUS: | Ja | ||||||||||||||||||||||||||||||||||||
In ISI Web of Science: | Nein | ||||||||||||||||||||||||||||||||||||
DOI: | 10.1007/978-3-319-21410-8_14 | ||||||||||||||||||||||||||||||||||||
Seitenbereich: | Seiten 177-192 | ||||||||||||||||||||||||||||||||||||
Herausgeber: |
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Verlag: | Springer International Publishing Switzerland | ||||||||||||||||||||||||||||||||||||
ISBN: | 978-3-319-21409-2 (Print) 978-3-319-21410-8 (Online) | ||||||||||||||||||||||||||||||||||||
Status: | veröffentlicht | ||||||||||||||||||||||||||||||||||||
Stichwörter: | Self-learning algorithm, Land-water mask, Interpretation, Remote sensing, VGT data, Cloud cover | ||||||||||||||||||||||||||||||||||||
Veranstaltungstitel: | 15th International Conference on Computational Science and its Applications - ICCSA 2015 | ||||||||||||||||||||||||||||||||||||
Veranstaltungsort: | Banff, Canada | ||||||||||||||||||||||||||||||||||||
Veranstaltungsart: | internationale Konferenz | ||||||||||||||||||||||||||||||||||||
Veranstaltungsbeginn: | 22 Juni 2015 | ||||||||||||||||||||||||||||||||||||
Veranstaltungsende: | 25 Juni 2015 | ||||||||||||||||||||||||||||||||||||
Veranstalter : | University of Calgary, Calgary, Canada | ||||||||||||||||||||||||||||||||||||
HGF - Forschungsbereich: | Luftfahrt, Raumfahrt und Verkehr | ||||||||||||||||||||||||||||||||||||
HGF - Programm: | Raumfahrt | ||||||||||||||||||||||||||||||||||||
HGF - Programmthema: | Erdbeobachtung | ||||||||||||||||||||||||||||||||||||
DLR - Schwerpunkt: | Raumfahrt | ||||||||||||||||||||||||||||||||||||
DLR - Forschungsgebiet: | R EO - Erdbeobachtung | ||||||||||||||||||||||||||||||||||||
DLR - Teilgebiet (Projekt, Vorhaben): | R - Vorhaben Fernerkundung der Landoberfläche (alt) | ||||||||||||||||||||||||||||||||||||
Standort: | Neustrelitz | ||||||||||||||||||||||||||||||||||||
Institute & Einrichtungen: | Deutsches Fernerkundungsdatenzentrum > Nationales Bodensegment Deutsches Fernerkundungsdatenzentrum > Landoberfläche | ||||||||||||||||||||||||||||||||||||
Hinterlegt von: | Fichtelmann, Dr.rer.nat. Bernd | ||||||||||||||||||||||||||||||||||||
Hinterlegt am: | 04 Aug 2015 10:47 | ||||||||||||||||||||||||||||||||||||
Letzte Änderung: | 24 Apr 2024 20:02 |
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