Diaconu, Codrut-Andrei und Bamber, Jonathan L. (2023) Detailed Glacier Area Change Analysis in the European Alps with Deep Learning. In: NeurIPS 2023 Workshop on Tackling Climate Change with Machine Learning, Seiten 1-7. NeurIPS 2023 Workshop on Tackling Climate Change with Machine Learning, 2023-12-10 - 2023-12-16, New Orleans, Louisiana, United States.
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Kurzfassung
Glacier retreat is a key indicator of climate change and requires regular updates of the glacier area. Recently, the release of a new inventory for the European Alps showed that glaciers continued to retreat at about 1.3% per year from 2003 to 2015. The outlines were produced by manually correcting the results of a semi-automatic method applied to Sentinel-2 imagery. In this work we develop a fully-automatic pipeline based on Deep Learning to investigate the evolution of the glaciers in the Alps from 2015 to present (2023). After outlier filtering, we provide individual estimates for around 1300 glaciers, representing 87% of the glacierized area. Regionally we estimate an area loss of -1.8% per year, with large variations between glaciers. Code and data are available at https://github.com/dcodrut/glacier_mapping_alps_tccml.
elib-URL des Eintrags: | https://elib.dlr.de/199664/ | ||||||||||||
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Dokumentart: | Konferenzbeitrag (Poster) | ||||||||||||
Titel: | Detailed Glacier Area Change Analysis in the European Alps with Deep Learning | ||||||||||||
Autoren: |
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Datum: | Dezember 2023 | ||||||||||||
Erschienen in: | NeurIPS 2023 Workshop on Tackling Climate Change with Machine Learning | ||||||||||||
Referierte Publikation: | Ja | ||||||||||||
Open Access: | Ja | ||||||||||||
Gold Open Access: | Nein | ||||||||||||
In SCOPUS: | Nein | ||||||||||||
In ISI Web of Science: | Nein | ||||||||||||
Seitenbereich: | Seiten 1-7 | ||||||||||||
Status: | veröffentlicht | ||||||||||||
Stichwörter: | Deep Learning, Glacier Mapping | ||||||||||||
Veranstaltungstitel: | NeurIPS 2023 Workshop on Tackling Climate Change with Machine Learning | ||||||||||||
Veranstaltungsort: | New Orleans, Louisiana, United States | ||||||||||||
Veranstaltungsart: | internationale Konferenz | ||||||||||||
Veranstaltungsbeginn: | 10 Dezember 2023 | ||||||||||||
Veranstaltungsende: | 16 Dezember 2023 | ||||||||||||
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 - Künstliche Intelligenz | ||||||||||||
Standort: | Oberpfaffenhofen | ||||||||||||
Institute & Einrichtungen: | Institut für Methodik der Fernerkundung > EO Data Science | ||||||||||||
Hinterlegt von: | Diaconu, Codrut-Andrei | ||||||||||||
Hinterlegt am: | 28 Nov 2023 12:40 | ||||||||||||
Letzte Änderung: | 24 Apr 2024 21:00 |
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