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Terminus area change of 17 key glaciers of the Antarctic Peninsula from 2013 to 2023 derived from remote sensing and deep learning
Metadaten
| Für den Inhalt der Forschungsdaten verantwortliche Person(en) | Loebel, Erik - Technische Universität Dresden (ORCID: 0000-0001-9874-9295) | |
| Für den Inhalt der Forschungsdaten verantwortliche Person(en) | Baumhoer, Celia A. - German Aerospace Center (ORCID: 0000-0003-1339-2288) | |
| Für den Inhalt der Forschungsdaten verantwortliche Person(en) | Dietz, Andreas - German Aerospace Center | |
| Für den Inhalt der Forschungsdaten verantwortliche Person(en) | Scheinert, Mirko - Technische Universität Dresden (ORCID: 0000-0002-0892-8941) | |
| Für den Inhalt der Forschungsdaten verantwortliche Person(en) | Horwath, Martin - Technische Universität Dresden (ORCID: 0000-0001-5797-244X) | |
| Kurzbeschreibung | Glacier terminus area changes are derived using the rectilinear box method applied to time series of glacier calving front locations. Terminus changes are provided in text file and image format. The following glaciers are included in this data record: Birley Glacier, Bleriot Glacier, Cayley Glacier, Crane Glacier, Dinsmore-Bombardier-Edgeworth Glacier system, Drygalski Glacier, Fleming Glacier, Hariot Glacier, Hektoria-Green-Evans Glacier system, Hugi Glacier, Jorum Glacier, Murphy Wilkinson Glacier, Prospect Glacier, Sjogren Glacier, Stringfellow Glacier, Trooz Glacier and Widdowson Glacier. | |
| Länder, auf die sich die Daten beziehen | ANTARCTICA | de |
| Region(en) auf die sich die Daten beziehen | Antarctic Peninsula | |
| Weitere Schlagwörter | Antarctica | |
| Weitere Schlagwörter | remote sensing | |
| Weitere Schlagwörter | machine learning | |
| Weitere Schlagwörter | satellite imagery | |
| Weitere Schlagwörter | Glaciers | |
| Entstehungsjahr oder Entstehungszeitraum | 2023 | |
| Veröffentlichungsjahr | 2023 | |
| Herausgeber | Technische Universität Dresden | |
| Referenzen auf ergänzende Materialien | IsPartOf: 123456789/5680 (Handle) | |
| Inhalt der Forschungsdaten | Image, Dataset: Terminus area change for 19 key glaciers of the Antarctic Peninsula from 2013 to 2023 | |
| Inhaber der Nutzungsrechte | Technische Universität Dresden | |
| Nutzungsrechte des Datensatzes | CC-BY-SA-4.0 | |
| Angabe der Fachgebiete | Geography | de |
| Angabe der Fachgebiete | Geological Science | de |
| Titel des Datensatzes | Terminus area change of 17 key glaciers of the Antarctic Peninsula from 2013 to 2023 derived from remote sensing and deep learning |
Dateien zu dieser Ressource
Die Datenpakete erscheinen in:
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Change pattern identification of marine-terminating outlet glaciers [5]
Marine-terminating outlet glaciers experience a combination of seasonal and climate-driven change. Nearby glaciers exhibit very different retreat and advance behavior despite being situated in similar climatic conditions. This highlights the demand to essentially improve our understanding of the driving mechanisms and to provide a basis for parameterizations of oceanic forcing that are fed into mass-loss projections. Temporal changes of glacial flow velocities are presumably linked to the evolution of the subglacial hydrological system. Depending on the type of subglacial system, the temporal acceleration of the glacier is represented by different characteristics. While this is typically investigated only along a central flow line, the spatial distribution contains more information on the cause of the acceleration. In a similar way, the spatial pattern of acceleration due to changes at the calving front is likely driven by upstream propagation of changes in stresses. Hence, understanding the mechanisms in detail requires an analysis of different physical variables in high temporal and spatial resolution and combination with ice modelling. With the new generation of satellites the era of big data has started in glaciology, and new efficient methods to analyze change patterns are required.