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Towards Forecasting Future Snow Cover Dynamics in the European Alps—The Potential of Long Optical Remote-Sensing Time Series

Köhler, Jonas und Bauer, André und Dietz, Andreas J. und Künzer, Claudia (2022) Towards Forecasting Future Snow Cover Dynamics in the European Alps—The Potential of Long Optical Remote-Sensing Time Series. Remote Sensing, 14 (18), Seiten 1-30. Multidisciplinary Digital Publishing Institute (MDPI). doi: 10.3390/rs14184461. ISSN 2072-4292.

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Offizielle URL: https://dx.doi.org/10.3390/rs14184461

Kurzfassung

Snow is a vital environmental parameter and dynamically responsive to climate change, particularly in mountainous regions. Snow cover can be monitored at variable spatial scales using Earth Observation (EO) data. Long-lasting remote sensing missions enable the generation of multi-decadal time series and thus the detection of long-term trends. However, there have been few attempts to use these to model future snow cover dynamics. In this study, we, therefore, explore the potential of such time series to forecast the Snow Line Elevation (SLE) in the European Alps. We generate monthly SLE time series from the entire Landsat archive (1985–2021) in 43 Alpine catchments. Positive long-term SLE change rates are detected, with the highest rates (5–8 m/y) in the Western and Central Alps. We utilize this SLE dataset to implement and evaluate seven uni-variate time series modeling and forecasting approaches. The best results were achieved by Random Forests, with a Nash–Sutcliffe efficiency (NSE) of 0.79 and a Mean Absolute Error (MAE) of 258 m, Telescope (0.76, 268 m), and seasonal ARIMA (0.75, 270 m). Since the model performance varies strongly with the input data, we developed a combined forecast based on the best-performing methods in each catchment. This approach was then used to forecast the SLE for the years 2022–2029. In the majority of the catchments, the shift of the forecast median SLE level retained the sign of the long-term trend. In cases where a deviating SLE dynamic is forecast, a discussion based on the unique properties of the catchment and past SLE dynamics is required. In the future, we expect major improvements in our SLE forecasting efforts by including external predictor variables in a multi-variate modeling approach.

elib-URL des Eintrags:https://elib.dlr.de/188379/
Dokumentart:Zeitschriftenbeitrag
Titel:Towards Forecasting Future Snow Cover Dynamics in the European Alps—The Potential of Long Optical Remote-Sensing Time Series
Autoren:
AutorenInstitution oder E-Mail-AdresseAutoren-ORCID-iDORCID Put Code
Köhler, JonasJonas.Koehler (at) dlr.dehttps://orcid.org/0000-0001-6086-2364NICHT SPEZIFIZIERT
Bauer, Andréandre.bauer (at) uni-wuerzburg.dehttps://orcid.org/0000-0002-5582-8812NICHT SPEZIFIZIERT
Dietz, Andreas J.Andreas.Dietz (at) dlr.dehttps://orcid.org/0000-0002-5733-7136NICHT SPEZIFIZIERT
Künzer, ClaudiaClaudia.Kuenzer (at) dlr.deNICHT SPEZIFIZIERTNICHT SPEZIFIZIERT
Datum:7 September 2022
Erschienen in:Remote Sensing
Referierte Publikation:Ja
Open Access:Ja
Gold Open Access:Ja
In SCOPUS:Ja
In ISI Web of Science:Ja
Band:14
DOI:10.3390/rs14184461
Seitenbereich:Seiten 1-30
Verlag:Multidisciplinary Digital Publishing Institute (MDPI)
ISSN:2072-4292
Status:veröffentlicht
Stichwörter:forecast; Earth Observation; time series; Snow Line Elevation; Alps; mountains; environmental modeling; machine learning
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 - Projekt Polar Monitor
Standort: Oberpfaffenhofen
Institute & Einrichtungen:Deutsches Fernerkundungsdatenzentrum
Deutsches Fernerkundungsdatenzentrum > Dynamik der Landoberfläche
Hinterlegt von: Köhler, Jonas
Hinterlegt am:22 Sep 2022 09:55
Letzte Änderung:22 Sep 2022 09:55

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