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Monitoring Inter- and Intra-Seasonal Dynamics of Rapidly Degrading Ice-Rich Permafrost Riverbanks in the Lena Delta with TerraSAR-X Time Series

Stettner, Samuel and Beamish, Alison L. and Bartsch, Annett and Heim, Birgit and Grosse, Guido and Roth, Achim and Lantuit, Hugues (2018) Monitoring Inter- and Intra-Seasonal Dynamics of Rapidly Degrading Ice-Rich Permafrost Riverbanks in the Lena Delta with TerraSAR-X Time Series. Remote Sensing, 10 (51), pp. 1-20. Multidisciplinary Digital Publishing Institute (MDPI). doi: 10.3390/rs10010051. ISSN 2072-4292.

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Official URL: http://www.mdpi.com/2072-4292/10/1/51/pdf

Abstract

Arctic warming is leading to substantial changes to permafrost including rapid Degradation of ice and ice-rich coasts and riverbanks. In this study, we present and evaluate a high spatiotemporal resolution three-year time series of X-Band microwave satellite data from the TerraSAR-X (TSX) satellite to quantify cliff-top erosion (CTE) of an ice-rich permafrost riverbank in the central Lena Delta. We apply a threshold on TSX backscatter images and automatically extract cliff-top lines to derive intra- and inter-annual CTE. In order to examine the drivers of erosion we statistically compare CTE with climatic baseline data using linear mixed models and analysis of variance (ANOVA). Our evaluation of TSX-derived CTE against annual optical-derived CTE and seasonal in situ measurements showed good agreement between all three datasets. We observed continuous erosion from June to September in 2014 and 2015 with no significant seasonality across the thawing season. We found the highest net annual cliff-top erosion of 6.9 m in 2014, in accordance with above-average mean temperatures and thawing degree days as well as low precipitation. We found high net annual erosion and erosion variability in 2015 associated with moderate mean temperatures but above average precipitation. According to linear mixed models, climate parameters alone could not explain intra-seasonal erosional patterns and additional factors such as ground ice content likely drive the observed erosion. Finally, mean backscatter intensity on the cliff surface decreased from -5.29 to -6.69 dB from 2013 to 2015, respectively, likely resulting from changes in surface geometry and properties that could be connected to partial slope stabilization. Overall, we conclude that X-Band backscatter time series can successfully be used to complement optical remote sensing and in situ monitoring of rapid tundra permafrost erosion at riverbanks and coasts by reliably providing information about intra-seasonal dynamics.

Item URL in elib:https://elib.dlr.de/117946/
Document Type:Article
Title:Monitoring Inter- and Intra-Seasonal Dynamics of Rapidly Degrading Ice-Rich Permafrost Riverbanks in the Lena Delta with TerraSAR-X Time Series
Authors:
AuthorsInstitution or Email of AuthorsAuthor's ORCID iDORCID Put Code
Stettner, SamuelAlfred-Wegener-Institut, PotsdamUNSPECIFIEDUNSPECIFIED
Beamish, Alison L.Alfred-Wegener-Institut, PotsdamUNSPECIFIEDUNSPECIFIED
Bartsch, AnnettZentralanstalt für Meteorologie und GeodynamikUNSPECIFIEDUNSPECIFIED
Heim, BirgitAlfred-Wegener-Institut, PotsdamUNSPECIFIEDUNSPECIFIED
Grosse, GuidoAlfred-Wegener-Institut, PotsdamUNSPECIFIEDUNSPECIFIED
Roth, AchimDLR-DFDUNSPECIFIEDUNSPECIFIED
Lantuit, HuguesAlfred-Wegener-Institut, PotsdamUNSPECIFIEDUNSPECIFIED
Date:2018
Journal or Publication Title:Remote Sensing
Refereed publication:Yes
Open Access:Yes
Gold Open Access:Yes
In SCOPUS:Yes
In ISI Web of Science:Yes
Volume:10
DOI:10.3390/rs10010051
Page Range:pp. 1-20
Publisher:Multidisciplinary Digital Publishing Institute (MDPI)
Series Name:Remote Sensing of Arctic Tundra
ISSN:2072-4292
Status:Published
Keywords:SAR; backscatter; X-Band; erosion; thermal erosion
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Earth Observation
DLR - Research area:Raumfahrt
DLR - Program:R EO - Earth Observation
DLR - Research theme (Project):R - TSX/TDX Payload Ground Segment
Location: Oberpfaffenhofen
Institutes and Institutions:German Remote Sensing Data Center > Land Surface
Deposited By: Roth, Achim
Deposited On:09 Jan 2018 13:36
Last Modified:14 Dec 2019 04:26

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