TY - JOUR
T1 - Sentinel-1 time series for mapping snow cover depletion and timing of snowmelt in Arctic periglacial environments
T2 - Case study from Zackenberg and Kobbefjord, Greenland
AU - Buchelt, Sebastian
AU - Skov, Kirstine
AU - Rasmussen, Kerstin Krøier
AU - Ullmann, Tobias
N1 - Publisher Copyright:
© 2022 The Author(s).
PY - 2022/2
Y1 - 2022/2
N2 - Snow cover (SC) and timing of snowmelt are key regulators of a wide range of Arctic ecosystem functions. Both are strongly inï¬ uenced by the ampliï¬?ed Arctic warming and essential variables to understand environmental changes and their dynamics. This study evaluates the potential of Sentinel-1 (S-1) synthetic aperture radar (SAR) time series for monitoring SC depletion and snowmelt with high spatiotemporal resolution to capture their understudied small-scale heterogeneity. We use 97 dual-polarized S-1 SAR images acquired over northeastern Greenland and 94 over southwestern Greenland in the interferometric wide swath mode from the years 2017 and 2018. Comparison of S-1 intensity against SC fraction maps derived from orthorectiï¬?ed terrestrial time-lapse imagery indicates that SAR backscatter can increase before a decrease in SC fraction is observed. Hence, the increase in backscatter is related to changing snowpack properties during the runoff phase as well as decreasing SC fraction. We here present a novel empirical approach based on the temporal evolution of the SAR signal to identify start of runoff (SOR), end of snow cover (EOS) and SC extent for each S-1 observation date during melt using backscatter thresholds as well as the derivative. Comparison of SC with orthorectified time-lapse imagery indicates that HV polarization outperforms HH when using a global threshold. The derivative avoids manual selection of thresholds and adapts to different environmental settings and seasonal conditions. With a global configuration (threshold: 4ĝ€¯dB; polarization: HV) as well as with the derivative, the overall accuracy of SC maps was in all cases above 75ĝ€¯% and in more than half of cases above 90ĝ€¯%. Based on the physical principle of SAR backscatter during snowmelt, our approach is expected to work well in other low-vegetation areas and, hence, could support large-scale SC monitoring at high spatiotemporal resolution (20ĝ€¯m, 6ĝ€¯d) with high accuracy.
AB - Snow cover (SC) and timing of snowmelt are key regulators of a wide range of Arctic ecosystem functions. Both are strongly inï¬ uenced by the ampliï¬?ed Arctic warming and essential variables to understand environmental changes and their dynamics. This study evaluates the potential of Sentinel-1 (S-1) synthetic aperture radar (SAR) time series for monitoring SC depletion and snowmelt with high spatiotemporal resolution to capture their understudied small-scale heterogeneity. We use 97 dual-polarized S-1 SAR images acquired over northeastern Greenland and 94 over southwestern Greenland in the interferometric wide swath mode from the years 2017 and 2018. Comparison of S-1 intensity against SC fraction maps derived from orthorectiï¬?ed terrestrial time-lapse imagery indicates that SAR backscatter can increase before a decrease in SC fraction is observed. Hence, the increase in backscatter is related to changing snowpack properties during the runoff phase as well as decreasing SC fraction. We here present a novel empirical approach based on the temporal evolution of the SAR signal to identify start of runoff (SOR), end of snow cover (EOS) and SC extent for each S-1 observation date during melt using backscatter thresholds as well as the derivative. Comparison of SC with orthorectified time-lapse imagery indicates that HV polarization outperforms HH when using a global threshold. The derivative avoids manual selection of thresholds and adapts to different environmental settings and seasonal conditions. With a global configuration (threshold: 4ĝ€¯dB; polarization: HV) as well as with the derivative, the overall accuracy of SC maps was in all cases above 75ĝ€¯% and in more than half of cases above 90ĝ€¯%. Based on the physical principle of SAR backscatter during snowmelt, our approach is expected to work well in other low-vegetation areas and, hence, could support large-scale SC monitoring at high spatiotemporal resolution (20ĝ€¯m, 6ĝ€¯d) with high accuracy.
UR - https://www.scopus.com/pages/publications/85125293807
U2 - 10.5194/tc-16-625-2022
DO - 10.5194/tc-16-625-2022
M3 - Journal article
AN - SCOPUS:85125293807
SN - 1994-0416
VL - 16
SP - 625
EP - 646
JO - Cryosphere
JF - Cryosphere
IS - 2
ER -