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TerraSAR-X and time-lapse photography for snow on sea-ice monitoring in Deception Bay, Nunavik

Dufour-Beauséjour, Sophie and Bernier, Monique and Wendleder, Anna and Poulin, Jimmy and Gilbert, Veronique and Tuniq, Juupi and Gauthier, Yves and Rouleau, Amélie (2018) TerraSAR-X and time-lapse photography for snow on sea-ice monitoring in Deception Bay, Nunavik. ArcticNet Annual Scientific Meeting 2018, 10.-14.Dez. 2018, Ottawa, Kanada.

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Snow is an important element of safety on the land for Inuit living in the Arctic; land users may be stranded on bare rocks for lack of snow on the ground. Snow is necessary for snowmobile transport on sea ice trails, and is closely tied to the thickness ice may reach on average in a given winter. While an observation of less snow in recent years was reported by salluimmiut (J. Tuniq, ArcticChange 2017), climate projections for 2071-2100 feature an increase in precipitation over Nunavik (Ouranos, 2018). In this context, the Safe Passage research project (Polar Knowledge Research Program), which included Ice Monitoring in Salluit, Deception and Kangiqsujuaq, also focused on snow on sea ice. This presentation will report on snow information derived from three years of Monitoring in Deception Bay, Nunavik (Hudson Strait). Time-lapse cameras have been taking hourly pictures of the bay since December 2015 as well as measuring air temperature. This database was used to develop a proxy for estimating snow accumulation on the bay. TerraSAR-X high-resolution satellite images have been acquired every 11 days since December 2015 and were analyzed to identify seasonal trends in backscattering from snow over sea ice. Fieldwork was done twice per winter since 2016 and includes snow and ice thickness measurements. Time-lapse camera pictures (N ~ 26 000) were filtered by view (four different views are acquired each hour) and visibility using machine learning (python-Tensorflow). The foreground in the field-of-view is highly exposed, and the wind-swept rocks are regularly almost snow-free. Ground pixels were classified as either snow or no snow using computer vision (python-openCV) and an average of snow cover fraction was computed daily. Daily snow accumulation was modeled as the increase in snow pixels from one day to the next, or as zero in the absence of a snow cover increase. TerraSAR-X images were processed by the German space agency (DLR) with the MultiSAR software. Backscattering statistics were computed for land pixels and water-ice Pixels seperately.This presentation will show how the snow accumulation proxy compares to snow thickness measurements and discuss the winter and spring trends seen in the X-band backscattering from snow on sea ice.

Item URL in elib:https://elib.dlr.de/124566/
Document Type:Conference or Workshop Item (Speech)
Title:TerraSAR-X and time-lapse photography for snow on sea-ice monitoring in Deception Bay, Nunavik
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Dufour-Beauséjour, SophieSophie.Dufour-Beausejour (at) ete.inrs.caUNSPECIFIED
Wendleder, Annaanna.wendleder (at) dlr.deUNSPECIFIED
Date:December 2018
Refereed publication:No
Open Access:No
Gold Open Access:No
In ISI Web of Science:No
Keywords:landfast sea ice, time-lapse photography, radar images, Nunavik, snow thickness
Event Title:ArcticNet Annual Scientific Meeting 2018
Event Location:Ottawa, Kanada
Event Type:international Conference
Event Dates:10.-14.Dez. 2018
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Earth Observation
DLR - Research area:Raumfahrt
DLR - Program:R EO - Erdbeobachtung
DLR - Research theme (Project):R - Remote sensing and geoscience
Location: Oberpfaffenhofen
Institutes and Institutions:German Remote Sensing Data Center > Land Surface Dynamics
Deposited By: Wendleder, Anna
Deposited On:08 Dec 2018 14:48
Last Modified:09 Jan 2019 20:41

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