Detecting Melt Pond Onset on Landfast Arctic Sea Ice Using a Dual C-Band Satellite Approach
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Published:2024-06-09
Issue:12
Volume:16
Page:2091
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ISSN:2072-4292
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Container-title:Remote Sensing
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language:en
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Short-container-title:Remote Sensing
Author:
Maknun Syeda Shahida1, Geldsetzer Torsten1ORCID, Nandan Vishnu123ORCID, Yackel John1, Mahmud Mallik4ORCID
Affiliation:
1. Department of Geography, University of Calgary, Calgary, AB T2N 1N4, Canada 2. Department of Electronics and Communication Engineering, Amrita University, Amritapuri 690525, Kollam, India 3. Center for Earth Observation Science, University of Manitoba, Winnipeg, MB R3T 5V6, Canada 4. Department of Geography, McGill University, Montreal, QC H3A 0B9, Canada
Abstract
The presence of melt ponds on the surface of Arctic Sea ice affects its albedo, thermal properties, and overall melting rate; thus, the detection of melt pond onset is of significant importance for understanding the Arctic’s changing climate. This study investigates the utility of a novel method for detecting the onset of melt ponds on sea ice using a satellite-based, dual-sensor C-band approach, whereby Sentinel-1 provides horizontally polarized (HH) data and Advanced SCATterometer (ASCAT) provides vertically polarized (VV) data. The co-polarized ratio (VV/HH) is used to detect the presence of melt ponds on landfast sea ice in the Canadian Arctic Archipelago in 2017 and 2018. ERA-5 air temperature and wind speed re-analysis datasets are used to establish the VV/HH threshold for pond onset detection, which have been further validated by Landsat-8 reflectance. The co-polarized ratio threshold of three standard deviations from the late winter season (April) mean co-pol ratio values are used for assessing pond onset detection associated with the air temperature and wind speed data, along with visual observations from Sentinel-1 and cloud-free Sentinel-2 imagery. In 2017, the pond onset detection rates were 70.59% for FYI and 92.3% for MYI. Results suggest that this method, because of its dual-platform application, has potential for providing large-area coverage estimation of the timing of sea ice melt pond onset using different earth observation satellites.
Funder
Maritime Awards Society of Canada Graduate Scholarship NSERC Discovery grants
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