Abstract
The Amery Ice Shelf (AIS) dynamics and mass balance caused by iceberg calving and basal melting are significant in the ocean climate system. Using satellite imagery from Sentinel-1 SAR, we monitored the temporal and spatial variability of the frontal positions on the Amery Ice Shelf, Antarctica, from 2015 to 2021. In this paper, we propose an automatic algorithm based on the SO-CFAR strategy and a profile cumulative method for frontal line extraction. To improve the accuracy of the extracted frontal lines, we developed a framework combining the Constant False Alarm Rate (CFAR) and morphological image-processing strategies. A visual comparison between the proposed algorithm and state-of-the-art algorithm shows that our algorithm is effective in these cases including rifts, icebergs, and crevasses as well as ice-shelf surface structures. We present a detailed analysis of the temporal and spatial variability of fronts on AIS that we find, an advance of the AIS frontal line before the D28 calving event, and a continuous advance after the event. The study reveals that the AIS extent has been advanced at the rate of 1015 m/year. Studies have shown that the frontal location of AIS has continuously expanded. From March 2015 to May 2021, the frontal location of AIS expanded by 6.5 km; while the length of the AIS frontal line is relatively different after the D28 event, the length of the frontal line increased by about 7.5% during 2015 and 2021 (255.03 km increased to 273.5 km). We found a substantial increase in summer advance rates and a decrease in winter advance rates with the seasonal characteristics. We found this variability of the AIS frontal line to be in good agreement with the ice flow velocity.
Highlights
Introduction published maps and institutional affilThe fronts of ice shelves in Antarctica are critical interfaces, between the ice sheet and ocean, and their geometry and variation can significantly impact the ice shelf-ocean interaction, which further affects upstream ice sheet dynamics and sea-level rise [1]
Before the D28 detachment, five rifts were actively propagated near the AIS front among seven active rifts over the 13 ice shelves in Antarctica, where most active rifts were initiated at the Amery Ice Shelf fronts [3,4,5]
synthetic aperture radar (SAR) data with speckle noise, high interclass, and high intraclass backscatter variability degrade the image details and decrease the separability among ocean, coastal rock outcrops, sea ice, and ice shelf. Considering these characteristics, we proposed a framework combining the Constant False Alarm Rate (CFAR) and profile method to automatically detect the ice-shelf fronts in AIS by Sentinel-1 SAR data
Summary
The frontal line extraction algorithm consists of three steps: SO (Smallest of)-CFAR. 2. Methods for binary classification [26,27,28,29], morphological image processing [30,31], and maximal cumulative based frontal[26,27,28,29], point extraction [32]. CFAR are[30,31], adaptable for binary classification morphological imagedetectors processing and threshold maximal detectors that use various statistical models to detect target returns from thethreshold ice shelf cumulative based frontal point extraction [32]. The threshold for every detectors that use various statistical models to detect target returns from the icedetectshelf ing cell (sliding window) is adaptive to maintain a constant probability of a false alarm against the background clutter, such as sea ice and ocean. The maximal cumulative value-based method is method is a strategy designed for frontal point extraction.
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