Efficient Location and Extraction of the Iceberg Calved Areas of the Antarctic Ice Shelves

• Published in: Remote Sensing
• Main Authors: Mengzhen Qi, Yan Liu, Yijing Lin, Fengming Hui, Teng Li, Xiao Cheng
• Format: Text
• Language: English
• Published: Multidisciplinary Digital Publishing Institute 2020
• Subjects: Antarctica; ice shelves; iceberg calving; coastline; ice velocity; remote sensing; Antarctic; The Antarctic; The Sentinel; Antarc*; Ice Sheet; Ice Shelf; Ice Shelves; Iceberg*
• Online Access: https://doi.org/10.3390/rs12162658

Continuous, rapid, and precise monitoring of calving events contributes to an in-depth understanding of calving mechanisms, which have the potential to cause significant mass loss from the Antarctic ice sheet. The difficulties in the precise monitoring of iceberg calving lie with the coexistence of ice shelf advances and calving. The manual location of iceberg calving is time-consuming and painstaking, while achieving precise extraction has mostly relied on the surface textural characteristics of the ice shelves and the quality of the images. Here, we propose a new and efficient method of separating the expansion and calving processes of ice shelves. We visualized the extension process by simulating a new coastline, based on the ice velocity, and detected the calved area using the simulated coastline and single-temporal post-calving images. We extensively tested the validity of this method by extracting four annual calving datasets (from August 2015 to August 2019) from the Sentinel-1 synthetic aperture radar mosaic of the Antarctic coastline. A total of 2032 annual Antarctic calving events were detected, with areas ranging from 0.05 km2 to 6141.0 km2, occurring on almost every Antarctic ice shelf. The extraction accuracy of the calved area depends on the positioning accuracy of the simulated coastline and the spatial resolution of the images. The positioning error of the simulated coastline is less than one pixel, and the determined minimum valid extraction area is 0.05 km2, when based on 75 m resolution images. Our method effectively avoids repetition and omission errors during the calved area extraction process. Furthermore, its efficiency is not affected by the surface textural characteristics of the calving fronts and the various changes in the frontal edge velocity, which makes it fully applicable to the rapid and accurate extraction of different calving types.