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An improved automated method to detect landfast ice edge off Zhongshan Station using SAR imagery

journal contribution
posted on 2023-05-20, 02:45 authored by Li, X, Ouyang, L, Hui, F, Cheng, X, Shokr, M, Petra HeilPetra Heil
Landfast ice is an important component of the Antarctic sea ice. Its edge generally advances offshore to its annual maximum extent by mid-winter before retreating later in spring. This study presents an automated method to detect the seaward landfast ice edge (SLIE) at its maximum extent in the beginning in the austral spring (October) for a region northeast of the Amery Ice Shelf, East Antarctic. Here, the net gradient difference algorithm developed by Mahoney [1] has been extended to include the medium edge detection method to automatically delineate the SLIE using the sequential SAR data. The underlying method is to use a spatial gradient operation to identify potential edge pixels, before applying the noise removal using a baseline (2000-2008) SLIE, and a pixel connection technique to generate a contiguous edge. We show that in 2016, the SLIE extended 20 km (25%) further equatorward than in 2008. Good agreement has been achieved between the SLIE derived from our automated method and the manual SLIE extraction using the original SAR as well as a near-coincident Landsat-8 OLI image. The error in the automated approach is minimized when using three to four calibrated SAR images, all with the same incident angle and the maximum separation between them is less than 20 days. Our results confirm the potential of the method for operational application, and we expect it to promote the study of Antarctic landfast ice.


Publication title

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing










Institute for Marine and Antarctic Studies


Institute of Electrical and Electronics Engineers

Place of publication

United States

Rights statement

© 2018 IEEE.

Repository Status

  • Restricted

Socio-economic Objectives

Assessment and management of coastal and estuarine ecosystems

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