eCite Digital Repository

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


Li, X and Ouyang, L and Hui, F and Cheng, X and Shokr, M and Heil, P, An improved automated method to detect landfast ice edge off Zhongshan Station using SAR imagery, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 11, (12) pp. 4737-4746. ISSN 1939-1404 (2018) [Refereed Article]

Copyright Statement

2018 IEEE.

DOI: doi:10.1109/JSTARS.2018.2882602


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.

Item Details

Item Type:Refereed Article
Keywords:Antarctica, landfast ice edge, SAR data
Research Division:Earth Sciences
Research Group:Hydrology
Research Field:Hydrology not elsewhere classified
Objective Division:Environmental Management
Objective Group:Coastal and estuarine systems and management
Objective Field:Assessment and management of coastal and estuarine ecosystems
UTAS Author:Heil, P (Dr Petra Heil)
ID Code:131912
Year Published:2018
Web of Science® Times Cited:7
Deposited By:CRC-Antarctic Climate & Ecosystems
Deposited On:2019-04-11
Last Modified:2019-05-13

Repository Staff Only: item control page