On the Detection and Long-Term Path Visualisation of A-68 Iceberg

• Published in: Remote Sensing
• Main Authors: Ludwin Lopez-Lopez, Flavio Parmiggiani, Miguel Moctezuma-Flores, Lorenzo Guerrieri
• Format: Article in Journal/Newspaper
• Language: English
• Published: MDPI AG 2021
• Subjects: SAR image processing; A-68 iceberg; stochastic processes; Science; Q; Antarctic; Antarctic Peninsula; The Antarctic; Antarc*; Ice Shelf; Iceberg*
• Online Access: https://doi.org/10.3390/rs13030460; https://doaj.org/article/b9b372a16cea4bd1a127a1cdbde39f3d

The article presents a methodology for examining a temporal sequence of synthetic aperture radar (SAR) images, as applied to the detection of the A-68 iceberg and its drifting trajectory. Using an improved image processing scheme, the analysis covers a period of eighteen months and makes use of a set of Sentinel-1 images. A-68 iceberg calved from the Larsen C ice shelf in July 2017 and is one of the largest icebergs observed by remote sensing on record. After the calving, there was only a modest decrease in the area (about 1%) in the first six months. It has been drifting along the east coast of the Antarctic Peninsula, and is expected to continue its path for more than a decade. It is important to track the huge A-68 iceberg to retrieve information on the physics of iceberg dynamics and for maritime security reasons. Two relevant problems are addressed by the image processing scheme presented here: (a) How to achieve quasi-automatic analysis using a fuzzy logic approach to image contrast enhancement, and (b) The use of ferromagnetic concepts to define a stochastic segmentation. The Ising equation is used to model the energy function of the process, and the segmentation is the result of a stochastic minimization.