On the Detection and Long-Term Path Visualisation of A-68 Iceberg
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 se...
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ftmdpi:oai:mdpi.com:/2072-4292/13/3/460/ 2023-08-20T04:02:27+02:00 On the Detection and Long-Term Path Visualisation of A-68 Iceberg Ludwin Lopez-Lopez Flavio Parmiggiani Miguel Moctezuma-Flores Lorenzo Guerrieri agris 2021-01-28 application/pdf https://doi.org/10.3390/rs13030460 EN eng Multidisciplinary Digital Publishing Institute Ocean Remote Sensing https://dx.doi.org/10.3390/rs13030460 https://creativecommons.org/licenses/by/4.0/ Remote Sensing; Volume 13; Issue 3; Pages: 460 SAR image processing A-68 iceberg stochastic processes Text 2021 ftmdpi https://doi.org/10.3390/rs13030460 2023-08-01T00:57:31Z 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. Text Antarc* Antarctic Antarctic Peninsula Ice Shelf Iceberg* MDPI Open Access Publishing Antarctic The Antarctic Antarctic Peninsula Remote Sensing 13 3 460 |
institution |
Open Polar |
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MDPI Open Access Publishing |
op_collection_id |
ftmdpi |
language |
English |
topic |
SAR image processing A-68 iceberg stochastic processes |
spellingShingle |
SAR image processing A-68 iceberg stochastic processes Ludwin Lopez-Lopez Flavio Parmiggiani Miguel Moctezuma-Flores Lorenzo Guerrieri On the Detection and Long-Term Path Visualisation of A-68 Iceberg |
topic_facet |
SAR image processing A-68 iceberg stochastic processes |
description |
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. |
format |
Text |
author |
Ludwin Lopez-Lopez Flavio Parmiggiani Miguel Moctezuma-Flores Lorenzo Guerrieri |
author_facet |
Ludwin Lopez-Lopez Flavio Parmiggiani Miguel Moctezuma-Flores Lorenzo Guerrieri |
author_sort |
Ludwin Lopez-Lopez |
title |
On the Detection and Long-Term Path Visualisation of A-68 Iceberg |
title_short |
On the Detection and Long-Term Path Visualisation of A-68 Iceberg |
title_full |
On the Detection and Long-Term Path Visualisation of A-68 Iceberg |
title_fullStr |
On the Detection and Long-Term Path Visualisation of A-68 Iceberg |
title_full_unstemmed |
On the Detection and Long-Term Path Visualisation of A-68 Iceberg |
title_sort |
on the detection and long-term path visualisation of a-68 iceberg |
publisher |
Multidisciplinary Digital Publishing Institute |
publishDate |
2021 |
url |
https://doi.org/10.3390/rs13030460 |
op_coverage |
agris |
geographic |
Antarctic The Antarctic Antarctic Peninsula |
geographic_facet |
Antarctic The Antarctic Antarctic Peninsula |
genre |
Antarc* Antarctic Antarctic Peninsula Ice Shelf Iceberg* |
genre_facet |
Antarc* Antarctic Antarctic Peninsula Ice Shelf Iceberg* |
op_source |
Remote Sensing; Volume 13; Issue 3; Pages: 460 |
op_relation |
Ocean Remote Sensing https://dx.doi.org/10.3390/rs13030460 |
op_rights |
https://creativecommons.org/licenses/by/4.0/ |
op_doi |
https://doi.org/10.3390/rs13030460 |
container_title |
Remote Sensing |
container_volume |
13 |
container_issue |
3 |
container_start_page |
460 |
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1774712897931313152 |