A practical algorithm for the retrieval of floe size distribution of Arctic sea ice from high-resolution satellite Synthetic Aperture Radar imagery
In this study, we present an algorithm for summer sea ice conditions that semi-automatically produces the floe size distribution of Arctic sea ice from high-resolution satellite Synthetic Aperture Radar data. Currently, floe size distribution data from satellite images are very rare in the literatur...
Published in: | Elementa: Science of the Anthropocene |
---|---|
Main Authors: | , , , , , , |
Format: | Article in Journal/Newspaper |
Language: | English |
Published: |
BioOne
2017
|
Subjects: | |
Online Access: | https://doi.org/10.1525/elementa.154 https://doaj.org/article/259015cc50214bb5ae865ed091d6e73f |
id |
ftdoajarticles:oai:doaj.org/article:259015cc50214bb5ae865ed091d6e73f |
---|---|
record_format |
openpolar |
spelling |
ftdoajarticles:oai:doaj.org/article:259015cc50214bb5ae865ed091d6e73f 2023-05-15T14:52:04+02:00 A practical algorithm for the retrieval of floe size distribution of Arctic sea ice from high-resolution satellite Synthetic Aperture Radar imagery Byongjun Hwang Jinchang Ren Samuel McCormack Craig Berry Ismail Ben Ayed Hans C. Graber Erchan Aptoula 2017-07-01T00:00:00Z https://doi.org/10.1525/elementa.154 https://doaj.org/article/259015cc50214bb5ae865ed091d6e73f EN eng BioOne https://www.elementascience.org/articles/154 https://doaj.org/toc/2325-1026 2325-1026 doi:10.1525/elementa.154 https://doaj.org/article/259015cc50214bb5ae865ed091d6e73f Elementa: Science of the Anthropocene, Vol 5 (2017) sea ice floe size Synthetic Aperture Radar image processing Arctic Environmental sciences GE1-350 article 2017 ftdoajarticles https://doi.org/10.1525/elementa.154 2022-12-31T03:59:17Z In this study, we present an algorithm for summer sea ice conditions that semi-automatically produces the floe size distribution of Arctic sea ice from high-resolution satellite Synthetic Aperture Radar data. Currently, floe size distribution data from satellite images are very rare in the literature, mainly due to the lack of a reliable algorithm to produce such data. Here, we developed the algorithm by combining various image analysis methods, including Kernel Graph Cuts, distance transformation and watershed transformation, and a rule-based boundary revalidation. The developed algorithm has been validated against the ground truth that was extracted manually with the aid of 1-m resolution visible satellite data. Comprehensive validation analysis has shown both perspectives and limitations. The algorithm tends to fail to detect small floes (mostly less than 100 m in mean caliper diameter) compared to ground truth, which is mainly due to limitations in water-ice segmentation. Some variability in the power law exponent of floe size distribution is observed due to the effects of control parameters in the process of de-noising, Kernel Graph Cuts segmentation, thresholds for boundary revalidation and image resolution. Nonetheless, the algorithm, for floes larger than 100 m, has shown a reasonable agreement with ground truth under various selections of these control parameters. Considering that the coverage and spatial resolution of satellite Synthetic Aperture Radar data have increased significantly in recent years, the developed algorithm opens a new possibility to produce large volumes of floe size distribution data, which is essential for improving our understanding and prediction of the Arctic sea ice cover Article in Journal/Newspaper Arctic Sea ice Directory of Open Access Journals: DOAJ Articles Arctic Elementa: Science of the Anthropocene 5 |
institution |
Open Polar |
collection |
Directory of Open Access Journals: DOAJ Articles |
op_collection_id |
ftdoajarticles |
language |
English |
topic |
sea ice floe size Synthetic Aperture Radar image processing Arctic Environmental sciences GE1-350 |
spellingShingle |
sea ice floe size Synthetic Aperture Radar image processing Arctic Environmental sciences GE1-350 Byongjun Hwang Jinchang Ren Samuel McCormack Craig Berry Ismail Ben Ayed Hans C. Graber Erchan Aptoula A practical algorithm for the retrieval of floe size distribution of Arctic sea ice from high-resolution satellite Synthetic Aperture Radar imagery |
topic_facet |
sea ice floe size Synthetic Aperture Radar image processing Arctic Environmental sciences GE1-350 |
description |
In this study, we present an algorithm for summer sea ice conditions that semi-automatically produces the floe size distribution of Arctic sea ice from high-resolution satellite Synthetic Aperture Radar data. Currently, floe size distribution data from satellite images are very rare in the literature, mainly due to the lack of a reliable algorithm to produce such data. Here, we developed the algorithm by combining various image analysis methods, including Kernel Graph Cuts, distance transformation and watershed transformation, and a rule-based boundary revalidation. The developed algorithm has been validated against the ground truth that was extracted manually with the aid of 1-m resolution visible satellite data. Comprehensive validation analysis has shown both perspectives and limitations. The algorithm tends to fail to detect small floes (mostly less than 100 m in mean caliper diameter) compared to ground truth, which is mainly due to limitations in water-ice segmentation. Some variability in the power law exponent of floe size distribution is observed due to the effects of control parameters in the process of de-noising, Kernel Graph Cuts segmentation, thresholds for boundary revalidation and image resolution. Nonetheless, the algorithm, for floes larger than 100 m, has shown a reasonable agreement with ground truth under various selections of these control parameters. Considering that the coverage and spatial resolution of satellite Synthetic Aperture Radar data have increased significantly in recent years, the developed algorithm opens a new possibility to produce large volumes of floe size distribution data, which is essential for improving our understanding and prediction of the Arctic sea ice cover |
format |
Article in Journal/Newspaper |
author |
Byongjun Hwang Jinchang Ren Samuel McCormack Craig Berry Ismail Ben Ayed Hans C. Graber Erchan Aptoula |
author_facet |
Byongjun Hwang Jinchang Ren Samuel McCormack Craig Berry Ismail Ben Ayed Hans C. Graber Erchan Aptoula |
author_sort |
Byongjun Hwang |
title |
A practical algorithm for the retrieval of floe size distribution of Arctic sea ice from high-resolution satellite Synthetic Aperture Radar imagery |
title_short |
A practical algorithm for the retrieval of floe size distribution of Arctic sea ice from high-resolution satellite Synthetic Aperture Radar imagery |
title_full |
A practical algorithm for the retrieval of floe size distribution of Arctic sea ice from high-resolution satellite Synthetic Aperture Radar imagery |
title_fullStr |
A practical algorithm for the retrieval of floe size distribution of Arctic sea ice from high-resolution satellite Synthetic Aperture Radar imagery |
title_full_unstemmed |
A practical algorithm for the retrieval of floe size distribution of Arctic sea ice from high-resolution satellite Synthetic Aperture Radar imagery |
title_sort |
practical algorithm for the retrieval of floe size distribution of arctic sea ice from high-resolution satellite synthetic aperture radar imagery |
publisher |
BioOne |
publishDate |
2017 |
url |
https://doi.org/10.1525/elementa.154 https://doaj.org/article/259015cc50214bb5ae865ed091d6e73f |
geographic |
Arctic |
geographic_facet |
Arctic |
genre |
Arctic Sea ice |
genre_facet |
Arctic Sea ice |
op_source |
Elementa: Science of the Anthropocene, Vol 5 (2017) |
op_relation |
https://www.elementascience.org/articles/154 https://doaj.org/toc/2325-1026 2325-1026 doi:10.1525/elementa.154 https://doaj.org/article/259015cc50214bb5ae865ed091d6e73f |
op_doi |
https://doi.org/10.1525/elementa.154 |
container_title |
Elementa: Science of the Anthropocene |
container_volume |
5 |
_version_ |
1766323187552878592 |