Object-based detection of linear kinematic features in sea ice
Source at: https://doi.org/10.3390/rs9050493 Inhomogenities in the sea ice motion field cause deformation zones, such as leads, cracks and pressure ridges. Due to their long and often narrow shape, those structures are referred to as Linear Kinematic Features (LKFs). In this paper we specifically ad...
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Online Access: | https://hdl.handle.net/10037/12575 https://doi.org/10.3390/rs9050493 |
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ftunivtroemsoe:oai:munin.uit.no:10037/12575 2023-05-15T18:17:38+02:00 Object-based detection of linear kinematic features in sea ice Linow, Stefanie Dierking, Wolfgang Fritz Otto 2017-05-18 https://hdl.handle.net/10037/12575 https://doi.org/10.3390/rs9050493 eng eng MDPI Remote Sensing Linow, S. & Dierking, W. F. O. (2017). Object-based detection of linear kinematic features in sea ice. Remote Sensing, 9(5), 1-15. https://doi.org/10.3390/rs9050493 FRIDAID 1526052 doi:10.3390/rs9050493 2072-4292 https://hdl.handle.net/10037/12575 openAccess VDP::Matematikk og Naturvitenskap: 400::Geofag: 450::Kvartærgeologi glasiologi: 465 VDP::Mathematics and natural science: 400::Geosciences: 450::Quaternary geology glaciology: 465 Journal article Tidsskriftartikkel Peer reviewed 2017 ftunivtroemsoe https://doi.org/10.3390/rs9050493 2021-06-25T17:55:39Z Source at: https://doi.org/10.3390/rs9050493 Inhomogenities in the sea ice motion field cause deformation zones, such as leads, cracks and pressure ridges. Due to their long and often narrow shape, those structures are referred to as Linear Kinematic Features (LKFs). In this paper we specifically address the identification and characterization of variations and discontinuities in the spatial distribution of the total deformation, which appear as LKFs. The distribution of LKFs in the ice cover of the polar oceans is an important factor influencing the exchange of heat and matter at the ocean-atmosphere interface. Current analyses of the sea ice deformation field often ignore the spatial/geographical context of individual structures, e.g., their orientation relative to adjacent deformation zones. In this study, we adapt image processing techniques to develop a method for LKF detection which is able to resolve individual features. The data are vectorized to obtain results on an object-based level. We then apply a semantic postprocessing step to determine the angle of junctions and between crossing structures. The proposed object detection method is carefully validated. We found a localization uncertainty of 0.75 pixel and a length error of 12% in the identified LKFs. The detected features can be individually traced to their geographical position. Thus, a wide variety of new metrics for ice deformation can be easily derived, including spatial parameters as well as the temporal stability of individual features. Article in Journal/Newspaper Sea ice University of Tromsø: Munin Open Research Archive Remote Sensing 9 5 493 |
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Open Polar |
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University of Tromsø: Munin Open Research Archive |
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ftunivtroemsoe |
language |
English |
topic |
VDP::Matematikk og Naturvitenskap: 400::Geofag: 450::Kvartærgeologi glasiologi: 465 VDP::Mathematics and natural science: 400::Geosciences: 450::Quaternary geology glaciology: 465 |
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VDP::Matematikk og Naturvitenskap: 400::Geofag: 450::Kvartærgeologi glasiologi: 465 VDP::Mathematics and natural science: 400::Geosciences: 450::Quaternary geology glaciology: 465 Linow, Stefanie Dierking, Wolfgang Fritz Otto Object-based detection of linear kinematic features in sea ice |
topic_facet |
VDP::Matematikk og Naturvitenskap: 400::Geofag: 450::Kvartærgeologi glasiologi: 465 VDP::Mathematics and natural science: 400::Geosciences: 450::Quaternary geology glaciology: 465 |
description |
Source at: https://doi.org/10.3390/rs9050493 Inhomogenities in the sea ice motion field cause deformation zones, such as leads, cracks and pressure ridges. Due to their long and often narrow shape, those structures are referred to as Linear Kinematic Features (LKFs). In this paper we specifically address the identification and characterization of variations and discontinuities in the spatial distribution of the total deformation, which appear as LKFs. The distribution of LKFs in the ice cover of the polar oceans is an important factor influencing the exchange of heat and matter at the ocean-atmosphere interface. Current analyses of the sea ice deformation field often ignore the spatial/geographical context of individual structures, e.g., their orientation relative to adjacent deformation zones. In this study, we adapt image processing techniques to develop a method for LKF detection which is able to resolve individual features. The data are vectorized to obtain results on an object-based level. We then apply a semantic postprocessing step to determine the angle of junctions and between crossing structures. The proposed object detection method is carefully validated. We found a localization uncertainty of 0.75 pixel and a length error of 12% in the identified LKFs. The detected features can be individually traced to their geographical position. Thus, a wide variety of new metrics for ice deformation can be easily derived, including spatial parameters as well as the temporal stability of individual features. |
format |
Article in Journal/Newspaper |
author |
Linow, Stefanie Dierking, Wolfgang Fritz Otto |
author_facet |
Linow, Stefanie Dierking, Wolfgang Fritz Otto |
author_sort |
Linow, Stefanie |
title |
Object-based detection of linear kinematic features in sea ice |
title_short |
Object-based detection of linear kinematic features in sea ice |
title_full |
Object-based detection of linear kinematic features in sea ice |
title_fullStr |
Object-based detection of linear kinematic features in sea ice |
title_full_unstemmed |
Object-based detection of linear kinematic features in sea ice |
title_sort |
object-based detection of linear kinematic features in sea ice |
publisher |
MDPI |
publishDate |
2017 |
url |
https://hdl.handle.net/10037/12575 https://doi.org/10.3390/rs9050493 |
genre |
Sea ice |
genre_facet |
Sea ice |
op_relation |
Remote Sensing Linow, S. & Dierking, W. F. O. (2017). Object-based detection of linear kinematic features in sea ice. Remote Sensing, 9(5), 1-15. https://doi.org/10.3390/rs9050493 FRIDAID 1526052 doi:10.3390/rs9050493 2072-4292 https://hdl.handle.net/10037/12575 |
op_rights |
openAccess |
op_doi |
https://doi.org/10.3390/rs9050493 |
container_title |
Remote Sensing |
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9 |
container_issue |
5 |
container_start_page |
493 |
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1766192205622411264 |