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Object-Based Detection of Linear Kinematic Features in Sea Ice

Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, 27570 Bremerhaven, Germany
Centre for Integrated Remote Sensing and Forecasting for Arctic Operations, University of Tromsø, 9037 Tromsø, Norway
Authors to whom correspondence should be addressed.
Academic Editors: Deepak R. Mishra and Prasad S. Thenkabail
Remote Sens. 2017, 9(5), 493;
Received: 10 February 2017 / Revised: 10 May 2017 / Accepted: 12 May 2017 / Published: 18 May 2017
PDF [9559 KB, uploaded 18 May 2017]


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. View Full-Text
Keywords: image processing; computer vision; object detection; sea ice deformation; linear kinematic features; RGPS; Arctic ocean image processing; computer vision; object detection; sea ice deformation; linear kinematic features; RGPS; Arctic ocean

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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

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Linow, S.; Dierking, W. Object-Based Detection of Linear Kinematic Features in Sea Ice. Remote Sens. 2017, 9, 493.

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