Journal
IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING
Volume 11, Issue 5, Pages 1419-1432Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/JSTARS.2018.2806640
Keywords
Image segmentation; sea ice; sentinel-1; synthetic aperture radar
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Funding
- ArcticNet
- Phase IV
- National Natural Science Foundation of China [41501410]
- Fujian Collaborative Innovation Center for Big Data Applications in Governments
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This study aims at proposing a semiautomated sea ice segmentation workflow utilizing Sentinel-1 synthetic aperture radar imagery. The workflow consists of two main steps. First, preferable features in sea ice interpretation were determined with a random forest feature selection method. Second, an unsupervised graph-cut image segmentation was performed. The workflow was tested on 13 Sentinel-1A images from January to June 2016, and the results were evaluated on open water segmentation per ice charts provided by Canada Ice Service. The results showed that the proposed workflow was able to segment Sentinel-1 images in to appropriate number of classes, and the potential water identification rate reached 95%.
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