Sea ice drift vector extraction based on feature matching using CS-1 Images
Abstract The study emphasizes the crucial role of sea ice drift in Arctic climate research and the protection of human activities. Employing C-SAR/01 (CS-1) imagery as the primary data source, the study assesses the effectiveness of the ORB feature matching algorithm for extracting Arctic Sea ice dr...
| Published in: | Journal of Physics: Conference Series |
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| Main Authors: | , |
| Format: | Article in Journal/Newspaper |
| Language: | unknown |
| Published: |
IOP Publishing
2024
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| Subjects: | |
| Online Access: | http://dx.doi.org/10.1088/1742-6596/2718/1/012012 https://iopscience.iop.org/article/10.1088/1742-6596/2718/1/012012 https://iopscience.iop.org/article/10.1088/1742-6596/2718/1/012012/pdf |
| Summary: | Abstract The study emphasizes the crucial role of sea ice drift in Arctic climate research and the protection of human activities. Employing C-SAR/01 (CS-1) imagery as the primary data source, the study assesses the effectiveness of the ORB feature matching algorithm for extracting Arctic Sea ice drift vectors. Additionally, it investigates the spatial distribution variations in the drift vectors extracted from the HH and HV polarization channels. The accuracy of the extracted drift vectors is validated using manually extracted sea ice drift data. Experimental results reveal a significant disparity in the number of drift vectors extracted from CS-1 HV polarization images compared to HH polarization images. The sea ice drift vectors extracted using the Oriented fast and Roasted Bried (ORB) operator demonstrate an average velocity error of less than 0.27 cm/s (0.31 km/d) and an average direction error of less than 5.66° in HV polarization images. |
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