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Assessing the Transferability of Neural Network-Based Sea Ice Classification between the Arctic and Antarctic

Permanent link
https://hdl.handle.net/10037/35289
DOI
https://doi.org/10.1109/IGARSS53475.2024.10641661
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Date
2024-09-05
Type
Journal article
Tidsskriftartikkel
Peer reviewed

Author
Huang, Lanqing; Johansson, Anna Malin Kristin; Hajnsek, Irena
Abstract
In this study, we trained a supervised neural network for sea ice classification using X-band SAR images obtained during an Antarctic fieldwork campaign and applied it to Arctic X-band data acquired during sea ice fieldwork campaigns. The results revealed a pronounced correlation between the predicted sea ice class and measured snow depth in the Arctic. This correlation is likely attributed to the Arctic acquisitions taking place during the cold winter conditions characterized by thicker snow layers, which resemble conditions in Antarctica.
Publisher
IEEE
Citation
Huang, Johansson A M, Hajnsek I. Assessing the Transferability of Neural Network-Based Sea Ice Classification between the Arctic and Antarctic. IEEE International Geoscience and Remote Sensing Symposium proceedings. 2024
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  • Artikler, rapporter og annet (fysikk og teknologi) [1058]
Copyright 2024 The Author(s)

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