Articles | Volume 17, issue 3
https://doi.org/10.5194/tc-17-1279-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/tc-17-1279-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
16 Mar 2023
Research article |
| 16 Mar 2023
| 16 Mar 2023
Sea ice classification of TerraSAR-X ScanSAR images for the MOSAiC expedition incorporating per-class incidence angle dependency of image texture
Wenkai Guo
CORRESPONDING AUTHOR
Department of Physics and Technology, UiT The Arctic University of Norway, Tromsø, Norway
Polona Itkin
Department of Physics and Technology, UiT The Arctic University of Norway, Tromsø, Norway
Suman Singha
Remote Sensing Technology Institute (IMF), German Aerospace Center (DLR), Bremen, Germany
currently at: National Center for Climate Research (NCKF), Danish Meteorological Institute (DMI), Copenhagen, Denmark
Anthony P. Doulgeris
Department of Physics and Technology, UiT The Arctic University of Norway, Tromsø, Norway
Malin Johansson
Department of Physics and Technology, UiT The Arctic University of Norway, Tromsø, Norway
Gunnar Spreen
Institute of Environmental Physics, University of Bremen, Bremen, Germany
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Cited
13 citations as recorded by crossref.
- The MOSAiC Distributed Network: Observing the coupled Arctic system with multidisciplinary, coordinated platforms B. Rabe et al. 10.1525/elementa.2023.00103
- MMSeaIce: a collection of techniques for improving sea ice mapping with a multi-task model X. Chen et al. 10.5194/tc-18-1621-2024
- Mosaicking and Correction Method of Gaofen-3 ScanSAR Images in Coastal Areas with Subswath Overlap Range Constraints J. Wang et al. 10.3390/jmse12122277
- Co-located OLCI optical imagery and SAR altimetry from Sentinel-3 for enhanced Arctic spring sea ice surface classification W. Chen et al. 10.3389/frsen.2024.1401653
- SAR deep learning sea ice retrieval trained with airborne laser scanner measurements from the MOSAiC expedition K. Kortum et al. 10.5194/tc-18-2207-2024
- Sea Ice Extraction via Remote Sensing Imagery: Algorithms, Datasets, Applications and Challenges W. Huang et al. 10.3390/rs16050842
- Formation and fate of freshwater on an ice floe in the Central Arctic M. Smith et al. 10.5194/tc-19-619-2025
- Arctic Sea ice leads detected using sentinel-1B SAR image and their responses to atmosphere circulation and sea ice dynamics M. Qu et al. 10.1016/j.rse.2024.114193
- Novel methods to study sea ice deformation, linear kinematic features and coherent dynamic clusters from imaging remote sensing data P. Itkin 10.5194/tc-19-1135-2025
- Modeling Snow and Ice Microwave Emissions in the Arctic for a Multi‐Parameter Retrieval of Surface and Atmospheric Variables From Microwave Radiometer Satellite Data J. Rückert et al. 10.1029/2023EA003177
- The AutoICE Challenge A. Stokholm et al. 10.5194/tc-18-3471-2024
- Antarctic Sea Ice Extraction for Remote Sensing Images via Modified U-Net Based on Feature Enhancement Driven by Graph Convolution Network W. Feng et al. 10.3390/jmse13030439
- Spatio-temporal variability of small-scale leads based on helicopter maps of winter sea ice surface temperatures L. Thielke et al. 10.1525/elementa.2023.00023
12 citations as recorded by crossref.
- The MOSAiC Distributed Network: Observing the coupled Arctic system with multidisciplinary, coordinated platforms B. Rabe et al. 10.1525/elementa.2023.00103
- MMSeaIce: a collection of techniques for improving sea ice mapping with a multi-task model X. Chen et al. 10.5194/tc-18-1621-2024
- Mosaicking and Correction Method of Gaofen-3 ScanSAR Images in Coastal Areas with Subswath Overlap Range Constraints J. Wang et al. 10.3390/jmse12122277
- Co-located OLCI optical imagery and SAR altimetry from Sentinel-3 for enhanced Arctic spring sea ice surface classification W. Chen et al. 10.3389/frsen.2024.1401653
- SAR deep learning sea ice retrieval trained with airborne laser scanner measurements from the MOSAiC expedition K. Kortum et al. 10.5194/tc-18-2207-2024
- Sea Ice Extraction via Remote Sensing Imagery: Algorithms, Datasets, Applications and Challenges W. Huang et al. 10.3390/rs16050842
- Formation and fate of freshwater on an ice floe in the Central Arctic M. Smith et al. 10.5194/tc-19-619-2025
- Arctic Sea ice leads detected using sentinel-1B SAR image and their responses to atmosphere circulation and sea ice dynamics M. Qu et al. 10.1016/j.rse.2024.114193
- Novel methods to study sea ice deformation, linear kinematic features and coherent dynamic clusters from imaging remote sensing data P. Itkin 10.5194/tc-19-1135-2025
- Modeling Snow and Ice Microwave Emissions in the Arctic for a Multi‐Parameter Retrieval of Surface and Atmospheric Variables From Microwave Radiometer Satellite Data J. Rückert et al. 10.1029/2023EA003177
- The AutoICE Challenge A. Stokholm et al. 10.5194/tc-18-3471-2024
- Antarctic Sea Ice Extraction for Remote Sensing Images via Modified U-Net Based on Feature Enhancement Driven by Graph Convolution Network W. Feng et al. 10.3390/jmse13030439
Latest update: 29 Mar 2025
Short summary
Sea ice maps are produced to cover the MOSAiC Arctic expedition (2019–2020) and divide sea ice into scientifically meaningful classes. We use a high-resolution X-band synthetic aperture radar dataset and show how image brightness and texture systematically vary across the images. We use an algorithm that reliably corrects this effect and achieve good results, as evaluated by comparisons to ground observations and other studies. The sea ice maps are useful as a basis for future MOSAiC studies.
Sea ice maps are produced to cover the MOSAiC Arctic expedition (2019–2020) and divide sea ice...
