Articles | Volume 14, issue 8
https://doi.org/10.5194/tc-14-2629-2020
© Author(s) 2020. 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-14-2629-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Classification of sea ice types in Sentinel-1 synthetic aperture radar images
Jeong-Won Park
CORRESPONDING AUTHOR
Ocean and Sea Ice Remote Sensing Group, Nansen Environmental and
Remote Sensing Center, 5006 Bergen, Norway
Unit of Arctic Sea Ice Prediction, Korea Polar Research Institute,
Incheon, 21990, South Korea
Anton Andreevich Korosov
Ocean and Sea Ice Remote Sensing Group, Nansen Environmental and
Remote Sensing Center, 5006 Bergen, Norway
Mohamed Babiker
Ocean and Sea Ice Remote Sensing Group, Nansen Environmental and
Remote Sensing Center, 5006 Bergen, Norway
Joong-Sun Won
Department of Earth System Sciences, Yonsei University, Seoul, 03722,
South Korea
Morten Wergeland Hansen
Ocean and Sea Ice Remote Sensing Group, Nansen Environmental and
Remote Sensing Center, 5006 Bergen, Norway
Department of Remote Sensing and Data Management, Norwegian
Meteorological Institute, 0371 Oslo, Norway
Hyun-Cheol Kim
Unit of Arctic Sea Ice Prediction, Korea Polar Research Institute,
Incheon, 21990, South Korea
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- A Data-Driven Deep Learning Model for Weekly Sea Ice Concentration Prediction of the Pan-Arctic During the Melting Season Y. Ren et al. 10.1109/TGRS.2022.3177600
- Arctic Sea Ice and Open Water Classification From Spaceborne Fully Polarimetric Synthetic Aperture Radar Y. Lu et al. 10.1109/TGRS.2023.3266158
- Spatio-temporal distribution of sea-ice thickness using a machine learning approach with Google Earth Engine and Sentinel-1 GRD data R. Shamshiri et al. 10.1016/j.rse.2021.112851
- Development of a Dual-Attention U-Net Model for Sea Ice and Open Water Classification on SAR Images Y. Ren et al. 10.1109/LGRS.2021.3058049
- Investigation of Polarimetric Decomposition for Arctic Summer Sea Ice Classification Using Gaofen-3 Fully Polarimetric SAR Data L. He et al. 10.1109/JSTARS.2022.3170732
- Analyzing short term spatial and temporal dynamics of water presence at a basin-scale in Mexico using SAR data A. López-Caloca et al. 10.1080/15481603.2020.1840106
- Sea Ice Elevation Measurements Using 3-D Laser Scanner M. Seo et al. 10.22761/GD.2023.0004
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- Delineating Polynya Area Using Active and Passive Microwave Sensors for the Western Ross Sea Sector of Antarctica G. Burada et al. 10.3390/rs15102545
- A Multiscale Dual Attention Network for the Automatic Classification of Polar Sea Ice and Open Water Based on Sentinel-1 SAR Images Z. Zhang et al. 10.1109/JSTARS.2024.3354912
- Supervised Classifications of Optical Water Types in Spanish Inland Waters M. Pereira-Sandoval et al. 10.3390/rs14215568
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- Automatic Selection of Relevant Attributes for Multi-Sensor Remote Sensing Analysis: A Case Study on Sea Ice Classification E. Khachatrian et al. 10.1109/JSTARS.2021.3099398
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- Presentation and evaluation of the Arctic sea ice forecasting system neXtSIM-F T. Williams et al. 10.5194/tc-15-3207-2021
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- Uncertainty-Incorporated Ice and Open Water Detection on Dual-Polarized SAR Sea Ice Imagery X. Chen et al. 10.1109/TGRS.2022.3233871
- Semantic image segmentation for sea ice parameters recognition using deep convolutional neural networks C. Zhang et al. 10.1016/j.jag.2022.102885
- Sea Ice Detection from RADARSAT-2 Quad-Polarization SAR Imagery Based on Co- and Cross-Polarization Ratio L. Zhao et al. 10.3390/rs16030515
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- An Improved Sea Ice Classification Algorithm with Gaofen-3 Dual-Polarization SAR Data Based on Deep Convolutional Neural Networks J. Zhang et al. 10.3390/rs14040906
- Robust Multiseasonal Ice Classification From High-Resolution X-Band SAR K. Kortum et al. 10.1109/TGRS.2022.3144731
- A Meta-Analysis of Sea Ice Monitoring Using Spaceborne Polarimetric SAR: Advances in the Last Decade H. Lyu et al. 10.1109/JSTARS.2022.3194324
- Synthetic Aperture Radar (SAR) for Ocean: A Review R. Asiyabi et al. 10.1109/JSTARS.2023.3310363
- Calibration of sea ice drift forecasts using random forest algorithms C. Palerme & M. Müller 10.5194/tc-15-3989-2021
- Classification of Sea Ice Types in Sentinel-1 SAR Data Using Convolutional Neural Networks H. Boulze et al. 10.3390/rs12132165
- Sea Ice Classification of SAR Imagery Based on Convolution Neural Networks S. Khaleghian et al. 10.3390/rs13091734
- Sea Ice Image Classification Based on Heterogeneous Data Fusion and Deep Learning Y. Han et al. 10.3390/rs13040592
- Changes Detection of Ice Dimension in Cheonji, Baekdu Mountain Using Sentinel-1 Image Classification S. Park et al. 10.5467/JKESS.2020.41.1.31
- Semantic Segmentation of Metoceanic Processes Using SAR Observations and Deep Learning A. Colin et al. 10.3390/rs14040851
- Isometric mapping algorithm based GNSS-R sea ice detection Y. Hu et al. 10.3934/mina.2024002
39 citations as recorded by crossref.
- Automatic Detection of Low-Backscatter Targets in the Arctic Using Wide Swath Sentinel-1 Imagery A. Cristea et al. 10.1109/JSTARS.2022.3214069
- Eddies in the Marginal Ice Zone of Fram Strait and Svalbard from Spaceborne SAR Observations in Winter I. Kozlov & O. Atadzhanova 10.3390/rs14010134
- Multi-Featured Sea Ice Classification with SAR Image Based on Convolutional Neural Network H. Wan et al. 10.3390/rs15164014
- A review of Earth Artificial Intelligence Z. Sun et al. 10.1016/j.cageo.2022.105034
- Data Augmentation for SAR Sea Ice and Water Classification Based on Per-Class Backscatter Variation With Incidence Angle Q. Wang et al. 10.1109/TGRS.2023.3291927
- Effects of Arctic sea-ice concentration on turbulent surface fluxes in four atmospheric reanalyses T. Uhlíková et al. 10.5194/tc-18-957-2024
- A Data-Driven Deep Learning Model for Weekly Sea Ice Concentration Prediction of the Pan-Arctic During the Melting Season Y. Ren et al. 10.1109/TGRS.2022.3177600
- Arctic Sea Ice and Open Water Classification From Spaceborne Fully Polarimetric Synthetic Aperture Radar Y. Lu et al. 10.1109/TGRS.2023.3266158
- Spatio-temporal distribution of sea-ice thickness using a machine learning approach with Google Earth Engine and Sentinel-1 GRD data R. Shamshiri et al. 10.1016/j.rse.2021.112851
- Development of a Dual-Attention U-Net Model for Sea Ice and Open Water Classification on SAR Images Y. Ren et al. 10.1109/LGRS.2021.3058049
- Investigation of Polarimetric Decomposition for Arctic Summer Sea Ice Classification Using Gaofen-3 Fully Polarimetric SAR Data L. He et al. 10.1109/JSTARS.2022.3170732
- Analyzing short term spatial and temporal dynamics of water presence at a basin-scale in Mexico using SAR data A. López-Caloca et al. 10.1080/15481603.2020.1840106
- Sea Ice Elevation Measurements Using 3-D Laser Scanner M. Seo et al. 10.22761/GD.2023.0004
- A bibliometric analysis on the visibility of the Sentinel-1 mission in the scientific literature B. Pham-Duc & H. Nguyen 10.1007/s12517-022-10089-3
- Enhancing sea ice segmentation in Sentinel-1 images with atrous convolutions R. Pires de Lima et al. 10.1080/01431161.2023.2248560
- Delineating Polynya Area Using Active and Passive Microwave Sensors for the Western Ross Sea Sector of Antarctica G. Burada et al. 10.3390/rs15102545
- A Multiscale Dual Attention Network for the Automatic Classification of Polar Sea Ice and Open Water Based on Sentinel-1 SAR Images Z. Zhang et al. 10.1109/JSTARS.2024.3354912
- Supervised Classifications of Optical Water Types in Spanish Inland Waters M. Pereira-Sandoval et al. 10.3390/rs14215568
- Deep Learning Based Sea Ice Classification with Gaofen-3 Fully Polarimetric SAR Data T. Zhang et al. 10.3390/rs13081452
- Automatic Selection of Relevant Attributes for Multi-Sensor Remote Sensing Analysis: A Case Study on Sea Ice Classification E. Khachatrian et al. 10.1109/JSTARS.2021.3099398
- Incidence Angle Dependencies for C-Band Backscatter From Sea Ice During Both the Winter and Melt Season T. Geldsetzer & S. Howell 10.1109/TGRS.2023.3315056
- A random forest approach to quality-checking automatic snow-depth sensor measurements G. Blandini et al. 10.5194/tc-17-5317-2023
- Fusion of SAR and Optical Image for Sea Ice Extraction W. Li et al. 10.1007/s11802-021-4824-y
- Presentation and evaluation of the Arctic sea ice forecasting system neXtSIM-F T. Williams et al. 10.5194/tc-15-3207-2021
- Recent Developments in Artificial Intelligence in Oceanography C. Dong et al. 10.34133/2022/9870950
- Monitoring Arctic thin ice: a comparison between CryoSat-2 SAR altimetry data and MODIS thermal-infrared imagery F. Müller et al. 10.5194/tc-17-809-2023
- Eastern Arctic Sea Ice Sensing: First Results from the RADARSAT Constellation Mission Data H. Lyu et al. 10.3390/rs14051165
- Cross-platform classification of level and deformed sea ice considering per-class incident angle dependency of backscatter intensity W. Guo et al. 10.5194/tc-16-237-2022
- Uncertainty-Incorporated Ice and Open Water Detection on Dual-Polarized SAR Sea Ice Imagery X. Chen et al. 10.1109/TGRS.2022.3233871
- Semantic image segmentation for sea ice parameters recognition using deep convolutional neural networks C. Zhang et al. 10.1016/j.jag.2022.102885
- Sea Ice Detection from RADARSAT-2 Quad-Polarization SAR Imagery Based on Co- and Cross-Polarization Ratio L. Zhao et al. 10.3390/rs16030515
- Sea Ice Extraction via Remote Sensing Imagery: Algorithms, Datasets, Applications and Challenges W. Huang et al. 10.3390/rs16050842
- Sea ice classification of TerraSAR-X ScanSAR images for the MOSAiC expedition incorporating per-class incidence angle dependency of image texture W. Guo et al. 10.5194/tc-17-1279-2023
- Deep-Learning-Based Sea Ice Classification With Sentinel-1 and AMSR-2 Data L. Zhao et al. 10.1109/JSTARS.2023.3285857
- An Improved Sea Ice Classification Algorithm with Gaofen-3 Dual-Polarization SAR Data Based on Deep Convolutional Neural Networks J. Zhang et al. 10.3390/rs14040906
- Robust Multiseasonal Ice Classification From High-Resolution X-Band SAR K. Kortum et al. 10.1109/TGRS.2022.3144731
- A Meta-Analysis of Sea Ice Monitoring Using Spaceborne Polarimetric SAR: Advances in the Last Decade H. Lyu et al. 10.1109/JSTARS.2022.3194324
- Synthetic Aperture Radar (SAR) for Ocean: A Review R. Asiyabi et al. 10.1109/JSTARS.2023.3310363
- Calibration of sea ice drift forecasts using random forest algorithms C. Palerme & M. Müller 10.5194/tc-15-3989-2021
6 citations as recorded by crossref.
- Classification of Sea Ice Types in Sentinel-1 SAR Data Using Convolutional Neural Networks H. Boulze et al. 10.3390/rs12132165
- Sea Ice Classification of SAR Imagery Based on Convolution Neural Networks S. Khaleghian et al. 10.3390/rs13091734
- Sea Ice Image Classification Based on Heterogeneous Data Fusion and Deep Learning Y. Han et al. 10.3390/rs13040592
- Changes Detection of Ice Dimension in Cheonji, Baekdu Mountain Using Sentinel-1 Image Classification S. Park et al. 10.5467/JKESS.2020.41.1.31
- Semantic Segmentation of Metoceanic Processes Using SAR Observations and Deep Learning A. Colin et al. 10.3390/rs14040851
- Isometric mapping algorithm based GNSS-R sea ice detection Y. Hu et al. 10.3934/mina.2024002
Latest update: 27 Mar 2024
Short summary
A new Sentinel-1 radar-based sea ice classification algorithm is proposed. We show that the readily available ice charts from operational ice services can reduce the amount of manual work in preparation of large amounts of training/testing data and feed highly reliable data to the trainer in an efficient way. Test results showed that the classifier is capable of retrieving three generalized cover types with overall accuracy of 87 % and 67 % in the winter and summer seasons, respectively.
A new Sentinel-1 radar-based sea ice classification algorithm is proposed. We show that the...