Articles | Volume 12, issue 1
https://doi.org/10.5194/tc-12-343-2018
© Author(s) 2018. 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-12-343-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
26 Jan 2018
Research article |
| 26 Jan 2018
| 26 Jan 2018
Estimation of degree of sea ice ridging based on dual-polarized C-band SAR data
Finnish Meteorological Institute (FMI), Marine Research, Erik Palménin aukio 1, 00560 Helsinki, Finland
Markku Similä
Finnish Meteorological Institute (FMI), Marine Research, Erik Palménin aukio 1, 00560 Helsinki, Finland
Juha Karvonen
Finnish Meteorological Institute (FMI), Marine Research, Erik Palménin aukio 1, 00560 Helsinki, Finland
Mikko Lensu
Finnish Meteorological Institute (FMI), Marine Research, Erik Palménin aukio 1, 00560 Helsinki, Finland
Marko Mäkynen
Finnish Meteorological Institute (FMI), Marine Research, Erik Palménin aukio 1, 00560 Helsinki, Finland
Jouni Vainio
Finnish Meteorological Institute (FMI), Marine Research, Erik Palménin aukio 1, 00560 Helsinki, Finland
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Cited
25 citations as recorded by crossref.
- Estimation of Level and Deformed First-Year Sea Ice Surface Roughness in the Canadian Arctic Archipelago from C- and L-Band Synthetic Aperture Radar S. Cafarella et al. 10.1080/07038992.2019.1647102
- Sea-Ice Mapping of RADARSAT-2 Imagery by Integrating Spatial Contexture With Textural Features M. Jiang et al. 10.1109/JSTARS.2022.3205849
- Polarimetric SAR Applications of Sea Ice: A Review M. Shokr & M. Dabboor 10.1109/JSTARS.2023.3295735
- 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
- Sea Ice Extraction via Remote Sensing Imagery: Algorithms, Datasets, Applications and Challenges W. Huang et al. 10.3390/rs16050842
- Calibration of sea ice drift forecasts using random forest algorithms C. Palerme & M. Müller 10.5194/tc-15-3989-2021
- 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
- Satellite Observations for Detecting and Forecasting Sea-Ice Conditions: A Summary of Advances Made in the SPICES Project by the EU’s Horizon 2020 Programme M. Mäkynen et al. 10.3390/rs12071214
- Monitoring of Dangerous Ice Phenomena Using Satellite Imagery and Model Simulation V. Smirnov et al. 10.3103/S1068373919110049
- Operational Service for Mapping the Baltic Sea Landfast Ice Properties M. Mäkynen et al. 10.3390/rs12244032
- A Brief Review of Random Forests for Water Scientists and Practitioners and Their Recent History in Water Resources H. Tyralis et al. 10.3390/w11050910
- Alignment of Multifrequency SAR Images Acquired Over Sea Ice Using Drift Compensation D. Demchev et al. 10.1109/JSTARS.2023.3302576
- Arctic Sea Ice Surface Roughness Estimated from Multi-Angular Reflectance Satellite Imagery A. Nolin & E. Mar 10.3390/rs11010050
- Characterizing winter landfast sea-ice surface roughness in the Canadian Arctic Archipelago using Sentinel-1 synthetic aperture radar and the Multi-angle Imaging SpectroRadiometer R. Segal et al. 10.1017/aog.2020.48
- Big maritime data for the Baltic Sea with a focus on the winter navigation system M. Lensu & F. Goerlandt 10.1016/j.marpol.2019.02.038
- TanDEM-X multiparametric data features in sea ice classification over the Baltic sea M. Marbouti et al. 10.1080/10095020.2020.1845574
- Supplementing Remote Sensing of Ice: Deep Learning-Based Image Segmentation System for Automatic Detection and Localization of Sea-ice Formations From Close-Range Optical Images N. Panchi et al. 10.1109/JSEN.2021.3084556
- Ice ridge density signatures in high-resolution SAR images M. Lensu & M. Similä 10.5194/tc-16-4363-2022
- Estimation of degree of sea ice ridging in the Bay of Bothnia based on geolocated photon heights from ICESat-2 R. Fredensborg Hansen et al. 10.5194/tc-15-2511-2021
- Estimating the Speed of Ice-Going Ships by Integrating SAR Imagery and Ship Data from an Automatic Identification System M. Similä & M. Lensu 10.3390/rs10071132
- Remote Sensing of Ice Phenology and Dynamics of Europe’s Largest Coastal Lagoon (The Curonian Lagoon) R. Idzelytė et al. 10.3390/rs11172059
- Measuring Deformed Sea Ice in Seasonal Ice Zones Using L-Band SAR Images T. Toyota et al. 10.1109/TGRS.2020.3043335
- Interannual sea ice thickness variability in the Bay of Bothnia I. Ronkainen et al. 10.5194/tc-12-3459-2018
- Copernicus Marine Service Ocean State Report, Issue 3 K. von Schuckmann et al. 10.1080/1755876X.2019.1633075
- On Suitability of ALOS-2/PALSAR-2 Dual-Polarized SAR Data for Arctic Sea Ice Parameter Estimation J. Karvonen et al. 10.1109/TGRS.2020.2985696
25 citations as recorded by crossref.
- Estimation of Level and Deformed First-Year Sea Ice Surface Roughness in the Canadian Arctic Archipelago from C- and L-Band Synthetic Aperture Radar S. Cafarella et al. 10.1080/07038992.2019.1647102
- Sea-Ice Mapping of RADARSAT-2 Imagery by Integrating Spatial Contexture With Textural Features M. Jiang et al. 10.1109/JSTARS.2022.3205849
- Polarimetric SAR Applications of Sea Ice: A Review M. Shokr & M. Dabboor 10.1109/JSTARS.2023.3295735
- 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
- Sea Ice Extraction via Remote Sensing Imagery: Algorithms, Datasets, Applications and Challenges W. Huang et al. 10.3390/rs16050842
- Calibration of sea ice drift forecasts using random forest algorithms C. Palerme & M. Müller 10.5194/tc-15-3989-2021
- 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
- Satellite Observations for Detecting and Forecasting Sea-Ice Conditions: A Summary of Advances Made in the SPICES Project by the EU’s Horizon 2020 Programme M. Mäkynen et al. 10.3390/rs12071214
- Monitoring of Dangerous Ice Phenomena Using Satellite Imagery and Model Simulation V. Smirnov et al. 10.3103/S1068373919110049
- Operational Service for Mapping the Baltic Sea Landfast Ice Properties M. Mäkynen et al. 10.3390/rs12244032
- A Brief Review of Random Forests for Water Scientists and Practitioners and Their Recent History in Water Resources H. Tyralis et al. 10.3390/w11050910
- Alignment of Multifrequency SAR Images Acquired Over Sea Ice Using Drift Compensation D. Demchev et al. 10.1109/JSTARS.2023.3302576
- Arctic Sea Ice Surface Roughness Estimated from Multi-Angular Reflectance Satellite Imagery A. Nolin & E. Mar 10.3390/rs11010050
- Characterizing winter landfast sea-ice surface roughness in the Canadian Arctic Archipelago using Sentinel-1 synthetic aperture radar and the Multi-angle Imaging SpectroRadiometer R. Segal et al. 10.1017/aog.2020.48
- Big maritime data for the Baltic Sea with a focus on the winter navigation system M. Lensu & F. Goerlandt 10.1016/j.marpol.2019.02.038
- TanDEM-X multiparametric data features in sea ice classification over the Baltic sea M. Marbouti et al. 10.1080/10095020.2020.1845574
- Supplementing Remote Sensing of Ice: Deep Learning-Based Image Segmentation System for Automatic Detection and Localization of Sea-ice Formations From Close-Range Optical Images N. Panchi et al. 10.1109/JSEN.2021.3084556
- Ice ridge density signatures in high-resolution SAR images M. Lensu & M. Similä 10.5194/tc-16-4363-2022
- Estimation of degree of sea ice ridging in the Bay of Bothnia based on geolocated photon heights from ICESat-2 R. Fredensborg Hansen et al. 10.5194/tc-15-2511-2021
- Estimating the Speed of Ice-Going Ships by Integrating SAR Imagery and Ship Data from an Automatic Identification System M. Similä & M. Lensu 10.3390/rs10071132
- Remote Sensing of Ice Phenology and Dynamics of Europe’s Largest Coastal Lagoon (The Curonian Lagoon) R. Idzelytė et al. 10.3390/rs11172059
- Measuring Deformed Sea Ice in Seasonal Ice Zones Using L-Band SAR Images T. Toyota et al. 10.1109/TGRS.2020.3043335
- Interannual sea ice thickness variability in the Bay of Bothnia I. Ronkainen et al. 10.5194/tc-12-3459-2018
- Copernicus Marine Service Ocean State Report, Issue 3 K. von Schuckmann et al. 10.1080/1755876X.2019.1633075
- On Suitability of ALOS-2/PALSAR-2 Dual-Polarized SAR Data for Arctic Sea Ice Parameter Estimation J. Karvonen et al. 10.1109/TGRS.2020.2985696
Latest update: 14 Dec 2024
Short summary
The paper demonstrates the use of SAR imagery in retrieving ice-ridging information for navigation. Based on image segmentation and several texture features extracted from SAR, we perform a classification into four ridging categories from level ice to heavily ridged ice. We compare our results with the manually drawn ice charts over the Baltic Sea. We conclude that the SAR-based product is more detailed than FIS and can be used by ships (non-icebreakers) to aid independent navigation.
The paper demonstrates the use of SAR imagery in retrieving ice-ridging information for...
