Articles | Volume 10, issue 1
https://doi.org/10.5194/tc-10-121-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/tc-10-121-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
18 Jan 2016
Research article |
| 18 Jan 2016
Utilisation of CryoSat-2 SAR altimeter in operational ice charting
E. Rinne
CORRESPONDING AUTHOR
Finnish Meteorological Institute, Marine Research, P.O. Box 503, 00101 Helsinki, Finland
M. Similä
Finnish Meteorological Institute, Marine Research, P.O. Box 503, 00101 Helsinki, Finland
Viewed
Total article views: 3,766 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 03 Aug 2015)
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 1,706 | 1,862 | 198 | 3,766 | 199 | 194 |
- HTML: 1,706
- PDF: 1,862
- XML: 198
- Total: 3,766
- BibTeX: 199
- EndNote: 194
Total article views: 3,044 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 18 Jan 2016)
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 1,406 | 1,478 | 160 | 3,044 | 180 | 175 |
- HTML: 1,406
- PDF: 1,478
- XML: 160
- Total: 3,044
- BibTeX: 180
- EndNote: 175
Total article views: 722 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 03 Aug 2015)
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 300 | 384 | 38 | 722 | 19 | 19 |
- HTML: 300
- PDF: 384
- XML: 38
- Total: 722
- BibTeX: 19
- EndNote: 19
Cited
20 citations as recorded by crossref.
- Lead detection using Cryosat-2 delay-doppler processing and Sentinel-1 SAR images M. Passaro et al. 10.1016/j.asr.2017.07.011
- 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
- Mapping the thickness of sea ice in the Arctic as an example of using data from a ship-based television complex for operational hydrometeorological support of maritime activities E. Afanasyeva et al. 10.30758/0555-2648-2022-68-2-96-117
- S3MPC: Improvement on Inland Water Tracking and Water Level Monitoring from the OLTC Onboard Sentinel-3 Altimeters N. Taburet et al. 10.3390/rs12183055
- Sensitivity of Radar Altimeter Waveform to Changes in Sea Ice Type at Resolution of Synthetic Aperture Radar W. Aldenhoff et al. 10.3390/rs11222602
- Sea Ice Classification Using Cryosat-2 Altimeter Data by Optimal Classifier–Feature Assembly X. Shen et al. 10.1109/LGRS.2017.2743339
- Assessment of Arctic Sea Ice Classification Ability of Chinese HY-2B Dual-Band Radar Altimeter During Winter to Early Spring Conditions X. Zhang et al. 10.1109/JSTARS.2021.3114228
- Estimating Arctic sea ice thickness and volume using CryoSat-2 radar altimeter data R. Tilling et al. 10.1016/j.asr.2017.10.051
- Comparative Evaluation of Sea Ice Lead Detection Based on SAR Imagery and Altimeter Data N. Longepe et al. 10.1109/TGRS.2018.2889519
- Discrimination of different sea ice types from CryoSat-2 satellite data using an Object-based Random Forest (ORF) S. Shu et al. 10.1080/01490419.2019.1671560
- 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
- Classification of Sea Ice Types in the Arctic by Radar Echoes from SARAL/AltiKa R. Fredensborg Hansen et al. 10.3390/rs13163183
- Arctic Sea Ice Classification Based on CFOSAT SWIM Data at Multiple Small Incidence Angles M. Liu et al. 10.3390/rs14010091
- 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
- Sea ice recognition for CFOSAT SWIM at multiple small incidence angles in the Arctic M. Liu et al. 10.3389/fmars.2022.986228
- Near-real-time Arctic sea ice thickness and volume from CryoSat-2 R. Tilling et al. 10.5194/tc-10-2003-2016
- A Study of the Technology Used to Distinguish Sea Ice and Seawater on the Haiyang-2A/B (HY-2A/B) Altimeter Data C. Jiang et al. 10.3390/rs11121490
- Machine learning based classification of lake ice and open water from Sentinel-3 SAR altimetry waveforms J. Mugunthan et al. 10.1016/j.rse.2023.113891
- Estimation of degree of sea ice ridging based on dual-polarized C-band SAR data A. Gegiuc et al. 10.5194/tc-12-343-2018
- A New Retracking Algorithm for Retrieving Sea Ice Freeboard from CryoSat-2 Radar Altimeter Data during Winter–Spring Transition X. Shen et al. 10.3390/rs11101194
20 citations as recorded by crossref.
- Lead detection using Cryosat-2 delay-doppler processing and Sentinel-1 SAR images M. Passaro et al. 10.1016/j.asr.2017.07.011
- 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
- Mapping the thickness of sea ice in the Arctic as an example of using data from a ship-based television complex for operational hydrometeorological support of maritime activities E. Afanasyeva et al. 10.30758/0555-2648-2022-68-2-96-117
- S3MPC: Improvement on Inland Water Tracking and Water Level Monitoring from the OLTC Onboard Sentinel-3 Altimeters N. Taburet et al. 10.3390/rs12183055
- Sensitivity of Radar Altimeter Waveform to Changes in Sea Ice Type at Resolution of Synthetic Aperture Radar W. Aldenhoff et al. 10.3390/rs11222602
- Sea Ice Classification Using Cryosat-2 Altimeter Data by Optimal Classifier–Feature Assembly X. Shen et al. 10.1109/LGRS.2017.2743339
- Assessment of Arctic Sea Ice Classification Ability of Chinese HY-2B Dual-Band Radar Altimeter During Winter to Early Spring Conditions X. Zhang et al. 10.1109/JSTARS.2021.3114228
- Estimating Arctic sea ice thickness and volume using CryoSat-2 radar altimeter data R. Tilling et al. 10.1016/j.asr.2017.10.051
- Comparative Evaluation of Sea Ice Lead Detection Based on SAR Imagery and Altimeter Data N. Longepe et al. 10.1109/TGRS.2018.2889519
- Discrimination of different sea ice types from CryoSat-2 satellite data using an Object-based Random Forest (ORF) S. Shu et al. 10.1080/01490419.2019.1671560
- 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
- Classification of Sea Ice Types in the Arctic by Radar Echoes from SARAL/AltiKa R. Fredensborg Hansen et al. 10.3390/rs13163183
- Arctic Sea Ice Classification Based on CFOSAT SWIM Data at Multiple Small Incidence Angles M. Liu et al. 10.3390/rs14010091
- 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
- Sea ice recognition for CFOSAT SWIM at multiple small incidence angles in the Arctic M. Liu et al. 10.3389/fmars.2022.986228
- Near-real-time Arctic sea ice thickness and volume from CryoSat-2 R. Tilling et al. 10.5194/tc-10-2003-2016
- A Study of the Technology Used to Distinguish Sea Ice and Seawater on the Haiyang-2A/B (HY-2A/B) Altimeter Data C. Jiang et al. 10.3390/rs11121490
- Machine learning based classification of lake ice and open water from Sentinel-3 SAR altimetry waveforms J. Mugunthan et al. 10.1016/j.rse.2023.113891
- Estimation of degree of sea ice ridging based on dual-polarized C-band SAR data A. Gegiuc et al. 10.5194/tc-12-343-2018
- A New Retracking Algorithm for Retrieving Sea Ice Freeboard from CryoSat-2 Radar Altimeter Data during Winter–Spring Transition X. Shen et al. 10.3390/rs11101194
Saved (final revised paper)
Discussed (final revised paper)
Latest update: 20 Apr 2024
Short summary
This paper demonstrates the use of the CryoSat-2 SAR altimeter in operational ice charting. We take CryoSat-2 data and compare them to ice charts over the sea-ice-covered regions in the Barents and Kara seas. We also present an automatic classification method for CryoSat-2 measurements that could be used to support navigation. We conclude that SAR altimeter measurements can be valuable to operational ice charting if other data sources are unavailable.
This paper demonstrates the use of the CryoSat-2 SAR altimeter in operational ice charting. We...
