Articles | Volume 8, issue 5
https://doi.org/10.5194/tc-8-1639-2014
© Author(s) 2014. 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-8-1639-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
05 Sep 2014
Research article |
| 05 Sep 2014
A sea ice concentration estimation algorithm utilizing radiometer and SAR data
J. Karvonen
Finnish Meteorological Institute (FMI), Helsinki, PB 503, 00101, Finland
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Cited
36 citations as recorded by crossref.
- Improving satellite-based monitoring of the polar regions: Identification of research and capacity gaps C. Gabarró et al. https://doi.org/10.3389/frsen.2023.952091
- Deep Learning for Seasonal Navigability Prediction Along the Northern Sea Route: When Does It Add Value? S. Lee et al. https://doi.org/10.3390/su18104873
- Impact of intermediate ice concentration training data on sea ice concentration estimates from a convolutional neural network Y. Xu & K. Scott https://doi.org/10.1080/01431161.2019.1582113
- The AutoICE Challenge A. Stokholm et al. https://doi.org/10.5194/tc-18-3471-2024
- Sea Ice Concentration Estimation: Using Passive Microwave and SAR Data With a U-Net and Curriculum Learning K. Radhakrishnan et al. https://doi.org/10.1109/JSTARS.2021.3076109
- Baltic Sea Ice Concentration Estimation Using SENTINEL-1 SAR and AMSR2 Microwave Radiometer Data J. Karvonen https://doi.org/10.1109/TGRS.2017.2655567
- Simulating transient ice-ocean Ekman transport in the Regional Arctic System Model and Community Earth System Model A. Roberts et al. https://doi.org/10.3189/2015AoG69A760
- Mapping sea-ice types from Sentinel-1 considering the surface-type dependent effect of incidence angle J. Lohse et al. https://doi.org/10.1017/aog.2020.45
- Skill metrics for evaluation and comparison of sea ice models D. Dukhovskoy et al. https://doi.org/10.1002/2015JC010989
- Atmospheric controls on the Terra Nova Bay polynya occurrence in Antarctica R. Fonseca et al. https://doi.org/10.1007/s00382-023-06845-0
- On Suitability of ALOS-2/PALSAR-2 Dual-Polarized SAR Data for Arctic Sea Ice Parameter Estimation J. Karvonen et al. https://doi.org/10.1109/TGRS.2020.2985696
- Comparing Near Coincident Space Borne C and X Band Fully Polarimetric SAR Data for Arctic Sea Ice Classification R. Ressel & S. Singha https://doi.org/10.3390/rs8030198
- SAR data applications in earth observation: An overview A. Tsokas et al. https://doi.org/10.1016/j.eswa.2022.117342
- SAR and Passive Microwave Fusion Scheme: A Test Case on Sentinel‐1/AMSR‐2 for Sea Ice Classification E. Khachatrian et al. https://doi.org/10.1029/2022GL102083
- MODIS Sea Ice Thickness and Open Water–Sea Ice Charts over the Barents and Kara Seas for Development and Validation of Sea Ice Products from Microwave Sensor Data M. Mäkynen & J. Karvonen https://doi.org/10.3390/rs9121324
- Baltic Sea Ice Concentration Estimation From C-Band Dual-Polarized SAR Imagery by Image Segmentation and Convolutional Neural Networks J. Karvonen https://doi.org/10.1109/TGRS.2021.3097885
- Sea Ice Extraction via Remote Sensing Imagery: Algorithms, Datasets, Applications and Challenges W. Huang et al. https://doi.org/10.3390/rs16050842
- A Conditional Denoising Diffusion Probabilistic Model for Sea Ice Concentration Estimation Y. Chen et al. https://doi.org/10.1109/LGRS.2025.3606975
- A practical algorithm for the retrieval of floe size distribution of Arctic sea ice from high-resolution satellite Synthetic Aperture Radar imagery B. Hwang et al. https://doi.org/10.1525/elementa.154
- Review of Methods to Retrieve Sea-Ice Parameters from Satellite Microwave Radiometer Data E. Zabolotskikh https://doi.org/10.1134/S0001433818060166
- Sea Ice Concentration Estimation During Melt From Dual-Pol SAR Scenes Using Deep Convolutional Neural Networks: A Case Study L. Wang et al. https://doi.org/10.1109/TGRS.2016.2543660
- The 2018 North Greenland polynya observed by a newly introduced merged optical and passive microwave sea-ice concentration dataset V. Ludwig et al. https://doi.org/10.5194/tc-13-2051-2019
- Multi-scale observations of the co-evolution of sea ice thermophysical properties and microwave brightness temperatures during the summer melt period in Hudson Bay M. Harasyn et al. https://doi.org/10.1525/elementa.412
- Classification of Sea Ice Types in Sentinel-1 SAR Data Using Convolutional Neural Networks H. Boulze et al. https://doi.org/10.3390/rs12132165
- A Meta-Analysis of Sea Ice Monitoring Using Spaceborne Polarimetric SAR: Advances in the Last Decade H. Lyu et al. https://doi.org/10.1109/JSTARS.2022.3194324
- Sea and Freshwater Ice Concentration from VIIRS on Suomi NPP and the Future JPSS Satellites Y. Liu et al. https://doi.org/10.3390/rs8060523
- Classification of sea ice types in Sentinel-1 synthetic aperture radar images J. Park et al. https://doi.org/10.5194/tc-14-2629-2020
- Study on improved DPR sea ice concentration retrieval algorithm X. Wang et al. https://doi.org/10.1080/01431161.2026.2687819
- Estimating Sea Ice Concentration From SAR: Training Convolutional Neural Networks With Passive Microwave Data C. Cooke & K. Scott https://doi.org/10.1109/TGRS.2019.2892723
- Satellite SAR Data-based Sea Ice Classification: An Overview N. Zakhvatkina et al. https://doi.org/10.3390/geosciences9040152
- Evaluation of a Neural Network With Uncertainty for Detection of Ice and Water in SAR Imagery N. Asadi et al. https://doi.org/10.1109/TGRS.2020.2992454
- Recognizing the Shape and Size of Tundra Lakes in Synthetic Aperture Radar (SAR) Images Using Deep Learning Segmentation D. Demchev et al. https://doi.org/10.3390/rs15051298
- Satellite passive microwave sea-ice concentration data set intercomparison using Landsat data S. Kern et al. https://doi.org/10.5194/tc-16-349-2022
- Incident Angle Dependence of Sentinel-1 Texture Features for Sea Ice Classification J. Lohse et al. https://doi.org/10.3390/rs13040552
- Prediction of Categorized Sea Ice Concentration From Sentinel-1 SAR Images Based on a Fully Convolutional Network I. de Gelis et al. https://doi.org/10.1109/JSTARS.2021.3074068
- A Sea Ice Concentration Estimation Methodology Utilizing ICESat-2 Photon-Counting Laser Altimeter in the Arctic J. Liu et al. https://doi.org/10.3390/rs14051130
36 citations as recorded by crossref.
- Improving satellite-based monitoring of the polar regions: Identification of research and capacity gaps C. Gabarró et al. https://doi.org/10.3389/frsen.2023.952091
- Deep Learning for Seasonal Navigability Prediction Along the Northern Sea Route: When Does It Add Value? S. Lee et al. https://doi.org/10.3390/su18104873
- Impact of intermediate ice concentration training data on sea ice concentration estimates from a convolutional neural network Y. Xu & K. Scott https://doi.org/10.1080/01431161.2019.1582113
- The AutoICE Challenge A. Stokholm et al. https://doi.org/10.5194/tc-18-3471-2024
- Sea Ice Concentration Estimation: Using Passive Microwave and SAR Data With a U-Net and Curriculum Learning K. Radhakrishnan et al. https://doi.org/10.1109/JSTARS.2021.3076109
- Baltic Sea Ice Concentration Estimation Using SENTINEL-1 SAR and AMSR2 Microwave Radiometer Data J. Karvonen https://doi.org/10.1109/TGRS.2017.2655567
- Simulating transient ice-ocean Ekman transport in the Regional Arctic System Model and Community Earth System Model A. Roberts et al. https://doi.org/10.3189/2015AoG69A760
- Mapping sea-ice types from Sentinel-1 considering the surface-type dependent effect of incidence angle J. Lohse et al. https://doi.org/10.1017/aog.2020.45
- Skill metrics for evaluation and comparison of sea ice models D. Dukhovskoy et al. https://doi.org/10.1002/2015JC010989
- Atmospheric controls on the Terra Nova Bay polynya occurrence in Antarctica R. Fonseca et al. https://doi.org/10.1007/s00382-023-06845-0
- On Suitability of ALOS-2/PALSAR-2 Dual-Polarized SAR Data for Arctic Sea Ice Parameter Estimation J. Karvonen et al. https://doi.org/10.1109/TGRS.2020.2985696
- Comparing Near Coincident Space Borne C and X Band Fully Polarimetric SAR Data for Arctic Sea Ice Classification R. Ressel & S. Singha https://doi.org/10.3390/rs8030198
- SAR data applications in earth observation: An overview A. Tsokas et al. https://doi.org/10.1016/j.eswa.2022.117342
- SAR and Passive Microwave Fusion Scheme: A Test Case on Sentinel‐1/AMSR‐2 for Sea Ice Classification E. Khachatrian et al. https://doi.org/10.1029/2022GL102083
- MODIS Sea Ice Thickness and Open Water–Sea Ice Charts over the Barents and Kara Seas for Development and Validation of Sea Ice Products from Microwave Sensor Data M. Mäkynen & J. Karvonen https://doi.org/10.3390/rs9121324
- Baltic Sea Ice Concentration Estimation From C-Band Dual-Polarized SAR Imagery by Image Segmentation and Convolutional Neural Networks J. Karvonen https://doi.org/10.1109/TGRS.2021.3097885
- Sea Ice Extraction via Remote Sensing Imagery: Algorithms, Datasets, Applications and Challenges W. Huang et al. https://doi.org/10.3390/rs16050842
- A Conditional Denoising Diffusion Probabilistic Model for Sea Ice Concentration Estimation Y. Chen et al. https://doi.org/10.1109/LGRS.2025.3606975
- A practical algorithm for the retrieval of floe size distribution of Arctic sea ice from high-resolution satellite Synthetic Aperture Radar imagery B. Hwang et al. https://doi.org/10.1525/elementa.154
- Review of Methods to Retrieve Sea-Ice Parameters from Satellite Microwave Radiometer Data E. Zabolotskikh https://doi.org/10.1134/S0001433818060166
- Sea Ice Concentration Estimation During Melt From Dual-Pol SAR Scenes Using Deep Convolutional Neural Networks: A Case Study L. Wang et al. https://doi.org/10.1109/TGRS.2016.2543660
- The 2018 North Greenland polynya observed by a newly introduced merged optical and passive microwave sea-ice concentration dataset V. Ludwig et al. https://doi.org/10.5194/tc-13-2051-2019
- Multi-scale observations of the co-evolution of sea ice thermophysical properties and microwave brightness temperatures during the summer melt period in Hudson Bay M. Harasyn et al. https://doi.org/10.1525/elementa.412
- Classification of Sea Ice Types in Sentinel-1 SAR Data Using Convolutional Neural Networks H. Boulze et al. https://doi.org/10.3390/rs12132165
- A Meta-Analysis of Sea Ice Monitoring Using Spaceborne Polarimetric SAR: Advances in the Last Decade H. Lyu et al. https://doi.org/10.1109/JSTARS.2022.3194324
- Sea and Freshwater Ice Concentration from VIIRS on Suomi NPP and the Future JPSS Satellites Y. Liu et al. https://doi.org/10.3390/rs8060523
- Classification of sea ice types in Sentinel-1 synthetic aperture radar images J. Park et al. https://doi.org/10.5194/tc-14-2629-2020
- Study on improved DPR sea ice concentration retrieval algorithm X. Wang et al. https://doi.org/10.1080/01431161.2026.2687819
- Estimating Sea Ice Concentration From SAR: Training Convolutional Neural Networks With Passive Microwave Data C. Cooke & K. Scott https://doi.org/10.1109/TGRS.2019.2892723
- Satellite SAR Data-based Sea Ice Classification: An Overview N. Zakhvatkina et al. https://doi.org/10.3390/geosciences9040152
- Evaluation of a Neural Network With Uncertainty for Detection of Ice and Water in SAR Imagery N. Asadi et al. https://doi.org/10.1109/TGRS.2020.2992454
- Recognizing the Shape and Size of Tundra Lakes in Synthetic Aperture Radar (SAR) Images Using Deep Learning Segmentation D. Demchev et al. https://doi.org/10.3390/rs15051298
- Satellite passive microwave sea-ice concentration data set intercomparison using Landsat data S. Kern et al. https://doi.org/10.5194/tc-16-349-2022
- Incident Angle Dependence of Sentinel-1 Texture Features for Sea Ice Classification J. Lohse et al. https://doi.org/10.3390/rs13040552
- Prediction of Categorized Sea Ice Concentration From Sentinel-1 SAR Images Based on a Fully Convolutional Network I. de Gelis et al. https://doi.org/10.1109/JSTARS.2021.3074068
- A Sea Ice Concentration Estimation Methodology Utilizing ICESat-2 Photon-Counting Laser Altimeter in the Arctic J. Liu et al. https://doi.org/10.3390/rs14051130
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