22.3.4.1 Icebergs, Ice Floe, Sea Ice, Drifting Ice, Ice Motion

Chapter Contents (Back)
Iceberg Detection. Sea Ice Detection. Ice Detection.
See also Ice Shelf, Analysis.

Haarpaintner, J.,
Arctic-Wide Operational Sea Ice Drift From Enhanced-Resolution QuikScat/SeaWinds Scatterometry and Its Validation,
GeoRS(44), No. 1, January 2006, pp. 102-107.
IEEE DOI 0601
BibRef

Lu, P., Li, Z.,
A Method of Obtaining Ice Concentration and Floe Size From Shipboard Oblique Sea Ice Images,
GeoRS(48), No. 7, July 2010, pp. 2771-2780.
IEEE DOI 1007
BibRef

Thomas, M.[Mani], Kambhamettu, C.[Chandra], Geiger, C.[Cathleen],
Motion Tracking of Discontinuous Sea Ice,
GeoRS(49), No. 12, December 2011, pp. 5064-5079.
IEEE DOI 1201
BibRef
Earlier: A1, A2, A3:
Vector field resampling using local streamline approximation,
ICPR08(1-4).
IEEE DOI 0812
BibRef
Earlier: A1, A3, A2:
Vector field characterization in ERS-1 imagery of sea ice,
WACV07(23-23).
IEEE DOI 0702
BibRef
Earlier: A1, A3, A2:
Discontinuous Non-Rigid Motion Analysis of Sea Ice using C-Band Synthetic Aperture Radar Satellite Imagery,
Non-Rigid04(24).
HTML Version. 0502
BibRef

Girard-Ardhuin, F., Ezraty, R.,
Enhanced Arctic Sea Ice Drift Estimation Merging Radiometer and Scatterometer Data,
GeoRS(50), No. 7, July 2012, pp. 2639-2648.
IEEE DOI 1208
BibRef

Dierking, W., Wesche, C.,
C-Band Radar Polarimetry: Useful for Detection of Icebergs in Sea Ice?,
GeoRS(52), No. 1, January 2014, pp. 25-37.
IEEE DOI 1402
oceanographic techniques BibRef

Berg, A., Eriksson, L.E.B.,
Investigation of a Hybrid Algorithm for Sea Ice Drift Measurements Using Synthetic Aperture Radar Images,
GeoRS(52), No. 8, August 2014, pp. 5023-5033.
IEEE DOI 1403
Correlation BibRef

Br÷han, D.[David], Kaleschke, L.[Lars],
A Nine-Year Climatology of Arctic Sea Ice Lead Orientation and Frequency from AMSR-E,
RS(6), No. 2, 2014, pp. 1451-1475.
DOI Link 1403
BibRef

Komarov, A.S., Barber, D.G.,
Sea Ice Motion Tracking From Sequential Dual-Polarization RADARSAT-2 Images,
GeoRS(52), No. 1, January 2014, pp. 121-136.
IEEE DOI 1402
hydrological techniques BibRef

Komarov, A.S., Buehner, M.,
Automated Detection of Ice and Open Water From Dual-Polarization RADARSAT-2 Images for Data Assimilation,
GeoRS(55), No. 10, October 2017, pp. 5755-5769.
IEEE DOI 1710
data assimilation, geophysical image processing, regression analysis, remote sensing by radar, sea ice, snow, synthetic aperture radar, HH backscatter signal, HV backscatter signal, Interactive Multisensor Snow and Ice Mapping System, BibRef

Komarov, A.S., Buehner, M.,
Improved Retrieval of Ice and Open Water From Sequential RADARSAT-2 Images,
GeoRS(57), No. 6, June 2019, pp. 3694-3702.
IEEE DOI 1906
Ice, Synthetic aperture radar, Wind speed, Probability, Image analysis, Data assimilation, Arctic, Ice motion, synthetic aperture radar (SAR) BibRef

Zhang, Q.[Qin], Skjetne, R.,
Image Processing for Identification of Sea-Ice Floes and the Floe Size Distributions,
GeoRS(53), No. 5, May 2015, pp. 2913-2924.
IEEE DOI 1502
geophysical image processing BibRef

Marino, A., Dierking, W., Wesche, C.,
A Depolarization Ratio Anomaly Detector to Identify Icebergs in Sea Ice Using Dual-Polarization SAR Images,
GeoRS(54), No. 9, September 2016, pp. 5602-5615.
IEEE DOI 1609
oceanographic techniques BibRef

Ye, Y.F.[Yu-Fang], Shokr, M.[Mohammed], Heygster, G.[Georg], Spreen, G.[Gunnar],
Improving Multiyear Sea Ice Concentration Estimates with Sea Ice Drift,
RS(8), No. 5, 2016, pp. 397.
DOI Link 1606
BibRef

Ludwig, V.[Valentin], Spreen, G.[Gunnar], Pedersen, L.T.[Leif Toudal],
Evaluation of a New Merged Sea-Ice Concentration Dataset at 1 km Resolution from Thermal Infrared and Passive Microwave Satellite Data in the Arctic,
RS(12), No. 19, 2020, pp. xx-yy.
DOI Link 2010
BibRef

Ye, Y.F.[Yu-Fang], Heygster, G.[Georg], Shokr, M.[Mohammed],
Improving Multiyear Ice Concentration Estimates With Reanalysis Air Temperatures,
GeoRS(54), No. 5, May 2016, pp. 2602-2614.
IEEE DOI 1604
atmospheric techniques BibRef

Zhang, T.Y.[Tian-Yu], Yang, Y.[Ying], Shokr, M.[Mohammed], Mi, C.L.[Chun-Lei], Li, X.M.[Xiao-Ming], Cheng, X.[Xiao], Hui, F.M.[Feng-Ming],
Deep Learning Based Sea Ice Classification with Gaofen-3 Fully Polarimetric SAR Data,
RS(13), No. 8, 2021, pp. xx-yy.
DOI Link 2104
BibRef

Hui, F.M.[Feng-Ming], Li, X.Q.[Xin-Qing], Zhao, T.C.[Tian-Cheng], Shokr, M.[Mohammed], Heil, P.[Petra], Zhao, J.C.[Jie-Chen], Liu, Y.[Yan], Liang, S.L.[Shun-Lin], Cheng, X.[Xiao],
Semi-Automatic Mapping of Tidal Cracks in the Fast Ice Region near Zhongshan Station in East Antarctica Using Landsat-8 OLI Imagery,
RS(8), No. 3, 2016, pp. 242.
DOI Link 1604
BibRef

Hui, F.M.[Feng-Ming], Zhao, T.C.[Tian-Cheng], Li, X.Q.[Xin-Qing], Shokr, M.[Mohammed], Heil, P.[Petra], Zhao, J.C.[Jie-Chen], Zhang, L.[Lin], Cheng, X.[Xiao],
Satellite-Based Sea Ice Navigation for Prydz Bay, East Antarctica,
RS(9), No. 6, 2017, pp. xx-yy.
DOI Link 1706
BibRef

Heiselberg, P.[Peder], Heiselberg, H.[Henning],
Ship-Iceberg Discrimination in Sentinel-2 Multispectral Imagery by Supervised Classification,
RS(9), No. 11, 2017, pp. xx-yy.
DOI Link 1712
BibRef

Korosov, A.A.[Anton Andreevich], Rampal, P.[Pierre],
A Combination of Feature Tracking and Pattern Matching with Optimal Parametrization for Sea Ice Drift Retrieval from SAR Data,
RS(9), No. 3, 2017, pp. xx-yy.
DOI Link 1704
BibRef

Griebel, J.[Jakob], Dierking, W.[Wolfgang],
A Method to Improve High-Resolution Sea Ice Drift Retrievals in the Presence of Deformation Zones,
RS(9), No. 7, 2017, pp. xx-yy.
DOI Link 1708
BibRef

Demchev, D., Volkov, V., Kazakov, E., Alcantarilla, P.F., Sandven, S., Khmeleva, V.,
Sea Ice Drift Tracking From Sequential SAR Images Using Accelerated-KAZE Features,
GeoRS(55), No. 9, September 2017, pp. 5174-5184.
IEEE DOI 1709
feature extraction, geophysical image processing, image matching, oceanographic techniques, radar imaging, remote sensing by radar, synthetic aperture radar, feature-tracking algorithm, nonlinear multiscale image representation, sequential satellite synthetic aperture radar image, BibRef

Xian, Y., Petrou, Z.I., Tian, Y., Meier, W.N.,
Super-Resolved Fine-Scale Sea Ice Motion Tracking,
GeoRS(55), No. 10, October 2017, pp. 5427-5439.
IEEE DOI 1710
passive microwave data, single image super-resolution algorithm, BibRef

Hyun, C.U.[Chang-Uk], Kim, H.C.[Hyun-Cheol],
A Feasibility Study of Sea Ice Motion and Deformation Measurements Using Multi-Sensor High-Resolution Optical Satellite Images,
RS(9), No. 9, 2017, pp. xx-yy.
DOI Link 1711
BibRef

Petrou, Z.I., Tian, Y.,
High-Resolution Sea Ice Motion Estimation With Optical Flow Using Satellite Spectroradiometer Data,
GeoRS(55), No. 3, March 2017, pp. 1339-1350.
IEEE DOI 1703
Integrated optics BibRef

Petrou, Z.I., Tian, Y.,
Prediction of Sea Ice Motion With Convolutional Long Short-Term Memory Networks,
GeoRS(57), No. 9, September 2019, pp. 6865-6876.
IEEE DOI 1909
Sea ice, Predictive models, Arctic, Data models, Atmospheric modeling, Numerical models, Microwave radiometry, recurrent neural networks (RNNs) BibRef

Akbari, V., Brekke, C.,
Iceberg Detection in Open and Ice-Infested Waters Using C-Band Polarimetric Synthetic Aperture Radar,
GeoRS(56), No. 1, January 2018, pp. 407-421.
IEEE DOI 1801
geophysical image processing, radar polarimetry, remote sensing by radar, sea ice, synthetic aperture radar, synthetic aperture radar (SAR) BibRef

Crawford, A.J.[Anna J.], Mueller, D.[Derek], Joyal, G.[Gabriel],
Surveying Drifting Icebergs and Ice Islands: Deterioration Detection and Mass Estimation with Aerial Photogrammetry and Laser Scanning,
RS(10), No. 4, 2018, pp. xx-yy.
DOI Link 1805
BibRef

Kramer, T., Johnsen, H., Brekke, C., Engen, G.,
Comparing SAR-Based Short Time-Lag Cross Correlation and Doppler-Derived Sea Ice Drift Velocities,
GeoRS(56), No. 4, April 2018, pp. 1898-1908.
IEEE DOI 1804
Antennas, Doppler effect, Global Positioning System, Satellites, Sea ice, Synthetic aperture radar, Doppler measurement, synthetic aperture radar BibRef

Petrou, Z.I.[Zisis I.], Xian, Y.[Yang], Tian, Y.L.[Ying-Li],
Towards breaking the spatial resolution barriers: An optical flow and super-resolution approach for sea ice motion estimation,
PandRS(138), 2018, pp. 164-175.
Elsevier DOI 1804
Arctic sea ice, Drift estimation, Maximum cross-correlation, Motion tracking, Optical flow, Super-resolution BibRef

Griebel, J.[Jakob], Dierking, W.[Wolfgang],
Impact of Sea Ice Drift Retrieval Errors, Discretization and Grid Type on Calculations of Ice Deformation,
RS(10), No. 3, 2018, pp. xx-yy.
DOI Link 1804
BibRef

Kjerstad, ě.K., L°set, S., Skjetne, R., Skarb°, R.A.,
An Ice-Drift Estimation Algorithm Using Radar and Ship Motion Measurements,
GeoRS(56), No. 6, June 2018, pp. 3007-3019.
IEEE DOI 1806
Ice, Marine vehicles, Radar imaging, Radar tracking, Sea measurements, Spaceborne radar, Arctic, Kalman filtering, ice, remote Sensing BibRef

Soldal, I.H.[Ingri Halland], Dierking, W.[Wolfgang], Korosov, A.[Anton], Marino, A.[Armando],
Automatic Detection of Small Icebergs in Fast Ice Using Satellite Wide-Swath SAR Images,
RS(11), No. 7, 2019, pp. xx-yy.
DOI Link 1904
BibRef

Barbat, M.M.[Mauro M.], Wesche, C.[Christine], Werhli, A.V.[Adriano V.], Mata, M.M.[Mauricio M.],
An adaptive machine learning approach to improve automatic iceberg detection from SAR images,
PandRS(156), 2019, pp. 247-259.
Elsevier DOI 1909
Icebergs, Detection, SAR, Southern Ocean, Machine learning BibRef

Chen, S.Y.[Shi-Yi], Shokr, M.[Mohammed], Li, X.Q.[Xin-Qing], Ye, Y.F.[Yu-Fang], Zhang, Z.L.[Zhi-Lun], Hui, F.M.[Feng-Ming], Cheng, X.[Xiao],
MYI Floes Identification Based on the Texture and Shape Feature from Dual-Polarized Sentinel-1 Imagery,
RS(12), No. 19, 2020, pp. xx-yy.
DOI Link 2010
BibRef

Farooq, U.[Usama], Rack, W.[Wolfgang], McDonald, A.[Adrian], Howell, S.[Stephen],
Long-Term Analysis of Sea Ice Drift in the Western Ross Sea, Antarctica, at High and Low Spatial Resolution,
RS(12), No. 9, 2020, pp. xx-yy.
DOI Link 2005
BibRef

Kim, S.H.[Seung Hee], Kim, H.C.[Hyun-Cheol], Hyun, C.U.[Chang-Uk], Lee, S.J.[Sung-Jae], Ha, J.S.[Jung-Seok], Kim, J.H.[Joo-Hong], Kwon, Y.J.[Young-Joo], Park, J.W.[Jeong-Won], Han, H.S.[Hyang-Sun], Jeong, S.Y.[Seong-Yeob], Kim, D.J.[Duk-Jin],
Evolution of Backscattering Coefficients of Drifting Multi-Year Sea Ice during End of Melting and Onset of Freeze-up in the Western Beaufort Sea,
RS(12), No. 9, 2020, pp. xx-yy.
DOI Link 2005
BibRef

Komarov, A.S., Caya, A., Buehner, M., Pogson, L.,
Assimilation of SAR Ice and Open Water Retrievals in Environment and Climate Change Canada Regional Ice-Ocean Prediction System,
GeoRS(58), No. 6, June 2020, pp. 4290-4303.
IEEE DOI 2005
Data assimilation, ice concentration analysis, RADARSAT-2, Regional Ice-Ocean Prediction System (RIOPS), synthetic aperture radar (SAR) BibRef

Podgˇrski, J.[Julian], Petlicki, M.[Michal],
Detailed Lacustrine Calving Iceberg Inventory from Very High Resolution Optical Imagery and Object-Based Image Analysis,
RS(12), No. 11, 2020, pp. xx-yy.
DOI Link 2006
BibRef

Bailey, J.[Johnson], Marino, A.[Armando],
Quad-Polarimetric Multi-Scale Analysis of Icebergs in ALOS-2 SAR Data: A Comparison between Icebergs in West and East Greenland,
RS(12), No. 11, 2020, pp. xx-yy.
DOI Link 2006
BibRef

Heiselberg, H.[Henning],
Ship-Iceberg Classification in SAR and Multispectral Satellite Images with Neural Networks,
RS(12), No. 15, 2020, pp. xx-yy.
DOI Link 2008
BibRef

Wang, M.F.[Ming-Feng], K÷nig, M.[Marcel], Oppelt, N.[Natascha],
Partial Shape Recognition for Sea Ice Motion Retrieval in the Marginal Ice Zone from Sentinel-1 and Sentinel-2,
RS(13), No. 21, 2021, pp. xx-yy.
DOI Link 2112
BibRef

Barbat, M.M.[Mauro M.], Rackow, T.[Thomas], Wesche, C.[Christine], Hellmer, H.H.[Hartmut H.], Mata, M.M.[Mauricio M.],
Automated iceberg tracking with a machine learning approach applied to SAR imagery: A Weddell sea case study,
PandRS(172), 2021, pp. 189 - 206.
Elsevier DOI 2101
Icebergs, SAR, Tracking, Southern Ocean, Machine learning, Antarctic BibRef

Nagi, A.S.[Anmol Sharan], Kumar, D.[Devinder], Sola, D.[Daniel], Scott, K.A.[K. Andrea],
RUF: Effective Sea Ice Floe Segmentation Using End-to-End RES-UNET-CRF with Dual Loss,
RS(13), No. 13, 2021, pp. xx-yy.
DOI Link 2107
BibRef

Lopez-Lopez, L.[Ludwin], Parmiggiani, F.[Flavio], Moctezuma-Flores, M.[Miguel], Guerrieri, L.[Lorenzo],
On the Detection and Long-Term Path Visualisation of A-68 Iceberg,
RS(13), No. 3, 2021, pp. xx-yy.
DOI Link 2102
BibRef

Guan, Z.F.[Zhen-Fu], Cheng, X.[Xiao], Liu, Y.[Yan], Li, T.[Teng], Zhang, B.G.[Bao-Gang], Yu, Z.T.[Zhi-Tong],
Effectively Extracting Iceberg Freeboard Using Bi-Temporal Landsat-8 Panchromatic Image Shadows,
RS(13), No. 3, 2021, pp. xx-yy.
DOI Link 2102
BibRef

Bailey, J.[Johnson], Marino, A.[Armando], Akbari, V.[Vahid],
Comparison of Target Detectors to Identify Icebergs in Quad-Polarimetric L-Band Synthetic Aperture Radar Data,
RS(13), No. 9, 2021, pp. xx-yy.
DOI Link 2105
BibRef

Kim, J.I.[Jae-In], Hyun, C.U.[Chang-Uk], Han, H.S.[Hyang-Sun], Kim, H.C.[Hyun-Cheol],
Digital surface model generation for drifting Arctic sea ice with low-textured surfaces based on drone images,
PandRS(172), 2021, pp. 147-159.
Elsevier DOI 2101
Sea ice, Digital surface model, Unmanned aerial vehicle, Image matching, Georeferencing, Low-textured surface BibRef

Park, J.W.[Jeong-Won], Kim, H.C.[Hyun-Cheol], Korosov, A.[Anton], Demchev, D.[Denis], Zecchetto, S.[Stefano], Kim, S.H.[Seung Hee], Kwon, Y.J.[Young-Joo], Han, H.S.[Hyang-Sun], Hyun, C.U.[Chang-Uk],
Feasibility Study on Estimation of Sea Ice Drift from KOMPSAT-5 and COSMO-SkyMed SAR Images,
RS(13), No. 20, 2021, pp. xx-yy.
DOI Link 2110
BibRef

Liu, T.T.[Ting-Ting], Wang, Z.[Zihan], Shokr, M.[Mohammed], Lei, R.[Ruibo], Zhang, Z.R.[Zhao-Ru],
An Assessment of Sea Ice Motion Products in the Robeson Channel Using Daily Sentinel-1 Images,
RS(14), No. 2, 2022, pp. xx-yy.
DOI Link 2201
BibRef

Wang, X.[Xue], Chen, R.T.[Run-Tong], Li, C.[Chao], Chen, Z.Q.[Zhuo-Qi], Hui, F.M.[Feng-Ming], Cheng, X.[Xiao],
An Intercomparison of Satellite Derived Arctic Sea Ice Motion Products,
RS(14), No. 5, 2022, pp. xx-yy.
DOI Link 2203
BibRef

Fang, H.L.[Hai-Lan], Zhang, X.[Xi], Shi, L.J.[Li-Jian], Bao, M.[Meng], Liu, G.[Genwang], Cao, C.[Chenghui], Zhang, J.[Jie],
Evaluation of Arctic Sea Ice Drift Products Based on FY-3, HY-2, AMSR2, and SSMIS Radiometer Data,
RS(14), No. 20, 2022, pp. xx-yy.
DOI Link 2211
BibRef

Qiu, H.C.[Hua-Chang], Gong, Z.N.[Zhao-Ning], Mou, K.[Kuinan], Hu, J.F.[Jian-Fang], Ke, Y.H.[Ying-Hai], Zhou, D.[Demin],
Automatic and Accurate Extraction of Sea Ice in the Turbid Waters of the Yellow River Estuary Based on Image Spectral and Spatial Information,
RS(14), No. 4, 2022, pp. xx-yy.
DOI Link 2202
BibRef

Zhou, L.[Li], Cai, J.[Jinyan], Ding, S.F.[Shi-Feng],
The Identification of Ice Floes and Calculation of Sea Ice Concentration Based on a Deep Learning Method,
RS(15), No. 10, 2023, pp. xx-yy.
DOI Link 2306
BibRef

Zhong, D.Y.[Deng-Yan], Liu, N.[Na], Yang, L.[Lei], Lin, L.[Lina], Chen, H.X.[Hong-Xia],
Self-Attention Convolutional Long Short-Term Memory for Short-Term Arctic Sea Ice Motion Prediction Using Advanced Microwave Scanning Radiometer Earth Observing System 36.5 GHz Data,
RS(15), No. 23, 2023, pp. 5437.
DOI Link 2312
BibRef


Zhou, Y., Du, J., Zhang, Y., Gong, C., Hu, Y.,
Parameter Estimation and Motion Tracking of Pack Ice From Fy-3/mersi Images,
ISPRS20(B3:925-932).
DOI Link 2012
Wg Iii/10 - Agriculture and Natural Ecosystems Modelling and Monitoring BibRef

Chapter on Remote Sensing General Issue, Land Use, Land Cover continues in
Ice Shelf, Analysis .


Last update:Jan 30, 2024 at 20:33:16