Detection and classification of sea ice from spaceborne multi-frequency synthetic aperture radar imagery and radar altimetry
Doctoral thesis, 2020

The sea ice cover in the Arctic is undergoing drastic changes. Since the start of satellite observations by microwave remote sensing in the late 1970's, the maximum summer sea ice extent has been decreasing and thereby causing a generally thinner and younger sea ice cover. Spaceborne radar remote sensing facilitates the determination of sea ice properties in a changing climate with the high spatio-temporal resolution necessary for a better understanding of the ongoing processes as well as safe navigation and operation in ice infested waters.

The work presented in this thesis focuses on the one hand on synergies of multi-frequency spaceborne synthetic aperture radar (SAR) imagery for sea ice classification. On the other hand, the fusion of radar altimetry observations with near-coincidental SAR imagery is investigated for its potential to improve 3-dimensional sea ice information retrieval.
Investigations of ice/water classification of C- and L-band SAR imagery with a feed-forward neural network demonstrated the capabilities of both frequencies to outline the sea ice edge with good accuracy. Classification results also indicate that a combination of both frequencies can improve the identification of thin ice areas within the ice pack compared to C-band alone. Incidence angle normalisation has proven to increase class separability of different ice types. Analysis of incidence angle dependence between 19-47° at co- and cross-polarisation from Sentinel-1 C-band images closed a gap in existing slope estimates at cross-polarisation for multiyear sea ice and confirms values obtained in other regions of the Arctic or with different sensors. Furthermore, it demonstrated that insufficient noise correction of the first subswath at cross-polarisation increased the slope estimates by 0.01 dB/1° for multiyear ice. The incidence angle dependence of the Sentinel-1 noise floor affected smoother first-year sea ice and made the first subswath unusable for reliable incidence angle estimates in those cases.
Radar altimetry can complete the 2-dimensional sea ice picture with thickness information. By comparison of SAR imagery with altimeter waveforms from CryoSat-2, it is demonstrated that waveforms respond well to changes of the sea ice surface in the order of a few hundred metres to a few kilometres. Freeboard estimates do however not always correspond to these changes especially when mixtures of different ice types are found within the footprint. Homogeneous ice floes of about 10 km are necessary for robust averaged freeboard estimates.

The results demonstrate that multi-frequency and multi-sensor approaches open up for future improvements of sea ice retrievals from radar remote sensing techniques, but access to in-situ data for training and validation will be critical.

sea ice

sea ice classification

Fram Strait

sea ice concentration

Beaufort Sea

SAR imaging

radar altimetry

Opponent: Dr. Marko Mäkynen, Finnish Meteorological Institute, Helsinki, Finland


Wiebke Aldenhoff

Chalmers, Space, Earth and Environment, Microwave and Optical Remote Sensing

Sea ice concentration estimation from Sentinel-1 Synthetic Aperture Radar images over the Fram Strait

36th IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2016; Beijing; China; 10-15 July 2016,; Vol. 2016-November(2016)p. Art no 7731001, Pages 7675-7677

Paper in proceedings

Comparison of ice/water classification in Fram Strait from C- A nd L-band SAR imagery

Annals of Glaciology,; Vol. 59(2018)p. 112-123

Journal article

Aldenhoff, W., Eriksson, L. E. B., Ye, Y. and Heuzé, C. First-year and Multiyear Sea Ice Incidence Angle Normalization of Dual-polarized Sentinel-1 SAR Images in the Beaufort Sea

Comparison of Sentinel-1 Sar and Sentinel-3 Altimetry Data for Sea Ice Type Discrimination

International Geoscience and Remote Sensing Symposium (IGARSS),; (2020)p. 4238-4240

Paper in proceedings

Sea ice is a crucial component of the Arctic as well as the global climate system that regulates the exchange of heat and momentum between the ocean and the atmosphere. Recent changes of the sea ice cover towards thinner and younger ice with decreased summer extent are therefore the most visible signs of climate change. Those observations would not have been possible without microwave remote sensing from satellites. Yet, observations with higher spatial and temporal resolution are needed, not only to better understand the involved processes of sea ice change but also to meet the requirements for safe navigation and operation in ice infested waters by increased touristic, economic and explorative activities. Synthetic aperture radar imagery provides the necessary spatial and often temporal resolution, year-round, to investigate the sea ice cover in terms of ice type distribution, sea ice extent and concentration as well as sea ice drift. Furthermore, sea ice thickness can be estimated by radar altimetry. To use an increasing amount of satellite data, automatic classification and retrieval of sea ice parameters is necessary. This thesis aims to provide a better understanding of potential synergies of multi-frequency radar data and fusion of altimeter data and synthetic aperture radar images for improved monitoring and observation of sea ice extent, age, thickness, concentration and drift.

Subject Categories

Remote Sensing

Geosciences, Multidisciplinary



Doktorsavhandlingar vid Chalmers tekniska högskola. Ny serie: 4729


Chalmers University of Technology



Opponent: Dr. Marko Mäkynen, Finnish Meteorological Institute, Helsinki, Finland

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