Spaceborne Synthetic Aperture Radar for Sea Ice Observations, Concentration and Dynamics
Doctoral thesis, 2014

Spaceborne Synthetic Aperture Radar (SAR) is the primary choice for sea ice monitoring due to its all-weather, day-and-night capability and regular delivery of high resolution images. This thesis presents methods for estimation of sea ice concentration and drift, a multi-sensor study of Baltic Sea ice radar signatures and an interferometric study of landfast sea ice. The ice concentration is determined by combining spatial autocorrelation and backscatter intensity in a neural network, which is trained with ice charts for the Baltic Sea. The root-mean-square error of the estimated concentration is found to be 7 percentage points for a spatially uniform distribution of ice concentrations. The ice drift is estimated from sequential SAR images by combining two methods: 1) areal matching by phase correlation, and 2) feature-based matching by detection and tracking of individual floes. The first method includes a module to resolve rotation. The second method is designed to assist tracking in the marginal ice zone and processes images in two steps: Firstly, by segmentation based on intensity thresholding to obtain objects corresponding to floes, and secondly, by feature tracking of floe outlines. A thresholding method that locates the antimode of imbalanced bimodal distributions is introduced, as well as a novel method for handling of aggregated floes. Assessment against manual measurements showed that up to 98% of drift vectors were estimated correctly, though the number varies with image pair and internal settings. Further, the ice drift algorithm is applied to C-band SAR images from a two-week spring period in the Fram Strait, and the measured ice drift is compared to drift modelled by the ice-ocean model HIROMB. The model is shown to overestimate the drift by a factor 1-2.5, attributable to an underestimated ice thickness, and to exhibit a 10°-30° offset in drift direction, independent of the drift direction. The thesis also evaluates the usefulness of spaceborne SAR sensors for ice charting. The traditionally employed C-band data is compared against X- and L-band data in terms of information content. It is found that L-band co-polarisation aids identification of ridge clusters and is less affected by microscale ice structures, whereas the information content in C- and X-band data is largely equivalent. Finally, interferometric acquisitions over landfast sea ice in the Bay of Bothnia demonstrate the capability of X-band SAR for small-scale deformation mapping of fast ice. Deformation occurs for example around leads, rocky islands and grounded ice ridges.

synthetic aperture radar



sea ice dynamics

sea ice monitoring

sea ice concentration

Room EB (EDIT-building), Hörsalsvägen 11, Chalmers University of Technology
Opponent: Prof. Stein Sandven, Department of Polar Environmental Remote Sensing, Nansen Environmental and Remote Sensing Center, Norway


Anders Berg

Chalmers, Earth and Space Sciences, Radar Remote Sensing

Comparison between SAR derived sea ice displacement and hindcasts by the operational ocean model HIROMB

Proceedings of the IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Melbourne, Australia, July 21-26, 2013,; (2013)p. 3630-3633

Paper in proceeding

Evaluation of new spaceborne SAR sensors for sea-ice monitoring in the Baltic Sea

Canadian journal of remote sensing,; Vol. 36(2010)p. S56-S73

Journal article

Investigation of a Hybrid Algorithm for Sea Ice Drift Measurements Using Synthetic Aperture Radar Images

IEEE Transactions on Geoscience and Remote Sensing,; Vol. 52(2014)p. 5023 - 5033

Journal article

SAR Algorithm for Sea Ice Concentration - Evaluation for the Baltic Sea

IEEE Geoscience and Remote Sensing Letters,; Vol. 9(2012)p. 938 - 942

Journal article

Driving Forces

Sustainable development

Areas of Advance


Subject Categories

Aerospace Engineering

Remote Sensing

Earth and Related Environmental Sciences

Signal Processing

Computer Vision and Robotics (Autonomous Systems)

Other Electrical Engineering, Electronic Engineering, Information Engineering



Doktorsavhandlingar vid Chalmers tekniska högskola. Ny serie: 3648

Room EB (EDIT-building), Hörsalsvägen 11, Chalmers University of Technology

Opponent: Prof. Stein Sandven, Department of Polar Environmental Remote Sensing, Nansen Environmental and Remote Sensing Center, Norway

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