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

Anders Berg (Institutionen för rymd- och geovetenskap, Radarfjärranalys)
Göteborg : Chalmers University of Technology, 2014. ISBN: 978-91-7385-967-7.- 58 s.

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.

Nyckelord: sea ice concentration, sea ice dynamics, sea ice monitoring, satellite, synthetic aperture radar, interferometry

The thesis is, in addition to the previously mentioned papers, based on the following submitted paper:

  • Berg, A., P. Dammert and L. E. B. Eriksson, X-Band Interferometric SAR Observations of Baltic Fast Ice. Submitted to IEEE Transactions on Geoscience and Remote Sensing

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Denna post skapades 2014-01-17. Senast ändrad 2014-09-02.
CPL Pubid: 192831


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Institutioner (Chalmers)

Institutionen för rymd- och geovetenskap, Radarfjärranalys (2010-2017)


Hållbar utveckling
Geovetenskap och miljövetenskap
Rymd- och flygteknik

Chalmers infrastruktur

Relaterade publikationer

Inkluderade delarbeten:

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

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

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

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


Datum: 2014-02-13
Tid: 10:00
Lokal: 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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