CIRFA seminar 29 April

CIRFA seminar Friday 29 April, 13:00-14:00, Forskningsparken 3, 3rd floor

Introductions by Malin Johansson, Vahid Akbari and Laurent Ferro-Famil

All welcome!



Very High Resolution Imaging of the Vertical Structure of Snowpack and Sea Ice, Prof. L. Ferro-Famil, University of Rennes 1, Rennes, France

This presentation introduces scientific investigations of both ice and snow properties based on high resolution Synthetic Aperture Radar (SAR) Tomography (TomoSAR). TomoSAR has been largely considered in recent years for forestry applications as it entails a fundamental advantage over traditional (i.e.: 2D) SAR imaging, namely the possibility to see the vertical structure of the imaged volume, to be afterwards employed as a robust basis for validation and development of physical models. The instrumentation to be employed for this scope is the Ground-Based Synthetic Aperture Radar (GB-SAR) developed by the SAPHIR team at IETR, University of Rennes I. Such a system can be operated at frequency bands ranging from C-Band to Ku-Band. The system is able to form a 2D aperture by moving transmitting and receiving antennas along a rail that can be vertically displaced, achieving a vertical resolution of few centimeters. Data are presented from the ESA campaign AlpSAR, in the Austrian Alps, dedicated to snowpack investigations, and from surveys carried out over Kattfjord, Tromsø, Norway, where sea ice was the focus of the analysis. For both snowpack and sea ice the images produced by the GBSAR revealed a multi-layered structure. In many cases the backscattered from the bottom layers was observed to dominate the one from the surface and near subsurface by over 20 dB. This result was found to be largely independent of the incidence angle. GBSAR images also turned out to provide sensitivity to propagation velocity within the snowpack, as revealed by the apparent depth variation with respect to the incidence angle. This effect was used to assess propagation velocity according to a simple model based on Snell law.

Newly formed sea ice in Arctic leads monitored by X-, C- and L- band SAR, Malin Johansson

Under calm conditions newly formed thin ice can have comparable backscatter signal to oil spills and low wind areas in synthetic aperture radar (SAR) imagery. Hence, newly formed thin sea ice could be seen as an oil spill look-alike. Given the predicted increase in maritime activities in the Arctic Ocean it is important to be able to separate thin ice from oil spills, especially if one wants to discriminate thin ice and oil within the ice pack.

During January to June 2015 the Norwegian Young sea ICE (N-ICE) cruise campaign was carried out by the Norwegian Polar Institute and partner institutes in the sea ice north of Svalbard. During this campaign, overlapping X-, C- and L-band SAR images were obtained as well as overlapping in-situ measurements. Such in-situ data include Electromagnetic soundings (EM) from helicopter. Using a combination of the EM measurements and the satellite image data we aim to gain further insight into how thin ice is seen in SAR satellite images. And how can we distinguish oil spills from thin ice.

During the campaign, a majority of the thin ice was observed in leads. Hence, we focus our study on those leads. We compare how the scattering entropy and co-polarization ratio vary with frequency and sea ice thickness.

Malin Johansson is a postdoctoral researcher funded by NORUSS, Research Council of Norway.


Quad-Polarimetric SAR for Detection and Characterization of Icebergs, Vahid Akbari

This talks investigates the potential improvement of iceberg detection and characterization using radar polarimetry. The interest in detection and monitoring of icebergs has a number of reasons. The most obvious challenge is the fact that they pose a danger to ships and offshore structures. While there is a great variety in iceberg shapes, sizes, and overall geometries, all icebergs, especially small ones, i.e., growlers, can present potential hazards to ships because they are harder to spot. As one of the most promising areas for future oil development, much attention has started to turn to the Arctic. In the high Arctic sea, there are a number of icebergs floating or grounded in sea and/or sea ice, which may cause tremendous damage to the undersea or subsea pipelines and production facilities.

A number of various satellite sensors have been used for monitoring icebergs. The use of data from optical sensors requires suitable cloud and light conditions. This restriction does not hold for synthetic aperture radar (SAR) imagery and hence iceberg detection generally is an important application of SAR in polar regions.

Potential of SAR remote sensing for iceberg detection  depends on the physical properties of the iceberg (such as size, shape, and structure), on the orientation relative to the radar-look direction, on the backscatter of the surrounding sea ice or open water, and also on the oceanic and meteorological conditions. In particular, polarimetric SAR has offered better detection performance over single-channel. It can provide polarimetric information that is inaccessible to single-channel SAR data.

The talks  presents the iceberg detection based on spectral analysis of polarimetric SAR images. The motivation of using spectral analysis for detection is that point and extended targets (i.e, icebergs with different dimensions and growlers) are supposed to have a spectral response that is more stable than surrounding sea ice or open water over the time separating.

The appearance of icebergs is evaluated with respect to scattering mechanisms and polarimetric information. To be able to detect a target in a SAR image, a significant contrast between target and background is needed. In this study, target-to-background ratio (TBR) is used to evaluate the contrast measures for different target types and background classes for different polarisation channels and the subaperture cross-correlation magnitude for different channels.

Vahid Akbari is a postdoctoral researcher funded by Arctic EO, Research Council of Norway. 

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