CIRFA Seminar Thursday 25. November

We are pleased to invite you to this weeks` CIRFA seminar given by post doc Debanshu Ratha.

Title: The Geodesic Distance-Based Approach to PolSAR Data Analysis and its Potential for Sea-Ice Applications.

When: 25 November 2021, 14:00-15:00.

Where: Teams Click here to join the meeting

Photographed by Swagat Saurav Mishra and edited by Debanshu Ratha.
Location: Venice, Italy.

Abstract: To monitor activities and phenomenon in the Arctic region, the Synthetic Aperture Radar (SAR) is more reliable due to its ability to acquire images day and night, as well as in cloudy conditions. Polarimetry along with SAR provides the added advantage of identifying classes of sea-ice, water and iceberg etc. which is both crucial for environment and for planning of maritime activities. The ESA Sentinel satellites provide dual polarimetric SAR images in wide areal swaths almost on a daily basis for the Arctic region. Thus, it is important to use this data to build a framework to monitor the Arctic region and provide accurate real-time classification of the scene.
Recently, the approach using the geodesic distance in the Kennaugh matrix space has opened up avenues for a number of applications for quad polarimetric SAR data. The initial results are encouraging and suggest a potential of this approach for sea ice applications. We will explore the difference in working with dual polarimetric SAR data in comparison to quad polarimetric SAR data and how the geodesic distance based approach still finds its relevance in the changed scenario.

Short bio: Debanshu Ratha has completed his five year Integrated M.Sc. in Mathematics from NISER, Bhubaneswar and Ph.D. from I.I.T Bombay. During his Ph.D., he has been a visiting researcher at the Universitie of Rennes 1, France for six months under the Indo-French Raman-Charpak Fellowship programme. Currently, he is a postdoc at the Department of Physics and Technology, UiT Norway where his objective is to develop interpretable features and methods for sea ice classification using radar polarimetry.

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