Advanced methods for the analysis of radar sounder data acquired at the Ice Sheets

Ana-Maria Ilisei PhD Thesis Defence
27 April 2016
April 27, 2016

Date: April 27, 2016
Time: 9:30
Location: Meeting room Ofek - Polo Scientifico e Tecnologico "Fabio Ferrari" (Building Povo 1, via Sommarive 5 – Povo, Trento)

Speaker
Ana-Maria Ilisei, University of Trento

Abstract
The World Climate Research Programme has recently reconfirmed the importance of a better understanding of the Cryosphere for advancing the analysis, modeling and prediction of climate change and its impact on the environment and society. One of the most complete collection of information about the ice sheets and glaciated areas is contained in the data (radargrams) acquired by Radar Sounder (RS) instruments. The need to better understand the structure of the ice sheets and the availability of enormous quantities of radargrams call for the development of automatic techniques for an efficient extraction of information from RS data. This topic has been only marginally addressed in the literature. Thus, in this thesis we address this challenge by contributing with four novel automatic techniques for the analysis of radargrams acquired at the ice sheets, i.e.,  i) a system for the automatic classification of ice subsurface targets in RS data, ii) an unsupervised model-based technique for the automatic detection and property estimation of ice subsurface targets, iii) an automatic technique for the local 3D reconstruction of the ice sheet, by jointly using RS and Altimeter (ALT) data, and iv) an automatic technique for the estimation of radar power losses in ice as a continuous non-linear function of depth, by using RS and ice core data.  Qualitative and quantitative experimental results obtained on real RS data confirm the effectiveness of the first three techniques. Also, preliminary results have been obtained by applying the fourth technique to real RS and ice core data acquired in Greenland. 
Due to their advantages over the traditional manual approach, e.g., efficiency, objectivity, possibility of jointly analyzing multisensor data (e.g., RS, ALT), the proposed methods can support the scientific community to enhance the data usage for a better modeling and understanding of the ice sheets. Moreover, they will become even more important in the near future, since the volume of data is expected to grow from the increase in airborne and possible Earth Observation spaceborne RS missions.

Contact: Ana-Maria Ilisei, anamaria.ilisei [at] unitn.it