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Proceedings Paper

Estimation of ice sheet attenuation by using radar sounder and ice core data
Author(s): Ana-Maria Ilisei; Jilu Li; Sivaprasad Gogineni; Lorenzo Bruzzone
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Paper Abstract

Due to their great impact on the environment and society, the study of the ice sheets has become a major concern of the scientific community. In particular, the estimation of the ice attenuation is crucial since it enables a more precise characterization of the ice and basal conditions. Although such problem has been often addressed in the literature, the assessment of the ice attenuation is subject to several hypotheses and uncertainties, resulting in a wide range of possible interpretations of the properties of the ice. In this paper, we propose a method for constraining the ice attenuation profiles in the vicinity of an ice core by jointly using coincident radar sounder (RS) data (radargrams) and dielectric profile (DEP) data. Radargrams contain measurements of radar reflected power from ice subsurface dielectric discontinuities (layers) on wide areas. DEP data contain ice dielectric permittivity measurements collected at an ice core. The method relies on the detection of ice layers in the radargrams, the estimation of their depth and reflectivity from the DEP data, and the use of the radar equation for the estimation of ice attenuation through the whole ice column and locally at each layer position. The method has been applied to RS and DEP data acquired at the NEEM core site in Greenland. Experimental results confirm the effectiveness of the proposed method.

Paper Details

Date Published: 18 October 2016
PDF: 9 pages
Proc. SPIE 10004, Image and Signal Processing for Remote Sensing XXII, 1000416 (18 October 2016); doi: 10.1117/12.2242038
Show Author Affiliations
Ana-Maria Ilisei, Univ. degli Studi di Trento (Italy)
Jilu Li, The Univ. of Kansas (United States)
Sivaprasad Gogineni, The Univ. of Kansas (United States)
Lorenzo Bruzzone, Univ. degli Studi di Trento (Italy)

Published in SPIE Proceedings Vol. 10004:
Image and Signal Processing for Remote Sensing XXII
Lorenzo Bruzzone; Francesca Bovolo, Editor(s)

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