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Comparing Near Coincident Space Borne C and X Band Fully Polarimetric SAR Data for Arctic Sea Ice Classification

Ressel, Rudolf and Singha, Suman (2016) Comparing Near Coincident Space Borne C and X Band Fully Polarimetric SAR Data for Arctic Sea Ice Classification. Remote Sensing, 8 (3), pp. 1-27. Multidisciplinary Digital Publishing Institute (MDPI). doi: 10.3390/rs8030198. ISSN 2072-4292.

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Official URL: http://www.mdpi.com/2072-4292/8/3/198


This work compares the polarimetric backscatter behavior of sea ice in spaceborne X-band and C-band Synthetic Aperture Radar (SAR) imagery. Two spatially and temporally coincident pairs of fully polarimetric acquisitions from the TerraSAR-X/TanDEM-X and RADARSAT-2 satellites are investigated. Proposed supervised classification algorithm consists of two steps: The first step comprises a feature extraction, the results of which are ingested into a neural network classifier in the second step. Based on the common coherency and covariance matrix, we extract a number of features and analyze the relevance and redundancy by means of mutual information for the purpose of sea ice classification. Coherency matrix based features which require an eigendecomposition are found to be either of low relevance or redundant to other covariance matrix based features, which makes coherency matrix based features dispensable for the purpose of sea ice classification. Among the most useful features for classification are matrix invariant based features (Geometric Intensity, Scattering Diversity, Surface Scattering Fraction). This analysis reveals analogous results for all four acquisitions, in both X-band and C-band frequencies. The subsequent classification produces similarly promising results for all four acquisitions. In particular, the overlapping image portions exhibit a reasonable congruence of detected ice types

Item URL in elib:https://elib.dlr.de/98218/
Document Type:Article
Additional Information:published online
Title:Comparing Near Coincident Space Borne C and X Band Fully Polarimetric SAR Data for Arctic Sea Ice Classification
AuthorsInstitution or Email of AuthorsAuthor's ORCID iD
Ressel, RudolfRudolf.Ressel (at) dlr.deUNSPECIFIED
Singha, Sumansuman.singha (at) dlr.dehttps://orcid.org/0000-0002-1880-6868
Date:29 February 2016
Journal or Publication Title:Remote Sensing
Refereed publication:Yes
Open Access:Yes
Gold Open Access:Yes
In ISI Web of Science:Yes
DOI :10.3390/rs8030198
Page Range:pp. 1-27
Publisher:Multidisciplinary Digital Publishing Institute (MDPI)
Series Name:Special Issue “Sea Ice Remote Sensing and Analysis”
Keywords:Polarimetry; Sea Ice; Feature Evaluation; Artificial Neural Network
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Earth Observation
DLR - Research area:Raumfahrt
DLR - Program:R EO - Earth Observation
DLR - Research theme (Project):R - Vorhaben Entwicklung und Erprobung von Verfahren zur Gewässerfernerkundung (old)
Location: Bremen , Oberpfaffenhofen
Institutes and Institutions:Remote Sensing Technology Institute
Remote Sensing Technology Institute > SAR Signal Processing
Deposited By: Kaps, Ruth
Deposited On:22 Jan 2016 08:57
Last Modified:14 Dec 2019 04:26

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