DLR-Logo -> http://www.dlr.de
DLR Portal Home | Imprint | Privacy Policy | Contact | Deutsch
Fontsize: [-] Text [+]

Neural Network based automatic Sea Ice Classification for CL-pol RISAT-1 Imagery

Ressel, Rudolf and Singha, Suman and Lehner, Susanne (2016) Neural Network based automatic Sea Ice Classification for CL-pol RISAT-1 Imagery. In: Geoscience and Remote Sensing Symposium (IGARSS), 2016 IEEE International, pp. 4835-4838. IEEE Xplore. IGARSS 2016, 10.- 15. Juli 2016, Peking, China. doi: 10.1109/IGARSS.2016.7730261. ISBN 978-1-5090-3332-4. ISSN 2153-7003.

[img] PDF

Official URL: http://dx.doi.org/10.1109/IGARSS.2016.7730261


SAR Polarimetry has become a valuable tool in spaceborne SAR based sea ice analysis. The two major objectives in SAR based remote sensing of sea ice is on the one hand to have a large coverage of the imaged ground area, and on the other hand to obtain a radar response that carries as much Information as possible. Whereas single-polarimetric acquisitions of existing sensors offer a wide coverage on the ground, dual polarimetric, or even better fully polarimetric data offer a higher information content which allows for a more reliable automated sea ice analysis. In order to reconcile the advantages of fully polarimetric acquisitions with the higher ground coverage of acquisitions with fewer polarimetric channels, hybrid polarimetric acquisitions offer a trade-off between the mentioned objectives. With the advent of the RISAT-1 satellite platform, we are able to explore the potential of hybrid dual pol acquisitions for sea ice analysis and classification. Our algorithmic approach for an automated sea ice classificationconsists of two steps. In the first step, we perform a Feature etraction procedure. The resulting feature vectors are then ingested into a trained neural network classifier to arrive at a pixelwise supervised classification. We present first results on a dataset acquired off the eastern Greenland coast.

Item URL in elib:https://elib.dlr.de/102298/
Document Type:Conference or Workshop Item (Poster)
Title:Neural Network based automatic Sea Ice Classification for CL-pol RISAT-1 Imagery
AuthorsInstitution or Email of AuthorsAuthor's ORCID iDORCID Put Code
Singha, SumanUNSPECIFIEDhttps://orcid.org/0000-0002-1880-6868UNSPECIFIED
Date:3 November 2016
Journal or Publication Title:Geoscience and Remote Sensing Symposium (IGARSS), 2016 IEEE International
Refereed publication:No
Open Access:Yes
Gold Open Access:No
In ISI Web of Science:No
Page Range:pp. 4835-4838
EditorsEmailEditor's ORCID iDORCID Put Code
Publisher:IEEE Xplore
Keywords:Sea Ice; Feature Extraction; SAR, Compact Pol; RISAT
Event Title:IGARSS 2016
Event Location:Peking, China
Event Type:international Conference
Event Dates:10.- 15. Juli 2016
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 14:04
Last Modified:31 Jul 2019 19:59

Repository Staff Only: item control page

Help & Contact
electronic library is running on EPrints 3.3.12
Website and database design: Copyright © German Aerospace Center (DLR). All rights reserved.