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Robustness of SAR Sea Ice Type Classification across Incidence Angles and Seasons at L-band

Singha, Suman and Johansson, A. Malin and Doulgeris, Anthony P. (2021) Robustness of SAR Sea Ice Type Classification across Incidence Angles and Seasons at L-band. IEEE Transactions on Geoscience and Remote Sensing, 59 (12), pp. 9941-9952. IEEE - Institute of Electrical and Electronics Engineers. doi: 10.1109/TGRS.2020.3035029. ISSN 0196-2892.

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Official URL: https://doi.org/10.1109/TGRS.2020.3035029

Abstract

In recent years, space-borne synthetic aperture radar (SAR) polarimetry has become a valuable tool for sea ice type retrieval. L-band SAR has proven to be sensitive toward deformed sea ice and is complementary compared with operationally used C-band SAR for sea ice type classification during the early and advanced melt seasons. Here, we employ an artificial neural network (ANN)-based sea ice type classification algorithm on a comprehensive data set of ALOS-2 PALSAR-2 fully polarimetric images acquired with a range of incidence angles and during different environmental conditions. The variability within the data set means that it is ideal for making a novel assessment of the robustness of the sea ice classification, investigating the intraclass variability, the seasonal variations, and the incidence angle effect on the sea ice classification results. The images coincide with two different Arctic campaigns in 2015: the Norwegian Young Sea Ice Cruise 2015 (N-ICE2015) and the Polarstern’s (PS92) Transitions in the Arctic Seasonal Sea Ice Zone (TRANSSIZ). We find that it is essential to take into account seasonality and intraclass variability when establishing training data for machine learning-based algorithms though moderate differences in incidence angle are possible to accommodate by the classifier during the dry and cold winter season. We also conclude that the incidence angle dependence of backscatter for a given ice type is consistent for different Arctic regions.

Item URL in elib:https://elib.dlr.de/137052/
Document Type:Article
Additional Information:© 2020 IEEE; first published online -> Nov 16, 2020
Title:Robustness of SAR Sea Ice Type Classification across Incidence Angles and Seasons at L-band
Authors:
AuthorsInstitution or Email of AuthorsAuthor's ORCID iD
Singha, SumanSuman.Singha (at) dlr.dehttps://orcid.org/0000-0002-1880-6868
Johansson, A. MalinUiT The Arctic University of Norway, Department of Physics and Technology, Tromsø, NorwayUNSPECIFIED
Doulgeris, Anthony P.UiT The Arctic University of Norway, Department of Physics and Technology, Tromsø, NorwayUNSPECIFIED
Date:December 2021
Journal or Publication Title:IEEE Transactions on Geoscience and Remote Sensing
Refereed publication:Yes
Open Access:Yes
Gold Open Access:No
In SCOPUS:Yes
In ISI Web of Science:Yes
Volume:59
DOI :10.1109/TGRS.2020.3035029
Page Range:pp. 9941-9952
Publisher:IEEE - Institute of Electrical and Electronics Engineers
ISSN:0196-2892
Status:Published
Keywords:Sea ice, classification, ice type, incidence angles , SAR, L-band, MOSAiC, oceanography
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 - SAR methods
Location: Bremen , Oberpfaffenhofen
Institutes and Institutions:Remote Sensing Technology Institute > SAR Signal Processing
Deposited By: Kaps, Ruth
Deposited On:13 Nov 2020 11:15
Last Modified:21 Mar 2022 12:24

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