elib
DLR-Header
DLR-Logo -> http://www.dlr.de
DLR Portal Home | Impressum | Datenschutz | Kontakt | English
Schriftgröße: [-] Text [+]

Towards Sea Ice Classification using combined Sentinel-1 and Sentinel-3 data

Wiehle, Stefan und Frost, Anja und Murashkin, Dmitrii und Bathmann, Martin und König, Christine und König, Thomas (2023) Towards Sea Ice Classification using combined Sentinel-1 and Sentinel-3 data. International Symposium on Sea Ice 2023, 04.-09. Jun. 2023, Bremerhaven, Germany.

Dieses Archiv kann nicht den Volltext zur Verfügung stellen.

Offizielle URL: https://www.igsoc.org/wp-content/uploads/2023/06/procabstracts_80.html#A4018

Kurzfassung

In this contribution, a new machine learning approach is presented that is intended for the classification of sea ice using a combination of synthetic aperture radar (SAR) data from the Sentinel-1 satellites and an existing sea ice classification method for optical–thermal data from the Sentinel-3 satellites. Compared to a SAR-only classification, initial results show that the new approach improves the classification reliability especially in areas of open water. Sea ice is constantly changing: wind and ocean currents can push together large ice masses and close leads; the pack ice formed by these processes is often not navigable even by icebreakers. Remote sensing data reveal different structures within the ice for remote polar areas, and provide the basis for automatic sea ice classification in terms of its stage of development. In spaceborne Sentinel-1 SAR data, different ice classes can mostly be distinguished by different radar backscatter, but some ice classes exhibit a similar backscatter, limiting the applicability of radar-based classification. In Sentinel-3 SLSTR optical/thermal data, information of water, ice and snow allows a refined ice class separation after classification, but the observations are in lower spatial resolution and clouds may obstruct the view. Combining radar satellite measurements of Sentinel-1 and results of a sea ice classification using the optical/thermal measurements of the SLSTR instrument onboard the Sentinel-3 satellite offers the possibility to gain a deeper look into sea ice properties than just using one sensor. The fused classification presented here is based on a Convolutional Neural Network (CNN) classifier and discriminates 6 ice types. Its input data are the HH and HV polarization channels of the Sentinel-1 image plus pre-classified Sentinel-3 images with continuous RGB labels. Improved sea ice classification allows planning of safer routes and better awareness for possible dangerous situations for polar ships. This work was prepared in the scope of the project EisKlass2, funded by the German Federal Ministry for Digital and Transport’s mFUND programme under grant 19F2122A.

elib-URL des Eintrags:https://elib.dlr.de/194038/
Dokumentart:Konferenzbeitrag (Vortrag)
Titel:Towards Sea Ice Classification using combined Sentinel-1 and Sentinel-3 data
Autoren:
AutorenInstitution oder E-Mail-AdresseAutoren-ORCID-iDORCID Put Code
Wiehle, StefanStefan.Wiehle (at) dlr.dehttps://orcid.org/0000-0003-1476-6261NICHT SPEZIFIZIERT
Frost, AnjaAnja.Frost (at) dlr.dehttps://orcid.org/0000-0002-9748-1589NICHT SPEZIFIZIERT
Murashkin, Dmitriidmitrii.murashkin (at) dlr.de/ University Bremen, Germanyhttps://orcid.org/0000-0002-5818-0038NICHT SPEZIFIZIERT
Bathmann, Martinmartin.bathmann (at) dlr.dehttps://orcid.org/0000-0002-7594-2444NICHT SPEZIFIZIERT
König, ChristineDr. Thomas König & Partner, Fernerkundung GbR, Dießen am AmmerseeNICHT SPEZIFIZIERTNICHT SPEZIFIZIERT
König, ThomasDr. Thomas König & Partner, Fernerkundung GbR, Dießen am AmmerseeNICHT SPEZIFIZIERTNICHT SPEZIFIZIERT
Datum:8 Juni 2023
Referierte Publikation:Nein
Open Access:Nein
Gold Open Access:Nein
In SCOPUS:Nein
In ISI Web of Science:Nein
Status:veröffentlicht
Stichwörter:SAR, Sea Ice,Classification, Sentinel-1, Sentinel-3, Oceanography
Veranstaltungstitel:International Symposium on Sea Ice 2023
Veranstaltungsort:Bremerhaven, Germany
Veranstaltungsart:internationale Konferenz
Veranstaltungsdatum:04.-09. Jun. 2023
Veranstalter :International Glaciological Society, Alfred-Wegener-Institute, Helmholtz-Zentrum für Polar- und Meeresforschung, University of Bremen
HGF - Forschungsbereich:Luftfahrt, Raumfahrt und Verkehr
HGF - Programm:Raumfahrt
HGF - Programmthema:Erdbeobachtung
DLR - Schwerpunkt:Raumfahrt
DLR - Forschungsgebiet:R EO - Erdbeobachtung
DLR - Teilgebiet (Projekt, Vorhaben):R - SAR-Methoden
Standort: Bremen , Oberpfaffenhofen
Institute & Einrichtungen:Institut für Methodik der Fernerkundung > SAR-Signalverarbeitung
Hinterlegt von: Kaps, Ruth
Hinterlegt am:11 Mai 2023 14:00
Letzte Änderung:19 Jan 2024 17:45

Nur für Mitarbeiter des Archivs: Kontrollseite des Eintrags

Blättern
Suchen
Hilfe & Kontakt
Informationen
electronic library verwendet EPrints 3.3.12
Gestaltung Webseite und Datenbank: Copyright © Deutsches Zentrum für Luft- und Raumfahrt (DLR). Alle Rechte vorbehalten.