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Estimation of Sea State from Sentinel-1 Synthetic Aperture Radar Imagery for Maritime Situation Awareness

Pleskachevsky, Andrey and Jacobsen, Sven and Tings, Björn and Schwarz, Egbert (2019) Estimation of Sea State from Sentinel-1 Synthetic Aperture Radar Imagery for Maritime Situation Awareness. International Journal of Remote Sensing, 40 (11), pp. 4104-4142. Taylor & Francis. doi: 10.1080/01431161.2018.1558377. ISBN ISSN: 0143-1161 (Print) 1366-5901. ISSN 0143-1161.

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Official URL: https://doi.org/10.1080/01431161.2018.1558377


A new empirical algorithm CWAVE_S1-IW for estimation of significant wave height Hs including swell and wind sea from C-band satellite-borne Synthetic Aperture Radar (SAR) data has been developed for Sentinel-1 (S1) Interferometric Wide Swath Mode (IW) imagery. The algorithm was implemented into the Sea Sate Processor (SSP) for fully automatic processing for near real time (NRT) services and allow the estimation of wave fields of thousands of kilometres in the flight direction and 250 km swath from S1 IW scenes consisting of a sequence of individual images. The priority of CWAVE_S1-IW development was an automatic, fast and robust raster processing independent from wave patterns, applicable even when only clutter is visible in the SAR images. The algorithm is based on the spectral analysis of subscenes in wavenumber space. The empirical function allows direct Hs estimation from image spectra without first converting them into wave spectra and uses integrated image spectra parameters as well as estimated local wind information. A texture analysis based on Grey Level Co-occurrence Matrices (GLCM) is also applied. In this way, also the parameters of short waves can be estimated, which are not visible in S1 IW images and are only represented by clutter. The algorithm was tuned worldwide using in-situ collocated measurements of 92 buoys with more than 2500 acquisitions. The validated SSP allows automatic processing of worldwide S1 IW images in VV or HH polarization, including Atlantic storms, cyclones and huge storms in the Gulf of Alaska with an root mean square error RMSE of 80 cm for Hs. For the closed seas like the North Sea, Baltic Seas and Black Sea the accuracy is higher with an RMSE = 55 cm. The algorithm is integrated into a demonstration service, used for further validation at the DLR ground station in Neustrelitz. The NRT processing has been tested by supporting a research ship cruise in the Antarctic Sea.

Item URL in elib:https://elib.dlr.de/124579/
Document Type:Article
Additional Information:This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited, and is not altered, transformed, or built upon in any way. To cite this article: Andrey Pleskachevsky, Sven Jacobsen, Björn Tings & Egbert Schwarz (2019) Estimation of sea state from Sentinel-1 Synthetic aperture radar imagery for maritime situation awareness, International Journal of Remote Sensing, 40:11, 4104-4142, DOI: 10.1080/01431161.2018.1558377
Title:Estimation of Sea State from Sentinel-1 Synthetic Aperture Radar Imagery for Maritime Situation Awareness
AuthorsInstitution or Email of AuthorsAuthor's ORCID iD
Pleskachevsky, AndreyAndrey.Pleskachevsky (at) dlr.deUNSPECIFIED
Jacobsen, SvenSven.Jacobsen (at) dlr.dehttps://orcid.org/0000-0003-4810-4186
Tings, BjörnBjoern.Tings (at) dlr.dehttps://orcid.org/0000-0002-1945-6433
Schwarz, EgbertEgbert.Schwarz (at) dlr.deUNSPECIFIED
Date:17 January 2019
Journal or Publication Title:International Journal of Remote Sensing
Refereed publication:Yes
Open Access:Yes
Gold Open Access:No
In ISI Web of Science:Yes
DOI :10.1080/01431161.2018.1558377
Page Range:pp. 4104-4142
Publisher:Taylor & Francis
ISBN:ISSN: 0143-1161 (Print) 1366-5901
Keywords:Radar satellites, sea state, near real time services, maritime safety
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 , Neustrelitz , Oberpfaffenhofen
Institutes and Institutions:Remote Sensing Technology Institute > SAR Signal Processing
German Remote Sensing Data Center > National Ground Segment
Deposited By: Kaps, Ruth
Deposited On:08 Dec 2018 14:27
Last Modified:01 Feb 2020 03:00

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