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Sea State from High Resolution Satellite-borne Synthetic Aperture Radar Imagery

Pleskachevsky, Andrey and Wiehle, Stefan and Gebhardt, Claus P. and Schwarz, Egbert and Krause, Detmar and Bruns, Thomas and Kieser, Jens (2016) Sea State from High Resolution Satellite-borne Synthetic Aperture Radar Imagery. In: Proceedings Hydro 2016, pp. 1-10. HYDRO 2016, 08. - 10. Nov. 2016, Rostock - Warnemünde, Germany.

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Official URL: http://hydro2016.com/conference-program.php


The Sea Sate Processor (SSP) was developed for fully automatic processing of high-resolution Synthetic Aperture Radar (SAR) data from TerraSAR-X (TS-X) satellites and implemented into the processing chain for Near Real Time (NRT) services in the DLR Ground Station "Neustrelitz". The NRT chain was organised and tested to provide the processed data to the German Weather Service (DWD) in order to validate the new coastal forecast model CWAM (Coastal WAve Model) in the German Bight of the North Sea with 900 m horizontal resolution. The NRT test-runs, wherein the processed TS-X data were transferred to DWD and then incorporated into forecast products reach the best performance about 10 min for delivery of processed TS-X data to DWD server after scene acquisition. To do this, a new empirical algorithm XWAVE_C (C = coastal) for estimation of significant wave height from X-band satellite-borne SAR data has been designed for coastal applications. The algorithm is based on the spectral analysis of subscenes and the empirical model function yields an estimation of integrated sea state parameters directly from SAR image spectra without transformation into wave spectra. To provide the raster coverage analysis, the SSP intends three steps of recognising and removing the influence of non-sea-state-produced signals in the Wadden Sea areas such as ships, buoys, dry sandbars as well as nonlinear SAR image distortions produced by e.g. short and breaking waves. For the validation, more than 150 TS-X StripMap scene sequences with a coverage of ~30 km × 300 km across the German Bight since 2013 were analysed and compared with in situ Buoy measurements from 6 different locations. On this basis, the SSP autonomous processing of TS-X Stripmap images has been confirmed to have a high accuracy with an error RMSE = 25 cm for the total significant wave height.

Item URL in elib:https://elib.dlr.de/103687/
Document Type:Conference or Workshop Item (Speech)
Additional Information:PDF available under [5A4]
Title:Sea State from High Resolution Satellite-borne Synthetic Aperture Radar Imagery
AuthorsInstitution or Email of AuthorsAuthor's ORCID iD
Pleskachevsky, AndreyAndrey.Pleskachevsky (at) dlr.deUNSPECIFIED
Wiehle, StefanStefan.Wiehle (at) dlr.dehttps://orcid.org/0000-0003-1476-6261
Gebhardt, Claus P.Claus.Gebhardt (at) dlr.dehttps://orcid.org/0000-0003-4811-6267
Schwarz, EgbertEgbert.Schwarz (at) dlr.deUNSPECIFIED
Krause, DetmarDetmar.Krause (at) dlr.deUNSPECIFIED
Bruns, ThomasThomas.Bruns (at) dwd.deUNSPECIFIED
Kieser, JensJens.Kieser (at) dwd.deUNSPECIFIED
Date:9 November 2016
Journal or Publication Title:Proceedings Hydro 2016
Refereed publication:No
Open Access:Yes
Gold Open Access:No
In ISI Web of Science:No
Page Range:pp. 1-10
Keywords:SAR, Sea State, Coastal Processes, TerraSAR-X, NRT, Bathymetry
Event Title:HYDRO 2016
Event Location:Rostock - Warnemünde, Germany
Event Type:international Conference
Event Dates:08. - 10. Nov. 2016
Organizer:German Hydrographic Society (DHyG) on behalf of the International Federation of Hydrographic Societies (IFHS)
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 , Neustrelitz , Oberpfaffenhofen
Institutes and Institutions:Remote Sensing Technology Institute
Remote Sensing Technology Institute > SAR Signal Processing
German Remote Sensing Data Center > National Ground Segment
German Remote Sensing Data Center
Deposited By: Kaps, Ruth
Deposited On:31 Mar 2016 15:19
Last Modified:31 Jul 2019 20:00

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