scholarly journals New Algorithm and Processor for Obtaining Maritime Information from Sentinel-1 Radar Imagery for Near Real Time Services

2020 ◽  
Author(s):  
Andrey Pleskachevsky ◽  
Björn Tings ◽  
Sven Jacobsen ◽  
Egbert Schwarz ◽  
Detmar Krause ◽  
...  
Keyword(s):  
High Resolution ◽  
Synthetic Aperture Radar ◽  
Real Time ◽  
Wave Height ◽  
Surface Wind ◽  
Open Ocean ◽  
Synthetic Aperture ◽  
Sea State ◽  
Sar Imagery

<p>The focus of the study is analysing storm peak/center propagation, front movement and arrival of swell using newest remote sensing information, numerical models, <em>in-situ</em> measurements and their combination. For this purposes, a new empirical algorithm for sea state retrieval from satellite borne Sentinel-1 (S1) Synthetic Aperture Radar (SAR) imagery was developed. The algorithm is applied inside a new processor for meteo-marine parameter estimation for Near Real Time (NRT) applications. These NRT-applications include the investigation of geophysical processes using different satellite modes ranging from high resolution modes with small image coverage of ~20km in open ocean to low resolution modes with wide coverage of ~250km in shelf areas.</p><p>The quick developments in satellite techniques, processors, algorithms and ground infrastructures provide new possibilities for series of oceanographic applications in the last years. These new techniques allow estimation of a wide range of oceanographic information including properties of surface waves and internal waves, surface wind speed, sub-meso scale fronts and eddies, ice coverage, oil spills, coastal bathymetry, currents and others. Generally, the new high resolution products from different models allow verification of meteo-marine parameters more accurately. Here, a cross validation with different sea state model results using WWIII (NOAA) and CMEMS (COPERNICUS), with <em>in situ</em> buoy measurements and with satellite estimated parameters allowed an significant improvement of the accuracy of the derived sea state and wind fields. </p><p>The new empirical algorithm allows estimation of total integrated sea state parameters including significant wave height <em>H<sub>s</sub></em>, first moment wave period <em>T<sub>m1</sub></em>, second moment period <em>T<sub>m2</sub></em>, mean period <em>T<sub>m</sub></em> and also partial integrated parameters like swell and windsea wave heights and windsea period. The algorithm allows processing of different S1 Synthetic Aperture Radar (SAR) modes into sea state fields: </p><ul><li>S1 Wave Mode (WV) acquires multiple vignettes with an extent of ~20km×20km and each displaced by 100 km along satellite tracks in open ocean (global). About 60 tracks around the globe have been acquired per day. The relatively high spatial resolution of ~4 m allows estimating wave height with accuracy of ~35cm. This is comparable with the accuracy of satellite altimetry and a new achievement for SAR based techniques. </li> <li>S1 Interferometric Wide Swath Mode (IW) covers area-strips of thousand kilometres of earth and ocean surface in coastal areas with a resolution of ~30m by sequences of multiple images with an approximate size of 200km×250km. The accuracy of ~ 70cm (<em>H<sub>s</sub></em>) for this mode is not as so high as for S1-WV, because the short waves are not visible for S1-IW mode and imaged as noise. However, the accuracy is much higher than state-of-the-art methods for this mode. </li> </ul><p>The algorithm has been integrated into a prototype processor for Sentinel-1 SAR imagery. The DLR Ground Station Neustrelitz applies this prototype as part of a near real-time demonstrator MSA service. The presented scientific service involves daily provision of surface wind and sea state parameters estimated fully automatically from S1 IW images of North and Baltic Sea in and around German territorial waters.</p>

Multiparametric Sea State from Spaceborne Synthetic Aperture Radar for Near Real Time Services

2021 ◽  
Author(s):  
Andrey Pleskachevsky ◽  
Björn Tings ◽  
Sven Jacobsen ◽  
Egbert Schwarz ◽  
Detmar Krause
Keyword(s):  
Synthetic Aperture Radar ◽  
Real Time ◽  
Spatial Information ◽  
Surface Wind ◽  
State Parameter ◽  
Synthetic Aperture ◽  
Wide Field ◽  
Atmospheric Conditions ◽  
Sea State ◽  
Aperture Radar

<p>Spaceborne synthetic aperture radar (SAR) is a powerful tool for monitoring marine environmental parameters of the seas. The ability to work independently of sun illumination, cloud coverage and atmospheric conditions, as well as the capability of delivering spatial information, makes SAR one of the most perceptive instruments. The newest methods for processing SAR data with increased precision allow sea state fields to be estimated with local variabilities. For large areas in oceans where no <em>in-situ</em> measurements and only forecast predictions are available, this information is indispensable for global shipping and over human activity. Due to newest developments, the derived meteo-marine parameters can be transferred to weather services and to a ship’s bridge several minutes after acquisition, where the ship route can be optimized.</p> <p>The study presents a method and application for estimating series of integrated sea state parameters from satellite-borne SAR, allow processing of data from different satellites and modes in near real time (NRT). The developed Sea State Processor (SSP) estimates total significant wave height <em>H<sub>s</sub></em>, dominant and secondary swell and windsea wave heights, first, and second moment wave periods, mean wave period and period of wind sea. The algorithm was applied for the Sentinel-1 (S1) C-band Interferometric Wide Swath Mode (IW), Extra Wide (EW) and Wave Mode (WM) Level-1 (L1) products and also extended to the X-band TerraSAR-X (TSX) StripMap (SM) mode. The scenes are processed in raster and result in continuous sea state fields with the exception of S1 WV. Each 20 km × 20 km WV imagette, acquired every 100 km along the orbit, presents averaged values for each sea state parameter.</p> <p>The SSP was tuned and validated using two independent global wave models WAVEWATCH-3 (NOAA) and CMEMS (Copernicus) and NDBC buoys. The accuracy of <em>H<sub>s</sub></em> reaches an RMSE of 0.25  m by comparison with models (S1 WV); comparisons to NDBC worldwide buoys result into an RMSE of 0.31  m. Due to implemented parallelization, a fine rater step for scene processing can be practical applied: for example, S1 IW scene with coverage of 200  km  ×  250  km can be processed using raster step of 1  km (corresponds to ~50.000 subscenes) during minutes.</p> <p>The DLR Ground Station “Neustrelitz” applies SSP as part of a near real-time demonstrator service that involves a fully automated daily provision of surface wind and sea state parameters estimates from S1 IW for the North and Baltic Sea. All results and the presented methods are novel and provide a wide field for applications and implementations in prediction systems.</p>

Better Utilization of SAR Dynamic Range

1977 ◽  
Vol 21 (3) ◽  
pp. 235-240
Author(s):  
Edward J. Dragavon
Keyword(s):  
Computer Simulation ◽  
Synthetic Aperture Radar ◽  
Real Time ◽  
Image Enhancement ◽  
Dynamic Range ◽  
Synthetic Aperture ◽  
Analytic Methods ◽  
Sar Imagery ◽  
Gray Shade ◽  
Aperture Radar

Three general classes of image enhancement techniques for synthetic aperture radar (SAR) video were investigated through non-real-time computer simulation. The general categories were 1) monochromatic adaptive gray shade transformations, 2) pseudocolor encoding, and 3) feature analytic methods. The class of feature analytic techniques was found to have the greatest potential for improving the operational utility of SAR imagery.

scholarly journals An Empirical Algorithm to Retrieve Significant Wave Height from Sentinel-1 Synthetic Aperture Radar Imagery Collected under Cyclonic Conditions

2018 ◽  
Vol 10 (9) ◽  
pp. 1367 ◽  
Author(s):  
Weizeng Shao ◽  
Yuyi Hu ◽  
Jingsong Yang ◽  
Ferdinando Nunziata ◽  
Jian Sun ◽  
...  
Keyword(s):  
Synthetic Aperture Radar ◽  
Wave Height ◽  
Significant Wave Height ◽  
Synthetic Aperture ◽  
Training Dataset ◽  
Sar Images ◽  
Data Set ◽  
Significant Wave ◽  
Sar Imagery ◽  
Aperture Radar

In this study, an empirical algorithm is proposed to retrieve significant wave height (SWH) from dual-polarization Sentinel-1 (S-1) synthetic aperture radar (SAR) imagery collected under cyclonic conditions. The retrieval scheme is based on the well-known CWAVE empirical function that is here updated to deal with multi-polarization S-1 SAR measurements collected using the interferometric wide (IW) and the Extra Wide-Swath (EW) imaging modes, under cyclonic conditions. First, a training dataset that consists of six S-1 SAR images collected under cyclonic conditions is exploited to both tune the retrieval function and to check the soundness of the retrievals against the co-located WAVEWATCH-III (WW3) numerical simulations. The comparison of simulation from the WW3 model and measurements from altimeter Jason-2 shows a 0.29m root mean square error (RMSE) of significant wave height (SWH). Then, a testing data-set that consists of two S-1 SAR images is exploited to provide a preliminary validation. The results, verified against both WW3 and European Centre for Medium-Range Weather Forecasts (ECMWF) data, show the soundness of the herein approach.

scholarly journals Validation of Sentinel-1 offshore winds and average wind power estimation around Ireland

2020 ◽  
Vol 5 (3) ◽  
pp. 1023-1036 ◽  
Author(s):  
Louis de Montera ◽  
Tiny Remmers ◽  
Ross O'Connell ◽  
Cian Desmond
Keyword(s):  
Wind Speed ◽  
Synthetic Aperture Radar ◽  
Wind Power ◽  
Surface Wind ◽  
Synthetic Aperture ◽  
Synthetic Aperture Radar Data ◽  
Average Wind ◽  
Level 2 ◽  
Aperture Radar

Abstract. In this paper, surface wind speed and average wind power derived from Sentinel-1 Synthetic Aperture Radar Level 2 Ocean (OCN) product were validated against four weather buoys and three coastal weather stations around Ireland. A total of 1544 match-up points was obtained over a 2-year period running from May 2017 to May 2019. The match-up comparison showed that the satellite data underestimated the wind speed compared to in situ devices, with an average bias of 0.4 m s−1, which decreased linearly as a function of average wind speed. Long-term statistics using all the available data, while assuming a Weibull law for the wind speed, were also produced and resulted in a significant reduction of the bias. Additionally, the average wind power was found to be consistent with in situ data, resulting in an error of 10 % and 5 % for weather buoys and coastal stations, respectively. These results show that the Sentinel-1 Level 2 OCN product can be used to estimate the wind resource distribution, even in coastal areas. Maps of the average and seasonal wind speed and wind power illustrated that the error was spatially dependent, which should be taken into consideration when working with Sentinel-1 Synthetic Aperture Radar data.

scholarly journals Extensive High-Resolution Synthetic Aperture Radar (SAR) Data Analysis of Tropical Cyclones: Comparisons with SFMR Flights and Best Track

2020 ◽  
Vol 148 (11) ◽  
pp. 4545-4563 ◽  
Author(s):  
Clement Combot ◽  
Alexis Mouche ◽  
John Knaff ◽  
Yili Zhao ◽  
Yuan Zhao ◽  
...  
Keyword(s):  
High Resolution ◽  
Synthetic Aperture Radar ◽  
Tropical Cyclones ◽  
Surface Wind ◽  
Heavy Precipitation ◽  
Ocean Surface ◽  
Outer Core ◽  
Synthetic Aperture ◽  
Airborne Measurements ◽  
Aperture Radar

AbstractTo produce more precise descriptions of air–sea exchanges under tropical cyclones (TCs), spaceborne synthetic aperture radar (SAR) instruments provide unique capabilities to probe the ocean surface conditions, at very high spatial resolution, and on synoptic scales. Using highly resolved (3 km) wind fields, an extensive database is constructed from RadarSat-2 and Sentinel-1 SAR acquisitions. Spanning 161 tropical cyclones, the database covers all TC intensity categories that have occurred in 5 different TC basins, and include 29 cases coincident with SFMR measurements. After locating the TC center, a specific methodology is applied to filter out areas contaminated by heavy precipitation to help extract, for each acquisition, the maximum wind speed (Vmax), its associated radius (Rmax), and corresponding outer wind radii (R34/50/64 kt). These parameters are then systematically compared with best track (BTK), and when available, SFMR airborne measurements. For collocated SFMR and SAR observations, comparisons yield root-mean-squares of 3.86 m s−1 and 3 km for ocean surface wind speeds and TC Rmax, respectively. High correlations remain for category-5 cases, with Vmax exceeding 60 m s−1. The largest discrepancies are found between BTK and SAR Rmax estimates, with Rmax fluctuations poorly captured by BTK, especially for rapidly evolving category-3, -4, and -5 TCs. In heavy precipitation (>35 mm h−1), the SAR C-band measurements may be impacted, with local ambiguities associated with rain features, as revealed by external rain measurements. Still, this large dataset demonstrates that SAR measurements have unique high-resolution capabilities, capturing the inner- and outer-core radial structure of the TC vortex, and provide independent and complementary measurements than those used for BTK estimates.

scholarly journals Application for Displaying Synthetic Aperture Radar Imagery in Real-time Implementation and Results

2015 ◽  
Vol 61 (4) ◽  
pp. 345-350
Author(s):  
Krzysztof Borowiec
Keyword(s):  
Synthetic Aperture Radar ◽  
Real Time ◽  
Synthetic Aperture ◽  
Processing Application ◽  
Time Operation ◽  
Real Time Operation ◽  
Radar Imagery ◽  
Synthetic Aperture Radar Imagery ◽  
Sar Imagery ◽  
Aperture Radar

Abstract The paper presents implementation and results of the application for displaying SAR (Synthetic Aperture Radar) imagery operating in real-time. The application performs SAR imagery formation and displays results in real-time after receiving of preprocessed data via an SAR processing application. The application was used in SARape (Synthetic Aperture Radar for all weather penetrating UAV application) project founded by the European Defence Agency. The real-time operation is achieved thanks to implementation based on multithreading.

Sign in / Sign up

Export Citation Format

Share Document