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River runoff on the Louisiana Coast produces shallow, low-salinity lenses. Due to the presence of a leaking oil platform (Taylor Energy), the fine structure of these lenses is visible in synthetic aperture radar (SAR) imagery. In this paper, we report results of the comprehensive study including high-resolution remote sensing and in-situ observations of low-salinity lenses on the Louisiana Coast as well as modeling the lens using a computational fluid dynamics (CFD) model. Our results indicate that these transient near-surface lenses create significant horizontal density gradients and spread as gravity currents, influencing the propagation of oil slicks.

Changes in the sea surface roughness are usually associated with a change in the sea surface wind field [...]

The Sentinel-1A is the first of two satellites that composes the Sentinel-1 radar mission. Both satellites operate a C-band synthetic aperture radar (SAR) system to give continuity to the European SAR program. SAR is a flexible sensor able to fulfil users/applications requirements in terms of resolution and coverage thanks to different operational modes and polarizations. With the in-orbit availability of very-high-resolution X-band SAR sensors, the Sentinel-1 satellites have been designed to achieve wide coverage at medium to high resolution. The interferometric wide swath (IWS) mode implemented with the terrain observation with progressive scan (TOPS) technique is the standard acquisition mode over European waters and land masses. IWS in dual-polarization (VV/VH) combination offers 250-km swath at $\hbox{5 m} \times \hbox{20 m}$ (range $\times$ azimuth) spatial resolution. These specifications are in line with the needs of the European Maritime and Security Agency (EMSA) for oil spill and ship detection applications included in the CleanSeaNet program. The main goals of this paper are: assessment of medium-to-high-resolution C-band Sentinel-1 data with very-high-resolution X-band TerraSAR-X data for maritime targets detection; synergetic use of multiplatforms satellite SAR data for target features extraction; evaluation of polarimetric target detectors for the available co-polarization and cross-polarization Sentinel-1A IWS VV/VH products. The objectives are achieved by means of real, almost coincident C-band and X-band SAR data acquired by Sentinel-1A and TerraSAR-X satellites over Gulf of Naples and Catania (South Italy). Furthermore, the obtained results are supported by recorded ground truth vessel reports via terrestrial automatic identification system (AIS) stations located in the area.

In northern latitudes, icebergs frequently cross shipping routes and impair marine traffic. To improve ship routing, we explore the capabilities of an algorithm that detects and charts icebergs from images provided by the German radar satellite TerraSAR-X. TerraSAR-X is in a near-polar orbit, equipped with an active X-Band radar antenna and, thus, allows monitoring the ocean and frozen waters regardless of cloud cover and darkness. The algorithm we apply is based on the iterative censoring constant false alarm rate (IC-CFAR) detector, which has proven its usefulness for terrestrial target detection already. Unlike the standard approach, we not only estimate statistical properties of open water intensities expressed by a probability density function, but also search for recurring patterns (i.e., waves). This allows discriminating icebergs from most false alarms that arise from rough sea and strong winds. Experiments carried out with a series of HH-polarized TerraSAR-X Stripmap images acquired bet...

Synthetic aperture radar (SAR) images are operationally used for the detection of oil spills in the marine environment, as they are independent of sun light and weather-induced phenomena. Exploitation of radar polarimetric features for operational oil spill detection is relatively new and until recently those properties have not been extensively exploited. This paper describes the development of a oil spill detection processing chain using coherent dual-polarimetric (copolarized channels, i.e., HH-VV) TerraSAR-X images. The proposed methodology focuses on offshore platform monitoring and introduces for the first time a combination of traditional and polarimetric features for object-based oil spill detection and look-alike discrimination. A total number of 35 feature parameters were extracted from 225 oil spills and 26 look-alikes and divided into training and validation dataset. Mutual information content among extracted features have been assessed and feature parameters are ranked according to their ability to discriminate between oil spill and look-alike. Extracted features are used for training and validation of a support vector machine-based classifier. Performance estimation was carried out for the proposed methodology on a large dataset with overall classification accuracy of 90% oil spills and 80% for look-alikes. Polarimetric features such as geometric intensity, copolarization power ratio, span proved to be more discriminative than other polarimetric and traditional features.

This article describes how the estimation of ship parameters from ship signatures on TerraSAR-X images can be adapted dynamically using combinatorial optimization and regression analysis. Research in the field of ship detection commonly addresses the improvement of processors with regard to accuracy performance of detection and parameter estimation. While most research implies beneficial improvements to the processors, the different techniques are rarely compared or combined. In this article the Monte Carlo combinatorial optimization cross-entropy method is used to evaluate the performance of improvements to parameter estimation and performance of combinations of these improvements. Then multiple linear regression analysis is applied to increase the accuracy of parameter estimation further. The underlying data set consists of TerraSAR-X Stripmap, ScanSAR, and ScanSAR Wide Multi Look Ground Range detected MGD images acquired over the North Sea and Baltic Sea with horizontal transmit, horizontal receive or vertical transmit, vertical receive polarization. Validation data are provided by the Automatic Identification System AIS. The optimization algorithm assesses optimal parameter settings and appropriate combinations of techniques dedicated to this data set. The resulting processor provides a significantly higher accuracy of ship parameter estimation than the initial processor.

High resolution TerraSAR-X/TanDEM-X as well as Sentinel-1 remote sensing Synthetic Aperture Radar (SAR) data are used to determine and monitor the waterline in the Wadden Sea. In this very unique and dynamic coastal region in the southeastern North Sea, tidal flats extend several kilometers away from the coast during low tide with features like tidal inlets and sand banks. Under the influence of tidal water currents transporting large amounts of eroded material, inlets and sand banks move over time; heavy storms can even cause large variations in their extensions in merely a few hours. Observation of these obstacles is crucial for maritime security as high ship traffic is caused by the ports of Hamburg, Bremerhaven, Wilhelmshaven and others. Conventional monitoring campaigns with ships or airplanes are economically expensive and can only provide limited coverage. We present an automatic algorithm with Near Real-Time capability for extracting the waterline at the time of recording from SAR images, which allows for a fast and large scale determination of changes in coastal outlines. The comparison of recent acquisitions of TerraSAR-X and Sentinel-1 to bathymetry data of the Elbe estuary obtained in 2010 reveals significant changes in tidal flat structures.

Remote sensing Synthetic Aperture Radar (SAR) data from TerraSAR-X and Tandem-X (TS-X and TD-X) satellites have been used for validation and verification of newly developed coastal forecast models in the German Bight of the North Sea. The empirical XWAVE algorithm for estimation of significant wave height has been adopted for coastal application and implemented for NRT services. All available TS-X images in the German Bight collocated with buoy measurements (6 buoys) since 2013 were processed and analysed (total of 46 scenes/passages with 184 StripMap images). Sea state estimated from series of TS-X images cover strips with length of ~200km and width of 30km over the German Bight from East-Frisian Islands to the Danish coast. The comparisons with results of wave prediction model show a number of local variations due to variety in bathymetry and wind fronts

SAR Polarimetry has become a valuable tool in spaceborne SAR based sea ice analysis. The two major objectives in SAR based remote sensing of sea ice is on the one hand to have a large coverage of the imaged ground area, and on the other hand to obtain a radar response that carries as much information as possible. Whereas single-polarimetric acquisitions of existing sensors offer a wide coverage on the ground, dual polarimetric, or even better fully polarimetric data offer a higher information content which allows for a more reliable automated sea ice analysis. In order to reconcile the advantages of fully polarimetric acquisitions with the higher ground coverage of acquisitions with fewer polarimetric channels, hybrid polarimetric acquisitions offer a trade-off between the mentioned objectives. With the advent of the RISAT-1 satellite platform, we are able to explore the potential of hybrid dual pol acquisitions for sea ice analysis and classification. Our algorithmic approach for an automated sea ice classification consists of two steps. In the first step, we perform a feature extraction procedure. The resulting feature vectors are then ingested into a trained neural network classifier to arrive at a pixelwise supervised classification. We present first results on a dataset acquired off the eastern Greenland coast.

In the present paper new algorithms to derive sea state developed at the German Aerospace Center are briefly introduced and used to determine SAR derived spectral sea state and individual parameters. As an example of SAR measurements for a severe North Pacific storm, which produced significant wave height (SWH) above 10 m are compared to ECMWF model results and Radar Altimeter. The results are intercompared and validated. Further an example of a cross sea is analyzed. It occurred in the South East Pacific and was captured clearly by consecutive ERS-2 SAR wave mode images acquired on August 10, 2000. The WAM model spectra, SAR cross spectra and nonlinear SAR retrieved spectra together with derived integral parameters of the spectra are used to analyze the generation and development of the cross sea. The swell dissipation is observed to increase in the cross sea.

Sentinel-1A (S1-A) is the first of a pair of satellites operating a C-band Synthetic Aperture Radar (SAR) developed to give continuity to the European SAR programme. After 6 months commissioning phase from its lunch on April 3rd 2014, S1-A started to systematically deliver data to Copernicus Ocean, Land and Emergency services. Interferometric Wide Swath (IWS) mode in dual-polarization VV+VH is the standard acquisition mode used for the observation of the European marine environment. The objectives of this study are the comparison and synergetic use of the S1-A imagery in IWS mode with TerraSAR-X (TS-X) imagery in StripMap mode for SAR ship detection application. Exemplary dataset acquired over the English Channel during a controlled experiment is used to pursue the objective. Automatic Identification System ships messages received by terrestrial stations in the area are used as ground truth and to identify the SAR detections.

Morphological changes in coastal areas, especially in river estuaries, are of high interest in many parts of the world. Satellite data from both optical and radar sensors can help to monitor and investigate these changes. Data from both kinds of sensors being available for up to 30 years now, allow examinations over large timescales, while high resolution sensors developed within the last decade allow increased accuracy. So the creation of digital elevation models (DEMs) of, for example, the wadden sea from a series of satellite images is already possible. ENVISAT, successfully launched on March 1, 2002, continues the line of higher resolution synthetic aperture radar (SAR) imaging sensors with its ASAR instrument and now also allows several polarization modes for better separation of land and water areas. This article gives an overview of sensors and algorithms for waterline determination as well as several applications. Both optical and SAR images are considered. Applications include morphodynamic monitoring studies and DEM generation.

Scanning Doppler lidar systems offer continuous wind measurements with some kilometres of range and a spatial distribution of concurrent measurements down to some metres. The synthetic aperture radar (SAR) satellite TerraSAR-X is capable to cover offshore areas of hundreds of square kilometres and to obtain wind data spatially distributed with some tens of metres. Images can be taken up to twice a day when the satellite passes the measurement site.Simultaneous wind speed measurements with ground based scanning Doppler lidar and TerraSAR-X in the region of the offshore wind farm "alpha ventus" in the German North Sea were collected. A comparison of both systems in free stream conditions is performed by extrapolating the lidardata to the measurement height of the radar satellite assuming a logarithmic wind profile. In wake conditions the wake tracks obtained by lidar and TerraSAR-X are compared. In free stream conditions the comparison reveals a mean absolute wind velocity difference ≤ 0.4 m/s in two of the four considered cases and 1.1 m/s in one case. The fourth case shows a bad agreement due to a unusually low radar backscatter in the satellite's measurement. In wake conditions the wind turbine wakes could be tracked in the lidar and the satellite data. The comparison for the considered case reveals similar wake tracks in principle, but no matching due to the time difference of the measurements and the lower spatial resolution of the radar measurements.

A TerraSAR-X (TS-X) Synthetic Aperture Radar (SAR) image acquired at the East China Sea offshore wind farm presents distinct wakes at a kilometer scale on the lee of the wind turbines. The presumption was that these wakes were caused by wind movement around turbine blades. However, wind analysis using spaceborne radiometer data, numerical weather prediction, and in situ measurements suggest that the prevailing wind direction did not align with the wakes. By analyzing measurement at the tidal gauge station and modeling of the tidal current field, these trailing wakes are interpreted to have formed when a strong tidal current impinged on the cylindrical monopiles of the wind turbines. A numerical simulation was further conducted to reproduce the tidal current wake under such conditions. Comparison of the simulated surface velocity in the wake region with the TS-X sea surface backscatter intensity shows a similar trend. Consequently, turbulence intensity (T.I.) of the tidal current wakes over multiple piles is studied using the TS-X observation. It is found that the T.I. has a logarithmic relation with distance. Furthermore, another case study showing wakes due to wind movement around turbine blades is presented to discuss the differences in the tidal current wakes and wind turbine wakes. The conclusion is drawn that small-scale wakes formed by interaction of the tidal current and the turbine piles could be also imaged by SAR when certain conditions are satisfied. The study is anticipated to draw more attentions to the impacts of offshore wind foundations on local hydrodynamic field.

In this article, the polarization ratio (PR) of TerraSAR-X (TS-X) vertical–vertical (VV) and horizontal–horizontal (HH) polarization data acquired over the ocean is investigated. Similar to the PR of C-band synthetic aperture radar (SAR), the PR of X-band SAR data also shows significant dependence on incidence angle. The normalized radar cross-section (NRCS) in VV polarization data is generally larger than that in HH polarization for incidence angles above 23°. Based on the analysis, two PR models proposed for C-band SAR were retuned using TS-X dual-polarization data. A new PR model, called X-PR hereafter, is proposed as well to convert the NRCS of TS-X in HH polarization to that in VV polarization. By using the developed geophysical model functions of XMOD1 and XMOD2 and the tuned PR models, the sea surface field is retrieved from the TS-X data in HH polarization. The comparisons with in situ buoy measurements show that the combination of XMOD2 and X-PR models yields a good retrieval with a root mean squ...

The high spatial resolution and large coverage of satellite-based synthetic aperture radars (SAR) offers a unique opportunity to derive mesoscale wind fields over the ocean surface, providing high resolution wind fields near the shore. For this purpose, algorithms were developed and tested using the ScanSAR aboard the Canadian satellite RADARSAT-1, operating at C-band with horizontal polarization in transmit and receive. Wind directions are extracted from wind-induced streaks visible on most SAR images. Wind speeds are derived from normalized radar cross sections (NRCS) using empirical models. The models were developed for scatterometers (SCAT) operating at C-band with vertical polarization and must be modified for horizontal polarization. Several available C-band polarization ratios were considered, including theoretical and empirical forms. To verify and improve the algorithm, wind speeds were computed from several RADARSAT-1 ScanSAR images and compared to colocated measurements from the SCAT aboard the European remote sensing satellite ERS-2 and to the results of the Danish high resolution limited area model (HIRLAM). Using the colocated measurements, the polarization ratio was estimated and applied to improve the wind retrieval algorithm. In addition, the main error sources in SAR wind field extraction are discussed with respect to the RADARSAT-1 ScanSAR data. Sensitivity studies were performed under different atmospheric situations using the modified C-band model to compute the errors due to wind direction and inaccuracies in NRCS.

A growing interest in global maritime surveillance has motivated the development of new methods and sensors to overcome the limitations of coastal-based systems coverage. Among the available state of the art tools, the Synthetic Aperture Radar (SAR) stands out as a powerful sensor for oceanographic observation and maritime surveillance, due to its capability of wide swath coverage and the ability to operate in all weather conditions. This paper examines the minimum ship size detectable by the Constant False Alarm Rate (CFAR) algorithm over different TerraSAR-X product modes, using simulation-based analyses. These analyses allow a comparison of the expected CFAR ship detection performance for different TerraSAR-X products, over different sea state conditions.

Simultaneous measurements of significant wave height (SWH) obtained from two independent active microwave sensors of Radar Altimeter 2 (RA-2) and Advanced Synthetic Aperture Radar (ASAR) onboard the ENVIronmental SATellite (ENVISAT) are used for a global verification of ocean wave models (WAMs). In the present study, SWH is retrieved from ASAR wave mode data using the empirical algorithm called C-band WAVE algorithm for ENVISAT, which is capable of representing total SWH irrespective of the cutoff of SAR. Comparisons of two radar measurements with the reanalyses ERA-Interim model (with assimilation of RA-2 measurements) and the German operational WAM (Deutscher Wetterdienst Global Sea wave Model, without assimilation before 2008) show that both WAMs agree well with ASAR and RA-2 measurements. However, the discrepancies of agreement indicate to which extent that the assimilation of RA-2 measurements can improve the performance of WAMs. Moreover, differences in the comparisons of ASAR and RA-2 measurements with the same WAM of ERA-Interim reveal that, although assimilation of RA-2 significantly improves the accuracy of model on grids near the RA-2 tracks, the improvement decreases along with the increase of distance between model grids and RA-2 tracks.

Ship detection is an important application of monitoring of environment and security or safety issues in African Waters. In order to overcome the limitations by other monitoring systems, e.g. coastal radar, surveillance with satellite Synthetic Aperture Radar (SAR) is used because of its potential to detect ships at high resolution over wide swaths and in all weather conditions and independent from sun illumination. TerraSAR-X (TS-X) is an X-band polarimetric SAR capable of imaging up to 1 m resolution in Spotlight mode. TS-X can be used for a wide variety of applications and methods of analysis including visual interpretation, mapping, digital-elevation-model creation, disaster monitoring, and oceanography. Results on the combined use of TS-X ship detection, Automatic Identification System (AIS), and satellite AIS (SatAIS) are presented. Using AIS is an effective terrestrial method for tracking vessels in real time typically up to 40 km off the coast. SatAIS is a space-based system with nearly global coverage for monitoring of AIS equipped ships. Since not all ships operate their AIS and smaller ships are not equipped with AIS, space borne SARs provide complimentary means for ship monitoring. As cases, images were acquired over the Somali Coast Area, South African Coast and Gibraltar in Stripmap mode with a resolution of 3 m at a coverage of 30 km× 50 km. The rapid tasking performance as well as the short response time of the TS-X data acquisition of the ground segment DLR-BN (Ground Station Neustrelitz, Germany), are very helpful to monitor hotspot areas such as the Gulf of Aden. For ascending orbits the delivery time of ship detection products is less than 20 min. Along with the detected ship positions, estimated wave heights and wind fields derived from large-area TS-X imagery can be used to get a detailed maritime picture of the situation.

New radar satellites image the sea surface with resolutions as high as 1 m. A large spectrum of ocean processes can be estimated using such Earth observation data. These data have been applied to investigations of geophysical processes as well as to forecast model validations and near-real-time services. The numerous processes, parameters, and features observed in high-resolution synthetic aperture radar images include winds, waves (with wavelengths as small as 30 m), oil slicks, waterline changes, changes in seabed morphology in shallow waters, wakes and bow waves of ships, underwater topography, wave energy flux along wave tracks from deep water to the coast, and breaking waves. New algorithms have been developed that are capable of taking into account fine-scale effects in coastal areas.

Synthetic aperture radar (SAR) ship detection is an important application in the field of maritime security. Azimuth ambiguities caused by the aliasing of the Doppler phase history of each point are often visible in SAR images particularly in ocean areas of low wind speed condition, e.g., in coastal areas, in harbors, etc. The main sources of azimuth ambiguities are man-made metallic structures over the ocean, e.g., ships, oil platforms etc., and over land near the coast, e.g., big tanks, bridges' pylons etc., that have a high SAR backscatter responses. Although the ambiguities' backscatter is generally low, in many situations, it is above the surrounding ocean clutter and are mistaken by classic detection techniques, like constant false alarm rate, as real targets causing false positives. This paper addresses both the discrimination of real targets from non-trivial false positives, namely those due to azimuth ambiguities and the detection itself using a Generalized- K distribution approach. The methodology is firstly proposed and demonstrated over a significant data set of full polarimetric X-band SAR data, which have been acquired by the German satellite TerraSAR-X during the experimental dual receive antenna campaign in April and May 2010. It is based on the intrinsic configuration of monostatic two-channel PolSAR systems and relies on the different signature of azimuth ambiguities in cross-polarized channels. Automatic Identification System messages collected and collocated with the data set analyzed are used as ground truth to evaluate and validate the proposed methodology.

A method to obtain underwater topography for coastal areas using state-of-the-art remote sensing data and techniques worldwide is presented. The data from the new Synthetic Aperture Radar (SAR) satellite TerraSAR-X with high resolution up to 1 m are used to render the ocean waves. As bathymetry is reflected by long swell wave refraction governed by underwater structures in shallow areas, it can be derived using the dispersion relation from observed swell properties. To complete the bathymetric maps, optical satellite data of the QuickBird satellite are fused to map extreme shallow waters, e.g., in near-coast areas. The algorithms for bathymetry estimation from optical and SAR data are combined and integrated in order to cover different depth domains. Both techniques make use of different physical phenomena and mathematical treatment. The optical methods based on sunlight reflection analysis provide depths in shallow water up to 20 m in preferably calm weather conditions. The depth estimation from SAR is based on the observation of long waves and covers the areas between about 70- and 10-m water depths depending on sea state and acquisition quality. The depths in the range of 20 m up to 10 m represent the domain where the synergy of data from both sources arises. Thus, the results derived from SAR and optical sensors complement each other. In this study, a bathymetry map near Rottnest Island, Australia, is derived. QuickBird satellite optical data and radar data from TerraSAR-X have been used. The depths estimated are aligned on two different grids. The first one is a uniform rectangular mesh with a horizontal resolution of 150 m, which corresponds to an average swell wavelength observed in the 10 × 10-km SAR image acquired. The second mesh has a resolution of 150 m for depths up to 20 m (deeper domain covered by SAR-based technique) and 2.4 m resolution for the shallow domain imaged by an optical sensor. This new technique provides a platform for mapping of coastal bathymetry over a broad area on a scale that is relevant to marine planners, managers, and offshore industry.

The increased amount of available Synthetic Aperture Radar (SAR) images involves a growing workload on the operators at analysis centers. In addition, even if the operators go through extensive training to learn manual oil spill detection, they can provide different and subjective responses. Hence, the upgrade and improvements of algorithms for automatic detection that can help in screening the images and prioritizing the alarms are of great benefit. In this paper we present the potentialities of TerraSAR-X (TS-X) data and Neural Network algorithms for oil spills detection. The radar on board satellite TS-X provides X-band images with a resolution of up to 1m. Such resolution can be very effective in the monitoring of coastal areas to prevent sea oil pollution. The network input is a vector containing the values of a set of features characterizing an oil spill candidate. The network output gives the probability for the candidate to be a real oil spill. Candidates with a probability less than 50% are classified as look-alikes. The overall classification performances have been evaluated on a data set of 50 TS-X images containing more than 150 examples of certified oil spills and well-known look-alikes (e.g. low wind areas, wind shadows, biogenic films). The preliminary classification results are satisfactory with an overall detection accuracy above 80%.

In this paper, several examples of synthetic aperture radar images of the sea surface from TerraSAR-X and RADARSAT-2 in the Straits of Florida are examined with corresponding in-situ data. The in-situ observations included vertical and horizontal fine thermo-haline structure, sonar transects, current velocity, directional wave characteristics, weather parameters, and Doppler weather radar data. The appearance of natural and artificial features in these images is discussed in relation to the environmental conditions during the overpass and the satellite sensor used for observation.

Ship detection is an important application of global monitoring of environment and security. In order to overcome the limitations by other systems, surveillance with satellite synthetic aperture radar (SAR) is used because of its possibility to provide ship detection at high resolution over wide swaths and in all weather conditions. A new X-band radar onboard the TerraSAR-X (TS-X) satellite gives access to spatial resolution as fine as 1 m. In this paper, first results on the combined use of TS-X ship detection, automatic identification system (AIS), and satellite AIS (SatAIS) is presented. The AIS system is an effective terrestrial method for tracking vessels in real time typically up to 40 km off the coast. SatAIS, as a space-based system, allows almost global coverage for monitoring of ships since not all ships operate their AIS and smaller ships are not equipped with AIS. The system is considered to be of cooperative nature. In this paper, the quality of TS-X images with respect to ship detection is evaluated, and a first assessment of its performance for ship detection is given. The velocity of a moving ship is estimated using complex TS-X data. As test cases, images were acquired over the North Sea, Baltic Sea, Atlantic Ocean, and Pacific Ocean in Stripmap mode with a resolution of 3 m at a coverage of 30 km 100 km. Simultaneous information on ship positions was available from TS-X and terrestrial as well as SatAIS. First results on the simultaneous superposition of SatAIS and high-resolution radar images are presented.

An empirical algorithm to retrieve integral ocean wave parameters such as significant wave height (SWH), mean wave period, and wave height of waves with period larger than 12 s $({H}_{12})$ from synthetic aperture radar (SAR) images over sea surface is presented. The algorithm is an extension to the Envisat Advanced SAR (ASAR) wave mode data based on the CWAVE approach developed for ERS-2 SAR wave mode data and is thus called CWAVE_ENV (CWAVE for Envisat). Calibrated ASAR images are used as the only source of input without needing prior information from an ocean wave model (WAM) as the standard algorithms used in weather centers. This algorithm makes SAR an independent instrument measuring integrated wave parameters like SWH and mean wave period to altimeter quality. A global data set of 25�000 pairs of ASAR wave mode images and collocated reanalysis WAM results from the European Centre for Medium-Range Weather Forecasts (ECMWF) is used to tune CWAVE_ENV model coefficients. Validation conducted by comparing the retrieved SWH to in situ buoy measurements shows a scatter index of 0.24 and 0.16 when compared to the ECMWF reanalysis WAM. Two case studies are presented to evaluate the performance of the CWAVE_ENV algorithm for high sea state. A North Atlantic storm during which SWH is above 18 m as observed by SAR and Radar Altimeter simultaneously is analyzed. For an extreme swell case that occurred in the Indian Ocean, the potential of using SWH measurements from ASAR wave mode data derived by the CWAVE_ENV algorithm is demonstrated.

A new X-band wind field algorithm (XMOD) based on a linear approach is discussed in another paper to describe the relationship between normalized radar cross section (NRCS), wind speed, wind direction and incidence angle. But XMOD could only be applied with VV polarization SAR data. To be use the HH polarization SAR data, two C-band polarization ratio models were analysed and modified to X-band. To demonstrate the applicability of the two models, 10m height wind speeds were computed with XMOD from several VV/HH TerraSAR-X images and validated by QuikScat and DWD model results. In addition, the wind speeds were retrieved and compared to each other from the HH and VV polarization TerraSAR-X images of the same scene at the same time.

Morphological changes in coastal areas, especially in river estuaries, are of high interest in many parts of the world. A new X-band radar on board the TerraSAR-X satellite gives access to spatial resolution as fine as 1 m. In Spotlight (SL) mode, resolution is down to 1.7 m in azimuth, with 10 × 10 km coverage. Spotlight is the best choice to monitor river estuaries, river channels, and bathymetry. Stripmap (SM) mode with a resolution down to 3.3 m and a swath width around 30 km is a perfect tool to investigate morphological features, such as coastline changes or wadden sea areas. ScanSAR (SC) mode with a resolution as fine as 18m and spatial coverage of 150 × 100 km is also used for remote sensing of coastal region and open seas. Several polarization modes allow better separation of land and water areas. For assessing the suitability of remote sensing satellite data (TerraSAR-X) to detect morphological changes, the highly morphodynamic area of the river Elbe estuary has been chosen. Morphological changes related to sedimentation, erosion and redeposition is shown by analysing in-situ data. Moreover, bottom topography retrieval can be quite efficiently demonstrated by using TerraSAR-X data compared to 1 arc-minute global relief model (ETOPO1).

In this paper, we show how satellite images taken by space-borne radar sensors can be used to determine mesoscale high-resolution wind fields in synergy with cloud parameters from optical data and, thus, help in the task of maintenance and planning offshore wind farms. The aim of this paper is to use synthetic aperture radar (SAR) and medium resolution imaging spectrometer (MERIS) onboard the environmental satellite (ENVISAT) in synergy to analyze severe weather systems, in particular, to describe the spatial evolution of the atmospheric boundary layer processes involved in cold air outbreaks. We investigated the fine-scale structure of a severe weather case on November 1, 2006 over the North Sea using satellite data. The satellite data are compared with numerical model results of the German Weather Service ldquoLokal Modellrdquo (LM) and the high-resolution limited area model (HIRLAM). LM and HIRLAM show differences in mesoscale turbulent behavior and coastal shadowing. Maximum wind speeds of up to 25 m/s are measured by SAR and are confirmed by the models. Significant differences are observed in the location of the maxima. High-resolution ENVISAT ASAR measurements provide very detailed information on small-scale atmospheric features, which seem to not be captured well by the analyzed numerical models, in particular, in coastal areas. Meteosat second generation (MSG) is used to determine the movement of cloud patterns. Cloud patterns seen in the optical data and radar cross-section modulation give a consistent dynamical picture of the atmospheric processes. The relevance for offshore wind farming is discussed.

In this study we show how satellite images taken by space-borne radar sensors can be used to determine mesoscale high resolution wind fields in synergy with cloud parameters from optical data. The aim of this study is to use Synthetic Aperture Radar (SAR) and Medium Resolution Imaging Spectrometer (MERIS) onboard the ENVIronmental SATellite (ENVISAT) in synergy to analyse severe weather systems. We investigated the fine scale structure of a severe weather case on Nov 1, 2006 over the North Sea using satellite data. The satellite data are compared with numerical model results of the German Weather Service "Lokal Modell", LM and the High Resolution Limited Area Model, HIRLAM. LM and HIRLAM show differences in mesoscale turbulent behaviour. Maximum wind speeds of up to 25 m/s are measured by SAR and are confirmed by the models. Significant differences are observed in the location of the maxima. Due to the high resolution ENVISAT ASAR measurements provide very detailed information on small scale atmospheric features, which seem to be not well captured by the analyzed numerical models in particular in coastal areas..

It is well known that satellite radar systems as flown on the ERS-2 or ENVISAT satellite are capable of providing high resolution information on the near surface ocean wind field and ocean waves independent of light or cloud conditions. In this presentation an overview is given of the retrieval of different geophysical parameters which are relevant for the optimal siting, the design and the operation of offshore wind farms and wave energy plants. Different examples of high resolution wind fields acquired over the wind parks “Horns Rev” and “Butendiek” in the North Sea are presented. Both image mode scenes of 100 km by 100 km size as well as wide swath images of 500 km by 500 km size are used for the investigation. Special emphasis is put on the use of the radar data for the analysis of small scale atmospheric phenomena like shadowing or turbulence as well as the estimation of ocean wave parameters like the significant wave height. High resolution maps of ocean wave parameters like significant wave height or wave period are presented. The presentation will also include the application of more sophisticated techniques like the use of Dual-Polarisation data available from ENVISAT. The final part of the presentation will deal with the next generation radar satellite TerraSAR-X launched in 2007. The spatial resolution of this instrument is in the order of 1 m, which is an order of magnitude better than the ENVISAT and ERS satellites used up to now. It has furthermore interferometric capabilities, which enable the derivation of ocean current information. The potential as well as the limitations of this new instrument with respect to the offshore windfarming and wave farming sector will be discussed.

Space borne radar systems are capable of providing wind field information over the ocean. Radar instruments are of high value for operational applications because of their all weather and daylight capabilities. Synthetic aperture radar (SAR) instruments as flown on the European satellites ERS-2, ENVISAT or the Canadian platform RADARSAT are of particular interest for applications where high resolution two- dimensional information on the near surface wind field is needed. All these operate in C-band. The respective wind field algorithm CMOD was tuned to this wavelength. New research focussed on high speed cases to be able to measure wind speeds above 20 m/sec and on the W to HH polarisation ratio. For future missions like TerraSAR-X, to be launched in May 2007 new wind field algorithms tuned to X-band are needed. The TerraSAR-X instrument has a spatial resolution of up to 1 m and additional features like multi polarisation which make it a very interesting tool for oceanographic applications. In this paper a new X band wind field algorithm, XMOD1.0 is introduced. The algorithm is based on the detection of wind streaks in the SAR images and scatterometer measurements of [1]. Data from the SRTM mission flown on the shuttle in February 2000 and SIR C/X SAR in 1994 are used to test the algorithm. Results are validated against in situ data and model data from ECMWF. The potential of SAR measurements to support the optimal siting, the design, as well as the operation of offshore wind parks is shown. Applications for offshore wind farming of the TerraSAR-X mission will be discussed. The platform FINO 1 was chosen as a primary test site to calibrate and validate wind fields for X band satellite images. For the development, optimisation and validation of the retrieval algorithms comparisons with in situ data, e.g., acquired at the FINO platform will be carried out. The respective calibration and validations strategies will be summarized.

Wind farming has grown rapidly in Europe over the last decade. All European countries with shallow coastal waters and strong mean coastal wind speeds are planning or already constructing offshore wind farms. Large parts of the North Sea and Baltic Sea are being investigated to see whether they are suitable for offshore wind parks. In this study we show how satellite images taken by space-borne radar sensors can be used to determine mesoscale wind fields and thus help in the task of planning offshore wind farms. High-resolution synthetic aperture radar (SAR) images acquired by the European remote sensing satellite ERS-2 showing single wind turbines are investigated. The methods for retrieving high-resolution wind fields from SAR images are explained and statistical comparisons of wind speed and wind direction at the two offshore wind park sites in the North Sea, Horns Rev and Butendiek, are given.

An algorithm is introduced, which is designed to retrieve high-resolution wind fields from C-band synthetic aperture radars (SAR) operating at both vertical and horizontal polarization. The wind directions are extracted from wind-induced streaks, which are approximately in line with the mean wind direction near to the ocean surface. The wind speeds are derived from the normalized radar cross section (NRCS) and image geometry of the calibrated SAR images, together with the local wind direction retrieved from the image. Therefore the semi empirical C-band model CMOD4, which describes the dependency of the NRCS on wind and image geometry, is used. The CMOD4 was originally developed for the scatterometer of the European remote sensing satellites ERS-1 and 2 operating at C-band with vertical polarization. Consequently CMOD4 requires modification for horizontal polarization, which is performed by considering the polarization ratio. To verify the algorithm, wind fields were computed from the European satellites ERS-1/2 and ENVISAT SAR as well as the Canadian satellite RADARSAT-1 and compared to results from numerical models and a scatterometer.

A method is presented to derive two-dimensional sea surface elevation fields from complex synthetic aperture radar (SAR) data. Applied to spaceborne SAR data as acquired by European Remote Sensing 2 (ERS-2) or the Environmental Satellite (ENVISAT), the method allows to analyze the structure of ocean wave fields, e.g., wave grouping or individual wave heights on a global scale. The technique, thus, provides wave parameters not obtained with common SAR wave retrieval schemes, which are designed to estimate the 2-D wave spectrum, i.e., second-order statistical moments of the wave field. Estimates of sea surface elevation fields are obtained based on the existing theory of SAR ocean wave imaging, i.e., the modulation of the SAR image intensity due real aperture radar and motion-related effects. A power series expansion is derived for SAR intensity images that enables the analysis of nonlinear effects as well as to derive a quasi-linear approximation of the SAR imaging model in the spatial domain. A statistical analysis is performed based on a global dataset of 2D wave spectra provided by the European Centre for Medium-Range Weather Forecast. Distributions are given for the relative error of the quasi-linear approximation in the spatial domain. It is shown that the error can be reduced by smoothing the SAR image in the azimuthal direction at the cost of lower resolution. Smoothed elevation fields are retrieved by the minimization of a cost function defined in the Fourier domain based on the quasi-linear approximation of the imaging process. A multilook technique is applied to infer the information on wave propagation directions, which is required because the SAR transfer function is non-Hermitian, i.e., the SAR image is not determined by the "frozen" sea surface, but wave motion has a significant impact. The method is applied to simulated SAR images as well as to data acquired by ERS-2. The errors of the retrieved wave field due to image noise, uncertainties in the SAR imaging model, and bandwidth limitations are analyzed. In particular, the fact that the estimated elevation field is smoothed due to the finite system resolution and smearing effects associated with wave motion is discussed. A statistical test is proposed to check the homogeneity of the SAR image. The method makes sure that atmospheric effects are not misinterpreted as being caused by ocean waves.

Recent techniques to derive sea state parameters in the spatial domain from radar images of the sea surface have been derived. This work describes these techniques in order to derive wave elevation maps from space borne SAR and nautical radar images of the sea surface. These wave elevation maps permits to extract additional sea state information in the spatial domain derived from the statistical analysis of the wave elevation, as well as wave height, spatial distribution.

Radar interferometry is known to be a useful technique for mapping terrain heights and surface currents. Several studies on along track or cross track interferometry provided highly accurate results. In the case of coastal applications a simultaneous measurement of topography and surface currents is beneficial. Therefore an approach for airborne interferometric measurements with a baseline consisting of an along and cross track component is presented. Analysis of experimental airborne interferometric data shows good results. The final accuracy is highly dependent on the accuracy of the navigation data of the aircraft.

The high spatial resolution and large coverage of satellite-based synthetic aperture radars (SAR) offer an unique opportunity to derive mesoscale wind fields over the ocean surface especially in coastal areas. For this purpose an algorithm was developed and tested using the C-band SAR images from the European remote sensing satellite ERS-2 and from the Canadian satellite RADARSAT-1. Wind speeds are derived from the normalized radar cross sections (NRCS) using a semi empirical model. The model was originally developed for a C-band scatterometer with vertical polarization and therefore has to be modified for horizontal polarization of the RADARSAT-1 SAR. Several C-band polarization ratios were considered including theoretical and empirical forms. To improve and verify the algorithm, wind speeds were computed from several RADARSAT-1 ScanSAR images and compared to results of the Danish high resolution limited area model (HIRLAM). Furthermore the main error sources in SAR wind field extraction are studied with respect to both polarizations.

Proceedings of the second international Conference on EuroGOOS, Rome, Italy, 11–13 March 1999; International audience; Surface wind fields over the ocean can be retrieved from synthetic aperture radar (SAR) measurements using empirical models. These models are based on the relation between the measured normalised radar cross section, wind speed and wind direction. In this study the applicability of these models to SAR images in a fetch limited situation is investigated. The mesoscale wind field is retrieved from one ERS-2 SAR image using the empirical C-band model CMOD_IFR2. The image was acquired on April 7, 1998 over the Gulf of Lion in the Mediterranean Sea during the Flux, Etat de la Mer et Télédétection en Condition de Fetch Variable (FETCH) experiment, which was performed to study wind and waves under fetch-limited situations. In addition, wind vectors were derived from an airborne real aperture radar (RAR) using the same empirical model as for the SAR. For comparison of the SAR and RAR retrieved results, in situ measurements were taken from a research vessel and a buoy, which were positioned in the area investigated.

Publisher Summary This chapter describes the different aspects of the complex ERS-2 synthetic aperture radar (SAR) wave mode. Flying over the ocean, the synthetic aperture radar (SAR) aboard the European remote sensing satellite ERS-2 acquires SAR images of 10 km × 6 km size every 200 km along the orbit. Imagettes are operationally processed to image power spectra (SWA.UWA) by the European space agency (ESA). As compared to conventional SAR intensity images used, SLC imagettes are better suited for wind and wave measurements because they contain a lot of additional information on sea surface motion. The multilook techniques are applied to derive directional wave spectra, ice parameters, and wind speed on a global scale. The first method is based on converting grey levels of SAR images into normalized calibrated radar cross-section (NCRS) using the ESA calibration algorithm. Wind speed is derived using the semi empirical CMOD4 algorithm and some additional information on wind direction. The complex imagettes processed with the SAR research processor (BSAR) are an important test data set to develop and validate ENVISAT ocean wave retrieval algorithms, which will be used by different meteorological institutes, such as the European Centre for Medium-Range Weather Forecast.

This paper introduces a recently developed algorithm to retrieve high-resolution wind fields over the ocean surface from spaceborne synthetic aperture radar (SAR) data. The algorithm consists of two parts, the first for determining wind direction and the second for wind speed retrieval. Wind directions are extracted from wind induced streaks e.g. from boundary layer rolls, Langmuir cells, or wind shadowing, which are approximately in line with the mean wind direction. Wind speed is derived from the normalized radar cross section (NRCS) and image geometry of the SAR image, together with the local retrieved wind direction. The application of SAR-wind retrieval in coastal regions is demonstrated using data acquired aboard the European satellites ERS-1 and ERS-2 and the Canadian satellite RADARSAT-1. These data allow to measure wind fields of an area of up to 500 km × 500 km with a resolution of up to 200 m. To improve and validate the set-up of numerical high-resolution models in coastal regions SAR-retrieved wind fields offer an unique opportunity. This is shown by comparisons of wind fields measured by SAR to results of the numerical model REMO, HIRLAM and GESIMA.Copyright © 2002 by ASME

Within the last 20 years at least 200 supercarriers have been lost, due to severe weather conditions. In many cases the cause of accidents is believed to be ‘rouge waves’, which are individual waves of exceptional wave height or abnormal shape. I situ measurements of extreme waves are scarce and most observations are reported by ship masters after the encounter. In this paper a global set of synthetic aperture radar (SAR) images is used to detect extreme ocean wave events. The data were acquired aboard the European remote sensing satellite ERS-2 every 200 km along the track. As the data are not available as a standard product of the Europea Space Agency (ESA), the radar raw data were focused to complex SAR images using the processor BSAR developed by the German Aerospace Center. The entire SAR data set covers 27 days representing 34000 SAR imagettes with a size of 5km×10km. Complex SAR data contain information on ocean wave height, propagation direction and grouping as well as on ocean surface winds. Combining all of this information allows to extract and locate extreme waves from complex SAR images on a global basis. Special algorithms have been developed to retrieve the following parameters from the SAR data: Wind speed and direction, significant wave height, wave direction, wave groups and their individual heights. The satellite ENVISAT launched in March 2002 acquires SAR data with an even higher sampling rate (every 100 km). It is expected that a long-term analysis of ERS and ENVISAT data will give new insight into the physical processes responsible for rogue wave generation. Furthermore, the identification of hot spots will contribute to the optimization of ship routes.

In 2001 the European Space Agency ESA will launch the earth observation satellite ENVISAT. It will carry several instruments that provide new opportunities to measure oceanographic variables. Together, they represent the main measurement techniques of satellite oceanography, and complement each other in an ideal manner. These instruments are to be used in synergy to: • Improve the analysis of measured wind and ocean wave fields, and thereby improve weather forecasting at weather centers; • Determine the extent and variables of sea ice and develop a five-day sea ice prediction model, to support maritime shipping and offshore activities; • Monitor and map sediment and suspended matter transport in coastal regions, especially in areas with large river estuaries, which greatly affects shipping lanes, harbors, and dredging activities; • Monitor hydrobiological and bio-geochemical variables related to water quality in coastal regions and large inland waters, which affects ecology, coastal development, aquaculture, drinking water supplies, and tourism. To prepare the oceanographic community to make best use of the ENVISAT sensors in the pre-launch phase, existing algorithms to derive marine parameters are used and validated using data from the ERS SAR, the ERS RA, SeaWiFS and IRS MOS sensors now in operation. Derived products are used to address problems that can best be tackled using the synergy of radar and optical data, such as the effect of surface slicks on radar wind measurements, of sea state on ocean color, of wind and waves on the resuspension of suspended matter, and of wind and waves on sea ice variables.

An across track interferometric synthetic aperture radar (InSAR) is used to image ocean waves. Across track InSAR data were acquired during the SAR INnterferometry Experiment for validation of ocean Wave imaging models (SINEWAVE) in the North Sea using an airborne X-band radar with horizontal polarization. A wind sea system was imaged at different flight levels and with different flight directions with respect to the ocean wave propagation direction. Simultaneously, ocean wave spectra were measured by a directional wave rider buoy. Thus, the experiment data comprises synthetic aperture radar (SAR) intensity, coherence, and phase images together with in situ measurements. As shown in a recent theoretical study by Schulz-Stellenfleth and Lehner (2001), across track InSAR provides distorted (bunched) digital elevation models (DEMs) of the sea surface. Using SINEWAVE data the DEM bunching mechanism is verified with in situ ocean wave measurements available for the first time. It is shown that significant waveheight as well as one-dimensional (1D) wavenumber spectra derived from bunched DEMs and buoy data are in good agreement for small nonlinearities. Peak wave directions and peak wavelength detected in bunched DEMs and SAR intensity images are compared with the buoy spectrum. Peak rotations of up to 30/spl deg/ with respect to the buoy spectrum are found depending on flight direction and flight level. Two-dimensional (2D) spectra of bunched DEMs, corresponding coherency maps, and SAR intensity images are intercompared. The signal-to-noise ratio (SNR) of bunched DEM spectra is shown to be about 5 to 10 dB higher than the SNR of SAR intensity image spectra.

Causal connections between mesoscale wind patterns and moisture distribution in the lower boundary layer can be studied using satellite synthetic aperture radar (SAR) observations. Wind information is retrieved from radar backscatter intensity over water areas, whereas the moisture distribution is reflected in the radar signal delay. The latter can only be observed over land areas, using the interferometric combination of two radar images. This paper reports on the relation between wind and moisture associated with boundary layer rolls and with a cold-frontal rain band. The combination of both signals, originating from one sensor, is used to infer a quantitative description of the underlying dynamical processes.

To calibrate synthetic aperture radar (SAR) images to normalized radar cross sections (NRCS) a calibration constant is required. Usually the calibration constant is determined by analyzing measurements of corner reflectors. However, due to the high costs there are only a very limited number of corner reflectors available. In this paper a new method for estimating the calibration constant on the basis of a few days of SAR data is introduced. The method is based on knowledge of the dependency of the NRCS on the ocean surface wind, which is described by well-tested empirical C-band models, e.g., CMOD4 and CMOD IFR2. Given the mean wind vector at each SAR wave mode image both models enable to derive the mean NRCS of the image. Application of the method is demonstrated and validated utilizing a total of 34000 SAR imagettes and co-located winds from the European Centre for Medium range Weather Forecast and the ERS-2 scatterometer. The SAR imagettes were processed to ENVISAT ASAR-like single look complex SAR images using three weeks of SAR wave mode data. It is shown that the method is an ideal tool for retrieving the SAR calibration constant and is capable to monitor and estimate variations of the calibration constant, e.g., due to saturation of the SAR analogue to digital convertor or gain drifts.

In the framework of the EuroROSE project high resolution ocean wave, wind and current fields were measured at the North Coast of Spain by simultaneous data acquisitions of spaceborne, airborne, and in situ instruments. The objective of the project was to provide a guidance system for ships entering the harbour of Gijon, by monitoring and forecasting wind, waves and currents. This paper presents first results of a new airborne three antenna interferometric synthetic aperture radar (InSAR) system which provides information on both sea surface elevation and motion. The system transmits and receives signals with a combination of three antennas, whereby two are placed along flight direction and the third in across flight direction. This configuration allows, for the first time, to acquire along and across track InSAR data simultaneously. The system was flown in different flight patterns with simultaneous measurements of directional wave spectra, wind and currents fields taken by the HF-radar WERA, the radar based wave monitoring system WaMoSII, the ERS-2 SAR and a waverider buoy.