[Show abstract][Hide abstract] ABSTRACT: The accuracy of the high resolution coastal wave forecast model CWAM is validated on the basis of sea state information from satellite images of TerraSAR-X (TS-X). At the same time, the performance of the satellite retrieval of sea state parameters is demonstrated. Employing 2-dimensional spatial Fourier Transformation, image spectra are derived from TS-X and locally varying patterns of the peak wavelength are provided using state-of-the-art satellite retrieval. Subsequently, wavelength comparisons are performed between a typical set of TS-X scenes acquired in December 2013 over the German Bight and the model hindcasts. The results are mostly in reasonable agreement. Potential shortcomings of the wave model are discussed as well.
[Show abstract][Hide abstract] ABSTRACT: 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.
No preview · Article · Aug 2015 · International Journal of Remote Sensing
[Show abstract][Hide abstract] ABSTRACT: We examine the performance of an automated sea ice classification algorithm based on TerraSAR-X ScanSAR data. In the first step of our process chain, gray-level co-occurrence matrix(GLCM)-based texture features are extracted from the image. In the second step, these data are fed into an artificial neural network to classify each pixel. Performance of our implementation is examined by utilizing a time series of ScanSAR images in the Western Barents Sea, acquired in spring 2013. The network is trained on the initial image of the time series and then applied to subsequent images. We obtain a reasonable classification accuracy of at least 70% depending on the choice of our ice-type regime, when the incidence angle range of the training data matches that of the classified image. Computational cost of our approach is sufficiently moderate to consider this classification procedure a promising step toward operational, near-realtime ice charting.
No preview · Article · Jul 2015 · IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
[Show abstract][Hide abstract] ABSTRACT: 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.
[Show abstract][Hide abstract] ABSTRACT: We present an algorithm for automatic detection of the land-water-line from TerraSAR-X images acquired over the Wadden Sea. In this coastal region of the southeastern North Sea, a strip of up to 20 km of seabed falls dry during low tide, revealing mudflats and tidal creeks. The tidal currents transport sediments and can change the coastal shape with erosion rates of several meters per month. This rate can be strongly increased by storm surges which also cause flooding of usually dry areas. Due to the high number of ships traveling through the Wadden Sea to the largest ports of Germany, frequent monitoring of the bathymetry is also an important task for maritime security. For such an extended area and the required short intervals of a few months, only remote sensing methods can perform this task efficiently. Automating the waterline detection in weather-independent radar images provides a fast and reliable way to spot changes in the coastal topography. The presented algorithm first performs smoothing, brightness thresholding, and edge detection. In the second step, edge drawing and flood filling are iteratively performed to determine optimal thresholds for the edge drawing. In the last step, small misdetections are removed.
[Show abstract][Hide abstract] ABSTRACT: In contrast to SAR single-pol data, which allow only classical image analysis, SAR dual-pol imagery can be analyzed by means of complex polarimetry. Our work investigates the potential of different dual-pol configurations (co-pol, compact polarimetry) in different satellite SAR sensors (TerraSAR-X, Sentinel; Radarsat) for automatic sea ice classification. The first step of our analysis comprises the extraction of polarimetric features. To enrich the information content of image segments, second order statistics on these polarimetric features are additionally computed. The discriminative power and relevance of the different features are ranked by utilizing the concept of mutual information. Different selections of the most relevant features are then fed into a neural network classifier. We explore different network configurations for optimal classification results. Performance is compared for different selections of relevant features. In order to evaluate the generalizability of trained classifiers, data for classification is taken from various geographical regions (Svalbard, Kara Sea, Baffin Island Coast, Antarctic). The outcome for the different sensors is then also discussed in terms of reliability and applicability.
The implemented dual-pol processing chain exhibits improved performance over classical single-pol texture based ice classification approaches and is well-suited for fully automated ice charting purposes in near real-time situations. The promising results we achieved for our single-pol based classification algorithm during field campaigns (Akademik Shokalskyi, Polarstern, Lance) can therefore also be expected for dual-pol data, complementing our portfolio of navigation assistance products.
[Show abstract][Hide abstract] ABSTRACT: Certain genera of bacteria found in the near-surface layer of the ocean can be involved in the production and decay of surface active materials (surfactants), resulting in slicks on the sea surface. Slicks can be observed with airborne or satellite-based synthetic aperture radar (SAR). Here, we report results, which point to a connection between the presence of surfactant-producing bacteria in the upper layer of the ocean and slicks, observed visually and in SAR imagery of the sea surface. From DNA analysis of in situ samples taken during RADARSAT-2 satellite overpass in the Straits of Florida during the 2010 Deepwater Horizon oil spill, we found a higher abundance of known surfactant-producing bacteria in the slick as compared to the non-slick area; furthermore, a higher abundance of these bacteria were observed in the water column as compared to those taken from the sea surface. Surfactants produced by marine bacteria in the organic matter-rich water column can then be transported to the sea surface through diffusion or advection. Within a certain range of wind-wave conditions, the organic materials (such as dissolved oil) in the water column processed by surfactant associated bacteria can thus be monitored with high resolution remote sensing techniques.
Full-text · Article · May 2015 · Canadian Journal of Remote Sensing
[Show abstract][Hide abstract] ABSTRACT: This Note examines two Adriatic bora events recorded in TerraSAR-X (TS-X) images taken in the winters of 2011 (Case 1) and 2012 (Case 2). In Case 1, the TS-X captured an image of a deep anti-cyclonic bora, whereas in Case 2 a shallow cyclonic bora was sampled. High resolution TS-X images resolved the finer bora spatial structure to a scale of ~1 km, which has not previously been reported in bora research. In particular, the structures in Case 2 appear to be driven by surface convective heat fluxes caused by substantial temperature differences between the relatively high sea surface temperature (SST) and the overflowing very cold air. The Weather Research and Forecasting (WRF) model simulations used to aid the analyses suggest that the very low upwind T2m in Case 2 reinforced the orographic wave breaking by enhancing the cross-mountain pressure gradient. The ensuing strong cross-mountain flow was responsible for the appearance of secondary jets in the lee of Mount Velebit, for which the TS-X Case 2 scene provides the first satellite-borne evidence.
Full-text · Article · May 2015 · Quarterly Journal of the Royal Meteorological Society
[Show abstract][Hide abstract] ABSTRACT: Over the last three decades, the Arctic summer sea ice coverage has decreased significantly. This trend is expected to continue due to persistent climate change. Besides increased research efforts in this field, this phenomenon has also attracted attention from maritime
end-users. To keep Arctic shipping routes safe, monitoring of icebergs and drift ice are crucial. Satellite borne remote sensing, in particular Synthetic Aperture Radar (SAR), is ideally suited to this purpose. Wide coverage, high-frequency availability, and Independence from daylight and cloud coverage are among the major advantages of this data source. We propose automated iceberg detection and sea ice classification algorithms based on TerraSAR-X imagery and their application for near real-time purposes. Operational data acquired during several cruises into ice-infested waters are discussed. We show how maritime users benefit from such value-added SAR based products.
[Show abstract][Hide abstract] ABSTRACT: High resolution remote sensing Synthetic Aperture Radar (SAR) data from TerraSAR-X/Tandem-X satellites are used to determine and monitor the waterline in the German Wadden Sea area.
The Wadden Sea is a very unique and dynamic coastal region located in the North Sea in the German bight. Tidal flats extend several kilometres 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, these sand banks are also moved over time; heavy storms can even cause large variations in sand bank extensions in merely a few hours.
The Wadden Sea is also subject to high ship traffic to the ports of Hamburg, Bremerhaven, Wilhemshaven and others. Hence, observation of obstacles like sand banks and decreasing water depth is crucial for maritime security. Conventional monitoring campaigns with ships or airplanes are economically expensive and can only provide limited coverage.
From the high resolution TerraSAR-X/Tandem-X data of the Wadden Sea and large river estuaries like Elbe and Weser, the waterline at the time of recording is extracted using an automatic algorithm with Near-Real-Time capability. This allows for a fast and large scale determination of changes in island and coastal outlines. Additionally, the bathymetry of the observed area can be determined from the extracted waterlines by combining data from many different flybys at different tidal levels.
[Show abstract][Hide abstract] ABSTRACT: High resolution remote sensing Synthetic Aperture Radar (SAR) data from TerraSAR-X/Tandem-X satellites are used to determine and monitor the sea surface in near real time and all weather and illumination conditions. The radar backscatter of the sea surface is determined by the sea surface roughness caused by the wind field and the sea state. These meteo parameters are modelled by the newly developed algorithms XMOD and XWAVE relating the wind field and sea state, depending on incidence angle and directionality to the radar backscatter sigma0. The TerraSAR-X Modes Stripmap, Scan SAR and Scan SAR Wide are used together with Sentinel and RADARSAT data to detect ships, oil spills and icebergs. The detectability depending on the background conditions is discussed. Several examples from near real time campaigns performed together with users are given.
[Show abstract][Hide abstract] ABSTRACT: 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
[Show abstract][Hide abstract] ABSTRACT: The increasing demand for renewable energy resources has promoted the construction of offshore wind farms e.g. in the North Sea. While the wind farm layout consists of an array of large turbines, the interrelation of wind turbine wakes with the remaining array is of substantial interest. The downstream spatial evolution of turbulent wind turbine wakes is very complex and depends on manifold parameters such as wind speed, wind direction and ambient atmospheric stability conditions.
To complement and validate existing numerical models, corresponding observations are needed. While in-situ measurements with e.g. anemometers provide a time-series at the given location, the merits of ground-based and space- or airborne remote sensing techniques are indisputable in terms of spatial coverage. Active microwave devices, such as Scatterometer and Synthetic Aperture Radar (SAR), have proven their capabilities of providing sea surface wind measurements and particularly SAR images reveal wind variations at a high spatial resolution while retaining the large coverage area. Platform-based Doppler LiDAR can resolve wind fields with a high spatial coverage and repetition rates of seconds to minutes. In order to study the capabilities of both methods for the investigation of small scale wind field structures, we present a direct comparison of observations obtained by high resolution TerraSAR-X (TS-X) X-band SAR data and platform-based LiDAR devices at the North Sea wind farm alpha ventus. We furthermore compare the results with meteorological data from the COSMO-DE model run by the German Weather Service DWD.
Our study indicates that the overall agreement between SAR and LiDAR wind fields is good and that under appropriate conditions small scale wind field variations compare significantly well.
[Show abstract][Hide abstract] ABSTRACT: Exploitation of polarimetric features for oil spill detection is relatively new and until recently those properties were not exploited for operational services. This paper describes the development of a Near Real Time (NRT) oil spill detection processing chain using coherent dual-polarimetric (co-polarized channels, i.e. HH/VV) TerraSAR-X images. Proposed methodology introduces for the first time a combination of traditional and polarimetric features for object-based oil spill and look-alike discrimination. A total number of 35 feature parameters were extracted from 225 oil spill and 26 look-alikes. Extracted features are then used for training and validation of a decision tree classifier. Initial performance estimation was carried out for the proposed methodology on a large dataset acquired over well-known platform location in order to evaluate its suitability for NRT operational service.
[Show abstract][Hide abstract] ABSTRACT: In the above titled paper (ibid., vol. 52, no. 5, pp. 2928-2939, May 2014), there is a typo in equation (A3) in the Appendix. The correct equation is presented here.
No preview · Article · Jan 2015 · IEEE Transactions on Geoscience and Remote Sensing
[Show abstract][Hide abstract] ABSTRACT: The fast development of offshore wind farms have drawn increasing attention to monitoring the offshore wind turbine wakes, which are of significant importance on improving layout of large offshore wind farms, prediction of accurate output power, and safety operation of wind turbines. Spaceborne synthetic aperture radar shows its unique advantages of observing the offshore wind turbine
wakes due to high spatial resolution and large coverage. Since the launch of RADARSAT-2, TerraSAR-X and Cosmo-SkyMed in 2007, the new generation spaceborne SAR in high spatial resolution up to 1 m offers a unique advantage to investigate the fine structures of oceanic and atmospheric phenomena occurred in the air-sea interface. In the paper, we present some TerraSAR-X images acquired at the offshore wind farms in the North Sea and the East China Sea. The high spatial resolution SAR images show different sea surface wake patterns downstream of the offshore wind turbines. The analysis suggests that there are major two types of wakes among the observed cases. The wind turbine wakes generated by movement of wind around wind turbines are the most often observed cases. In contrast, due to the strong local tidal currents in the near shore wind farm sites, the tidal current wakes induced by tidal current impinging on the wind turbine piles are also observed in the high spatial resolution TS-X images. The discrimination of the two types of wakes observed in the offshore wind farms is also described in the paper.
[Show abstract][Hide abstract] ABSTRACT: High resolution remote sensing Synthetic Aperture Radar (SAR) data from TerraSAR-X/Tandem-X satellites are used to determine and monitor the sea surface in near real time and all weather and illumination conditions. The radar backscatter of the sea surface is determined by the sea surface roughness caused by the wind field and the sea state. These meteo parameters are modelled by the newly developed algorithms XMOD and XWAVE relating the wind field and sea state, depending on incidence angle and directionality to the radar backscatter Sigma 0.
The TerrasAR-X Modes Stripmap, Scan SAR and Scan SAR Wide are used to detect ships, oil spills and icebergs. The
detectability depending on the background conditions is discussed. Several examples from near real time campaigns
performed together with users are given.