Benjamin Seppke

Detecting and tracking small scale eddies in the black sea and the Baltic Sea using high-resolution Radarsat-2 and TerraSAR-X imagery (DTeddie)

High-resolution Synthetic Aperture radar (SAR) images of coastal and off-coastal areas provide a nearly weather independent monitoring of small-scale oceanographic features. In this paper, we describe the advances, which have been achieved within the DTeddie project. Therefore, we present the application of formerly developed algorithms to high-resolution SAR data to estimate the sea surface current at sub-mesoscale. Inside the derived current sea surface current fields, vortical structures, e.g. eddies, will be detected by means of local current anomalies. Another approach uses the alignment of anchored ships as an indicator of the sea surface current. To infer dependent information for each ship, we present an automatic registration method between coastal photographs and the SAR images. Both approaches have proven to yield valuable results with respect to the detection of vortical current flows at sub-mesoscale.

Fast Derivation of Soil Surface Roughness Parameters Using Multi-band SAR Imagery and the Integral Equation Model

The Integral Equation Model (IEM) predicts the normalized radar cross section (NRCS) of dielectric surfaces given surface and radar parameters. To derive the surface parameters from the NRCS using the IEM, the model needs to be inverted. We present a fast method of this model inversion to derive soil surface roughness parameters from synthetic aperture radar (SAR) remote sensing data. The model inversion is based on two different collocated SAR images of different bands, the derivation of the parameters cannot be done using one band alone. The computation of the model and the model inversion are very time consuming tasks and therefore may be impractical for large remote sensing data. We present an approach that is based on a few model assumptions to speed up the computation of the surface parameters. We applied the algorithm to detect the correlation length of the surface for dry-fallen areas in the World Cultural Heritage ”Wadden Sea”, a coastal tidal flat at the German Bight (North Sea). The results are very promising and may be used for a classification of the area in future steps.

Using Snakes with Asymmetric Energy Terms for the Detection of Varying-Contrast Edges in SAR Images

Active contour methods like snakes, have become a basic tool in computer vision and image analysis over the last years. They have proven to be adequate for the task of finding boundary features like broken edges in an image. However, when applying the basic snake technique to synthetic aperture radar (SAR) remote sensing images, the detection of varying-contrast edges may not be satisfying. This is caused by the special imaging technique of SAR and the commonly known specklenoise. In this paper we propose the use of asymmetric external energy terms to cope with this problem. We show first results of the method for the detection of edges of tidal creeks using an ENVISAT ASAR image. These creeks can be found in the World Heritage Site ”Wadden Sea” located at the German Bight (North Sea).

Influence of material origin on the size distribution of wood particles for wood-plastic composite (WPC) manufacture

This paper presents results from sieve analysis and image analysis-based particle size measurement (FibreCube) of wood particles for the manufacture of wood-plastic composites. Wood of different origin (virgin Norway spruce, post-industrial particleboard residues, mixed waste wood) was used for particle manufacture. It was found that size distributions were different, although milling conditions were equal.

From multi-sensor tracking of sea surface films to mesoscale and sub-mesoscale sea surface current fields

The knowledge about mesoscale and sub-mesoscale sea surface current fields is of high interdisciplinary interest, since it results in a better understanding of ocean-atmosphere interactions. However, many available numerical model results are of resolutions, which are too coarse to investigate mesoscale and sub-mesoscale turbulent features like eddies, particularly in coastal waters. In this work we present the results of tracking biogenic and anthropogenic surface film signatures on multi-sensor satellite images (SAR and multispectral images) to estimate the local sea surface current field. The main advantage of this approach is that the resolution of the derived current fields depends mainly on the resolution of the images, which have been used for tracking. Due to the large temporal distance between two acquisitions of a scene and the high variability of the tracked sea surface films, classical tracking methods, e.g. feature based or Optical Flow methods may not be applicable to successfully track the imaged signatures of the surface films. In this work, we use our former developed generic framework, which ensures the applicability and increases the stability of the results for wellknown tracking and Optical Flow algorithms. With this framework, it is e.g. possible to compute the sea surface current field using Optical Flow approaches even for large spatiotemporal distances and with partial scene coverage. We present and compare the results of different tracking algorithms by means of tracking biogenic sea surface films. The investigated areas are the Baltic Sea and the Black Sea. We present the use of Landsat TM, SeaWiFS, ERS-2, TerraSARX and RADARSAT-2 data for the derivation of sea surface currents. The resolution of the images used varies from moderate to fine resolution, which allows the derivation sea surface current fields of moderate to fine resolutions.

The use of spatial constraints in the derivation of mesoscale sea surface current fields from multi-sensor satellite data

Sequential multi-sensor satellite images are used for the computation of mesoscale surface currents in the Northern and Southern Baltic Proper. Different marine surface films and accumulated algae at the water surface are imaged by the sensors working in the optical, infrared, and microwave part of the electromagnetic spectrum and can thus be used as tracers for the local motion of the sea surface. Due to the generality of the problem, there are different algorithms available for motion estimation using object tracking in images. To apply these to the field of sea surface current estimation, we need to take the smoothness assumptions into account that the algorithms were built up on. We present the influence of different spatial constraints in the algorithms for the derivation of mesoscale sea surface currents using multi-sensor / multi-channel satellite images by means of a quantitative comparison with model results provided by the German Federal and Maritime Agency (BSH).

A knowledge based framework for the detection of measurement uncertainties in derived sea surface current fields

In [6] we presented an approach to measure sea surface currents from satellite images by computing the displacement vectors of distinctive image features or measuring the optical flow between successive images of the same scene. These algorithms are based on the assumption that the image flow observed is caused by the motion of surface films with the currents to be measured. Optical flow due to other image features, e.g. ship wakes, does not correspond to the motion field and causes systematic errors. The decision whether a derived measurement is valid or not by domain experts is very time-consuming. We present first steps towards an automatic knowledge-based approach that uses description logic to validate the measurements of sea surface currents. The terminological knowledge is based on the experts knowledge of the domain in conjunction with a geographical database containing factual knowledge about the scene. The combination of different sources of knowledge makes it possible to infer about the validity of sea surface current measurements from image data by reasoning based on the local context of the image features.