133 publications from this institution
The Baltic Sea is one of the busiest marine regions in terms of commercial shipping. Increased marine traffic over the last decades already led to increased number of bigger ships and more powerful propulsions systems. This development has put a number of environmental effects of shipping, such as air pollution, marine noise or accidental discharges of hazardous substances, on the discussion list. What has, however, only marginally been studied is the possible effect of commercial shipping on sedimentation patterns and seafloor morphology. Here we use AIS data from the last 20 years to identify hotspots of marine traffic in the Baltic Sea. Subsequently we collect multibeam bathymetric data from different sources and databases to investigate seafloor morphology in some traffic hotspots. We further collect seabed sediment samples and time-lapse bathymetric data in the Bay of Kiel, where Kiel Canal, one of the most heavily used artificial waterways on the globe, commences. First results indicate that ships can erode hard substrate such as basal till, most likely through interaction of their wake with the seafloor. In addition to eroding the hard seafloor, the wakes may also mobilize and locally redistribute mobile sands.
Understanding the tsunami cycle requires a simple method for identification of tsunami backwash deposits. This study investigates Fourier transform infrared (FTIR) spectroscopy followed by careful analysis of variance (ANOVA), Gaussian distribution, hierarchical cluster analysis (HCA) and principal component analysis (PCA) for the discrimination of typical marine sediments and tsunami backwash deposits. In order to test the suitability of FTIR spectra as innovative methods for classifications of tsunami deposits, typical marine sediments and terrestrial soils were classified into three zones, namely zone-1 (i.e. typical marine sediments), zone-2 (i.e. including tsunami backwash deposits) and zone-3 (i.e. coastal terrestrial soils). HCA was performed to group the spectra according to their spectral similarity in a dendrogram and successfully separate FTIR spectra of all three sampling zones into two main clusters with five sub-clusters. The simplicifolious (i.e. single-leafed) type of dendrogram was observed with the strong dissimilarity of terrestrial components in subcluster-5. Graphical displays of PC1 vs PC2 highlight the prominent features of zone-1, which is explicitly different from those of zone-2 and zone-3. The acceptable discrimination of typical marine sediments and tsunami backwash deposits, even six years after the tsunami on Boxing Day 2004, dramatically demonstrates the potential of the method for the identification of paleotsunami.
The attached mosaics of side scan sonar data were recorded during 3 field campaigns in 2007, 2008 and 2010. High backscatter values are represented by darker colours. The mosaic is georeferenced in EPSG:32647 - WGS 84 / UTM zone 47N. Please refer to Feldens, P.; Schwarzer, K.; Sakuna, D.; Szczuciński, W.; Sompongchaiyakul, P. Sediment distribution on the inner continental shelf off Khao Lak (Thailand) after the 2004 Indian Ocean tsunami. <em>Earth, Planets and Space,</em> 2012, 64, 875-887; DOI:10.5047/eps.2011.09.001 and Sakuna-Schwartz, D.; Feldens, P.; Schwarzer, K.; Khokiattiwong, S.; Stattegger, K. Internal structure of event layers preserved on the Andaman Sea continental shelf, Thailand: tsunami vs. storm and flash-flood deposits. <em>Natural Hazards and Earth System Sciences,</em> 2015, 15, 1181-1199; DOI:10.5194/nhess-15-1181-201 and Feldens, P., Schwarzer K., Sakuna-Schwartz, D., Khokiattiwong, S. (in prep) Offshore geomorphological evolution in Phang Nga province (Thailand) during the Holocene: An example for a sediment starving shelf and references therein for further information on the dataset. The research was funded by Deutsche Forschungsgemeinschaft (DFG) grant No. SCHW 572/11-1 and National Research Council of Thailand (NRCT)
This dataset accompanies the manuscript "Spatial extent of trawl marks in the German Baltic Sea Basins based on bathymetric grids" by Peter Feldens, Inken Schulze, Elisabeth Seidel, Svenja Papenmeier, Aicha Naumann, Daniel Oesterwind, Jacob Geersen, and Mischa Schönke (Leibniz Institute for Baltic Sea Research Warnemünde / Thünen Institut für Ostseefischerei) submitted to the Journal "Anthropocene". The data support a study that uses a U-Net convolutional neural network to segment trawl marks from multibeam echo sounder (MBES) bathymetric slope grids across approximately 1,069 km² of seafloor in the south-western German Baltic Sea. Study areas include Mecklenburg Bay, the Arkona Basin, Kiel Bay, and the Fehmarn Belt. Bathymetric data were collected between 2016 and 2025 at 1 m resolution (interpolated to 0.25 m) and provided primarily by the German Federal Maritime Agency (BSH).Download links for the BSH data are given in the paper manuscript and are available from https://marine-data.de/ . The dataset is organized into four folders, which are here available as zip files:Training_Data/Contains the image patches and masks used to train the U-Net segmentation model, together with the trained model checkpoint. Images are 256×256 pixel PNG patches of slope data covering training areas in Mecklenburg Bay, Kiel Bay, Fehmarn Belt, and the Arkona Basin (German Baltic Sea). The dataset comprises 2,318 patches, each augmented 6 times (rotation, flips, brightness/contrast changes, elastic transformations, random cropping). Masks are binary: white pixels indicate trawl marks, black pixels indicate background. The model checkpoint (checkpoint_epoch13_mbes.pth) is for a U-Net with a ResNet-34 encoder (Segmentation Models PyTorch library), pre-trained on ImageNet. Test_Areas/Contains five independent test areas (Test1–Test5) not included in the training data, used for model validation. Each test area includes a slope GeoTIFF (.tif with .tfw world file and .prj projection file), a manually annotated binary mask GeoTIFF, and a shapefile (.shp, .shx, .dbf, .prj) defining the test area boundary. Test areas are distributed across Mecklenburg Bay, the southern Arkona Basin, Kiel Bay, and the Fehmarn Belt. Grid_Densities/Contains trawl mark density grids as GeoPackage files (.gpkg) for each investigation area: Mecklenburg Bay (MB), Arkona Basin areas 1 and 2 (ARK, ARK2), Kiel Bay (KB), and the Fehmarn Belt. Fehmarn Belt split into a reference area (REF; towards west) and a Marine Protected Area (MPA; towards east). For the MPA area, densities for 2025 are included as well, establishing a 2-year time series. Density values are computed within a regular 25 m × 25 m grid and normalized to 0–1, where 0 indicates no trawl marks and 1 indicates complete coverage. Polygons smaller than 100 m² were filtered to reduce noise as described in the paper. Time_Series/Contains slope GeoTIFFs for the Fehmarn Belt Marine Protected Area (FB-MPA) from 2024 and 2025, used to assess temporal changes in trawling intensity. The data were recorded on Elisabeth Mann Borgese cruises EMB345 (cruise report: doi:10.48433/cr_emb345) and EMB369 (cruise report: doi:10.48433/cr_emb369 ) in 2024 and 2025. These time-lapse datasets document seafloor regeneration timescales and trawl mark density in the two survey years.
