133 publications from this institution
<p>The identification of marine cobbles and boulders (stones) based on acoustic remote sensing is important for the detection, delineation and for an ecological assessment of important seafloor habitats. Due to the large areas involved and the required high-resolution data, a manual interpretation is not feasible. In recent years, automated methods for stone detection were developed. However, these developments were only applied in comparatively small proof of concept areas, and a common barrier to practical implementation by authorities is the required upscaling. This case study aims to apply automated methods for boulder detection based on convolutional neural networks to larger areas, by identifying and validating boulder densities over several hundred km<sup>2 </sup>in the western Baltic Sea in acoustic backscatter data and derived datasets. The use of distributed training sites of less than 0.5 km<sup>2  </sup>in size is proposed to improve the model capacity to adapt to variations of boulder appearance in remote sensing data related to local geological variation and survey conditions. Distributed validation sites of similar size are suggested to provide quality control during reprocessing with adapted models. Current limitations for the automated identification of individual boulders in backscatter data are demonstrated, which can be caused by survey geometry, data quality or obstacles and seafloor with similar acoustic characteristics.</p>
Dataset for the study "Can Anthipatella wollastoni be detected in Multibeam Echo Sounder multi-detect data?", currently under review at Frontiers in Remote Sensing. The files include: Photos.zip: GoPro Photos with ground truthing of two ridges with the occurrence of Black Corals. Photos have been geo-located using the coordinates of the onboard Multibeam System and correcting a time offset. Refer to the paper for details. Sound velocities: Sound velocity casts using a Base-X shallow water profiler used to correct the multibeam echo sounder. MD_manual_edit: Shape file including the position of Multi-Detects after the manual cleaning. The MD point objects have been joined with information from the local bathymetry and slope. Note that associated intensity values are erroneous due to a bug in the recording MBES firmware. MBES: Includes Norbit s7k (version 3) raw files of the multibeam echo sounder data (Norbit iwbms-e, Serial number #12). Files in folders with "MD" were used for the Multi-Detect study. Files with "MFE" include multifrequency data. We failed to locate the black corals in multi-frequency backscatter data. Multi-detect data were recorded with a swath width of 100° split into 512 beams. The multifrequency data contains 190 and 370 kHz information. Spreading correction was set to 40, absorption set to 107 dB/km (calculated for the 390 kHz frequency with a mean water temperature of 16°C, a salinity of 35. Actual temperature according to diver information was 24°C at the surface, 23° until 50 m and 21° until 80 m). All offsets have been accounted for during the survey. The data is located using an RTK correction (refer to paper for further details).
