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Acoustic bottom detection and seabed classification in the German Bight, southern North Sea
Authors:Alexander Bartholomä
Institution:(1) Department of Marine Science, Senckenberg Institute, Südstrand 40, 26382 Wilhelmshaven, Germany
Abstract:To investigate the hydrodynamic activity of the seabed in the German Bight, underwater remote sensing was carried out over an area of 32 km2 located 20 km northeast of Helgoland island in the southern North Sea in January, May and August 2001. On the basis of acoustic seabed classification, six seabed types have been identified by the combined evaluation of side-scan sonar records, wave-shape analysis of echo-sounder data, and 100 grab samples. In five seabed types, the acoustic classes can be distinguished on the basis of sediment characteristics, comprising size components ranging from coarse pebbles to fine sand. The sixth seabed type corresponds to large pebbles and cobbles which are completely overgrown with brown algae. Statistically, the complex spatial patchiness of the six classes varied significantly in the course of the study period. During the winter period (January 2001), the study site was dominated by coarse material, except for a small area of finer sediment in the centre. With the onset of more moderate weather conditions in spring (May 2001), a general fining trend in sediment composition was observed, especially in the deeper western parts of the study area. In summer (August 2001), finer sediments still dominated but a slight increase in signal roughness suggests an overprint by coarser lag deposits and/or denser coverage by benthic organisms (e.g. Lanice conchilega) which then were found more frequently in grab samples, in association with finer sand. These findings demonstrate that the distribution of seafloor sediments and their benthic fauna in the deeper part of the German Bight region are controlled largely by seasonal changes in hydrodynamic conditions. These changes are reflected in correspondingly high variability in the complex patchiness of sediment distribution patterns, which would not have been adequately resolved by any standard sampling procedure.
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