Objective
3 remoteote sensing methods for obtaining information on sea bottom topography have been investigated: passive optical bathymetry, sunglint observation and radar observation. Optical and microwave remotely sensed data as well as extensive in situ data, including a detailed bathymetric map, were gathered in a sand wave area off the Dutch coast. These data were compared with each other and with model predictions. The models are based on the current state of the art, with some extensions. Passive optical bathymetry has limited use above the North Sea because of its limited depth range. Sunglint observation of bottom topography is possible, but its practical applicability is limited by the requirement of low wind speeds and cloudless weather. Radar observation with an imaging radar operating at long wavelengths has the highest potential. The agreement between radar data and model predictions is not always good, due to lack of knowledge on the basic processes. However, in cases where there is good agreement, the imaging model can be inverted numerically to retrieve depth information from radar images.
PROJECT DESCRIPTION:
Numerical models for the dynamic behaviour of the sea floor are currently being developed. These models need information on the sea bottom topography for their calibration and validation. Traditional bathymetric surveys are time and cost consuming. Remote sensing methods, however, can give information about the sea bottom over large areas at relatively low costs. In this project the mapping of the sea bottom in shallow seas will be studied with microwave and optical sensors. It is known that wave-current interactions cause roughness variations at the sea surface which can be detected both with imaging radar and with optical sensors. The usability of this phenomenon will be investigated in terms of mapping accuracy and resolution by performing an experiment in a sand wave region off the Dutch coast. Comparison of the experimental results to predictions from numerical models based on existing knowledge of the imaging mechanisms will yield important information about our understanding of the processes involved. This understanding is crucial for the development of routine procedures in other projects.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
- engineering and technology electrical engineering, electronic engineering, information engineering electronic engineering sensors optical sensors
- natural sciences physical sciences astronomy planetary sciences planetary geology
- engineering and technology environmental engineering remote sensing
- engineering and technology electrical engineering, electronic engineering, information engineering information engineering telecommunications radio technology radar
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Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
Coordinator
2628 EB DELFT
Netherlands
The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.