3D seismic-derived bathymetry: a quantitative comparison with multibeam data

Power, Hannah E.; Clarke, Samantha

doi:10.1007/s00367-019-00596-w

Cited by 7 publications

(2 citation statements)

References 30 publications

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“…Due to the lack of regional watercolumn velocity profile, an average velocity of 1500 m/s value was obtained by averaging the nominal velocities specified in the navigation files of the surveys. The resulting velocity, while averaged from indirect sources, is comparable with values used in the literature to perform similar conversions (Mosher et al, 2006;Jibrin et al, 2013;Power and Clarke, 2019). The bin size of the reflection-derived bathymetry grids corresponds to the spacing of the seismic traces and is generally comprised between 12.5 m and 37.5 m.…”

Section: Data Processingsupporting

confidence: 67%

Towards a regional high-resolution bathymetry of the North West Shelf of Australia based on Sentinel-2 satellite images, 3D seismic surveys and historical datasets

Lebrec¹,

Paumard²,

O’Leary³

et al. 2021

Preprint

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Abstract. High-resolution bathymetry is a critical dataset for marine geoscientists. It can be used to characterize the seafloor and its marine habitats, to understand past sedimentary records and even to support the development of offshore engineering projects. Most methods to acquire bathymetry data are costly and can only be practically deployed on relatively small areas. It is therefore critical to develop cost-effective and advanced techniques to produce large-scale bathymetry datasets. This paper presents an integrated workflow that builds on satellites images and 3D seismic surveys, integrated with historical depth soundings, to generate a regional high-resolution digital elevation model. The method was applied to the southern half of Australia's North West Shelf and led to the creation of a new high-resolution bathymetry, with a resolution of 10 × 10 m in nearshore areas and 30 × 30 m elsewhere. The vertical and spatial accuracy of the datasets have been thoroughly assessed using open source Laser Airborne Depth Sounder (LADS) and Multi Beam Echo Sounder (MBES) surveys as a reference. The comparison of the datasets indicates that the seismic-derived bathymetry has a vertical accuracy better than 1 m + 2 % of the absolute water depths, while the satellite-derived bathymetry has a depth accuracy better than 1 m + 5 % of the absolute water depths. This dataset constitutes a significant improvement of the pre-existing regional 250 × 250 m grid and will support the onset of research projects on costal morphologies, marine habitats, archaeology, and sedimentology. All datasets used as inputs are publicly available and the method is fully integrated in Python scripts making it readily applicable elsewhere in Australia and around the world. The workflow as well as the resulting bathymetry have been independently reviewed and approved for release by a technical committee from the AusSeabed Community (Geoscience Australia). The regional digital elevation model as well as the underlying datasets can be accessed at: https://doi.org/10.26186/144600.

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Section: Data Processingsupporting

confidence: 67%

Towards a regional high-resolution bathymetry of the North West Shelf of Australia based on Sentinel-2 satellite images, 3D seismic surveys and historical datasets

Lebrec¹,

Paumard²,

O’Leary³

et al. 2021

Preprint

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“…Collier et al, 2006;Nixon et al, 2012;Sanderson et al, 2017;Westhead et al, 2018). In some cases, bathymetric models can be derived from 3D seismic data, but generally multi-beam phase-di erence methods are preferred (Power and Clarke, 2019). Remote mapping of seafloor lineaments complements land-based studies to help define the structural evolution of an area.…”

Section: Introductionmentioning

confidence: 99%

Application of the tilt derivative transform to bathymetric data for structural lineament mapping

Yeomans

Head

Lindsay

2021

Journal of Structural Geology

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High-resolution bathymetry surveys provide an opportunity to analyse local geological structure where onshore areas a ord limited exposure. Semi-automated lineament detection methods are necessary for areas of large coverage where a manual analysis would be subjective and timeconsuming. However, semi-automated approaches are dependent on e ective feature extraction methods to identify genuine lineaments. This study o ers solutions to common problems that can impede processing methods where sharp steps in the seafloor (e.g. palaeocoastlines) are present. Directional gradient, Sobel and Laplacian filters are explored as well as the hillshade and tilt derivative transform for feature extraction prior to applying an object-based image analysis lineament detection approach. The filtered datasets generally perform poorly with a marked improvement when using the hillshade transform. However, we find the azimuth-invariant tilt derivative, which incorporates a convolved vertical derivative, to be the most successful, identifying lineaments in a range of orientations and across a sharp step in the seafloor.

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