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

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Christopher Mark Yeomans , Matthew Head, Jordan James Lindsay


High-resolution bathymetry surveys provide an opportunity to analyse local geological structure where onshore areas afford limited exposure. Semi-automated lineament detection methods are necessary for areas of large coverage where a manual analysis would be subjective and time-consuming. However, semi-automated approaches are dependent on effective feature extraction methods to identify genuine lineaments. This study offers 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.



Computer Sciences, Earth Sciences, Geomorphology, Oceanography, Oceanography and Atmospheric Sciences and Meteorology, Physical Sciences and Mathematics, Tectonics and Structure


structural geology, bathymetry, lineament detection, OBIA, tilt derivative


Published: 2020-07-08 10:39

Last Updated: 2021-03-26 16:25

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CC BY Attribution 4.0 International

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