<div>The Otway, Gippsland Basins and Bass Strait 3D seismic derived bathymetry compilation (20220007C) was produced by the University of Western Australia, Norwegian Geotechnical Institute and UniLasalle in collaboration with Geoscience Australia through the AusSeabed initiative. The compilation integrates 87 bathymetry grids derived from available and workable 3D seismic datasets into a 30 m resolution 32-bit GeoTIFF, including both reflection and navigation derived data. A detailed workflow is described in: Lebrec, U., Paumard, V., O'Leary, M. J., and Lang, S. C., 2021, 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: Earth System Science Data, v. 13, no. 11, p. 5191-5212 https://doi.org/10.5194/essd-13-5191-2021, 2021.</div><div><br></div><div>This dataset is not to be used for navigational purposes.</div><div><br></div>

Seabed morphology maps and data are critical for knowledge-building and best practice management of marine environments. To facilitate objective and repeatable production of these maps, we have developed a number of semi-automated, rule-based GIS tools (Geoscience Australia’s Semi-automated Morphological Mapping Tools (GA-SaMMT)) to operationalise the mapping of a common set of bathymetric high and bathymetric low seabed Morphological Features. The tools have a graphical user interface and were developed using Python scripts under the widely-used proprietary ArcGIS Pro platform. The utility of these tools was tested across nine case study areas that represent a diverse range of complex bathymetric and physiographic settings. Overall, the mapping results are found to be more consistent than manual mapping and allow for capture of greater detail across a range of spatial scales. The mapping results demonstrate a number of advantages of GA-SaMMT, including: 1) requirement of only a bathymetry grid as sole data input; 2) flexibility to apply domain knowledge to user-defined tool parameters or to use default parameter settings; 3) repeatability and consistency in the mapping outputs when using a consistent set of tool parameters (user defined or default); 4) high-degree of objectivity; and 5) efficiency in mapping a large number (thousands) of seabed morphology features in a single dataset. In addition, GA-SaMMT generates 34 and 46 metrics to comprehensively quantify the characteristics of individual seabed bathymetric high and low features, respectively. Our results indicate that attribute metrics are invaluable in the interpretation and modelling of mapped Morphology Features and provide insights into their formative processes and habitat potential for marine communities. Appeared in Front. Mar. Sci., 28 August 2023, Sec. Ocean Observation, Volume 10.

<div>Maps of seabed geomorphology derived from bathymetry data provide foundational information that is used to support the sustainable use of the marine environment across a range of activities that contribute to the Blue Economy. The global recognition of the value of the Blue Economy and several key global initiatives, notably the Seabed 2030 project to map the global ocean and the United Nations Decade of Ocean Science for Sustainable Development, are driving the proliferation and open dissemination of these data and derived map products. To effectively support these global efforts, geomorphic characterisation of the seabed requires standardized multi-scalar and interjurisdictional approaches that can be applied locally, regionally and internationally. This document describes and illustrates a geomorphic lexicon for the full range of coastal to deep ocean geomorphic Settings and related Processes that drive the formation, modification and preservation of geomorphic units on the seabed. Terms and Settings/Processes have been selected from the literature and structured to balance established terminology with the need for consistency between the range of geomorphic Settings. This document also presents a glossary of the terms and identifies the insights that can be gained by mapping each unit type, from an applied perspective.</div> <b>Citation:</b> Nanson, Rachel, Arosio, Riccardo, Gafeira, Joana, McNeil, Mardi, Dove, Dayton, Bjarnadóttir, Lilja, Dolan, Margaret, Guinan, Janine, Post, Alix, Webb, John, & Nichol, Scott. (2023). <i>A two-part seabed geomorphology classification scheme; Part 2: Geomorphology classification framework and glossary (Version 1.0) (1.0).</i> Zenodo. https://doi.org/10.5281/zenodo.7804019