Techniques for Classifying Seabed Morphology and Composition on a Subtropical-Temperate Continental Shelf

• Published in: Geosciences (Basel) Vol. 9; no. 3; p. 141
• Main Authors: Linklater, Michelle, Ingleton, Timothy C., Kinsela, Michael A., Morris, Bradley D., Allen, Katie M., Sutherland, Michael D., Hanslow, David J.
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01-03-2019
• Subjects: Automation; Backscatter; Backscattering; Baseline studies; Bathymetry; Biodiversity; Cell size; Classification; Classification schemes; Coastal zone management; Composition; Continental shelves; Data; DEMs; Dictionaries; Earth science; Echo sounding; Echosounders; feature classification; Geodiversity; Geomorphology; geomorphometry; habitat mapping; High resolution; Landforms; Lidar; marine LiDAR; Morphology; multibeam echosounder; Ocean floor; Reflectance; Resolution; Risk assessment; substrate; Substrates; Australia
• ISSN: 2076-3263; 2076-3263
• DOI: 10.3390/geosciences9030141

In 2017, the New South Wales (NSW) Office of Environment and Heritage (OEH) initiated a state-wide mapping program, SeaBed NSW, which systematically acquires high-resolution (2–5 m cell size) multibeam echosounder (MBES) and marine LiDAR data along more than 2000 km of the subtropical-to-temperate southeast Australian continental shelf. This program considerably expands upon existing efforts by OEH to date, which have mapped approximately 15% of NSW waters with these technologies. The delivery of high volumes of new data, together with the vast repository of existing data, highlights the need for a standardised, automated approach to classify seabed data. Here we present a methodological approach with new procedures to semi-automate the classification of high-resolution bathymetry and intensity (backscatter and reflectivity) data into a suite of data products including classifications of seabed morphology (landforms) and composition (substrates, habitats, geomorphology). These methodologies are applied to two case study areas representing newer (Wollongong, NSW) and older (South Solitary Islands, NSW) MBES datasets to assess the transferability of classification techniques across input data of varied quality. The suite of seabed classifications produced by this study provide fundamental baseline data on seabed shape, complexity, and composition which will inform regional risk assessments and provide insights into biodiversity and geodiversity.