Methodologies for quantitatively characterising seabed substrate from acoustic & optical data  

Authors / CoAuthors

Siwabessy, P.J.W. | Daniell, J.J. | Li, J. | Huang, Z. | Nichol, S.L.

Abstract

Geoscience Australia (GA) has an active research interest in using multibeam bathymetry, backscatter data and their derivatives together with geophysical data, sediment samples, biological specimens and underwater video/still footage to create seabed habitat maps. This allows GA to provide spatial information about the physical and biological character of the seabed to support management of the marine estate. The main advantage of using multibeam systems over other techniques is that they provide spatially continuous maps that can be used to relate to physical samples and video observations. Here we present results of a study that aims to reliably and repeatedly delineate hard and soft seabed substrates using bathymetry, backscatter and their derivatives. Two independent approaches to the analysis of multibeam data are tested: (i) a two-stage classification-based clustering method, based solely on acoustic backscatter angular response curves, is used to derive a substrate type map. (ii) a prediction-based classification is produced using the Random Forest method based on bathymetry, backscatter data and their derivatives, with support from video and sediment data. Data for the analysis were collected by Geoscience Australia and the Australian Institute of Marine Science on the Van Dieman Rise in the Timor Sea using RV Solander. The mapped area is characterised by carbonate banks, ridges and terraces that form hardground with patchy sediment cover, and valleys and plains covered by muddy sediment. Results from the clustering method of hard and soft seabed types yielded classification accuracies of 78 - 87% when evaluated against seabed types as observed in underwater video. The prediction-based approach achieved a classification accuracy of 92% based on 10-fold cross-validation. These results are consistent with the current state of knowledge on geoacoustics. Patterns associated with geomorphic facies and biological categories are also observed. These results demonstrate the utility of acoustic data to broadly and objectively characterise the seabed substrate and thereby inform our understanding of the distribution of key habitat types.

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nonGeographicDataset

eCat Id

75497

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Keywords

• External PublicationAbstract

( Theme )

• backscatter

( Theme )

• bathymetry

( Theme )

• mapping

( Theme )

• multibeam

( Theme )

• numerical modelling

( Theme )

• marine

Australian and New Zealand Standard Research Classification (ANZSRC)

• Earth Sciences

• Published_Internal

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2013-03-04T00:00:00

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Australian Government Security ClassificationSystem    

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Creative Commons Attribution 4.0 International Licence    

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geoscientificInformation

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