Continental Shelf Research, Published online 17 May 2014
By Markus Diesing, Sophie L. Green, David Stephens, R. Murray Lark,
Heather A. Stewart, and Dayton Dove
“Marine spatial planning and conservation need underpinning with sufficiently detailed and accurate seabed substrate and habitat maps. Although multibeam echosounders enable us to map the seabed with high resolution and spatial accuracy, there is still a lack of fit-for-purpose seabed maps. This is due to the high costs involved in carrying out systematic seabed mapping programmes and the fact that the development of validated, repeatable, quantitative and objective methods of swath acoustic data interpretation is still in its infancy. We compared a wide spectrum of approaches including manual interpretation, geostatistics, object-based image analysis and machine-learning to gain further insights into the accuracy and comparability of acoustic data interpretation approaches based on multibeam echosounder data (bathymetry, backscatter and derivatives) and seabed samples with the aim to derive seabed substrate maps. Sample data were split into a training and validation data set to allow us to carry out an accuracy assessment.
Results of the map comparisons: A—manual-OBIA; B—manual-Random Forest; C—manual-geostatistics; D—OBIA-Random Forest; E—OBIA-geostatistics; F—Random Forest geostatistics. Green indicates agreement and red indicates disagreement.(For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)
“Overall thematic classification accuracy ranged from 67% to 76% and Cohen
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By Markus Diesing, Sophie L. Green, David Stephens, R. Murray Lark,
Heather A. Stewart, and Dayton Dove
“Marine spatial planning and conservation need underpinning with sufficiently detailed and accurate seabed substrate and habitat maps. Although multibeam echosounders enable us to map the seabed with high resolution and spatial accuracy, there is still a lack of fit-for-purpose seabed maps. This is due to the high costs involved in carrying out systematic seabed mapping programmes and the fact that the development of validated, repeatable, quantitative and objective methods of swath acoustic data interpretation is still in its infancy. We compared a wide spectrum of approaches including manual interpretation, geostatistics, object-based image analysis and machine-learning to gain further insights into the accuracy and comparability of acoustic data interpretation approaches based on multibeam echosounder data (bathymetry, backscatter and derivatives) and seabed samples with the aim to derive seabed substrate maps. Sample data were split into a training and validation data set to allow us to carry out an accuracy assessment.
Results of the map comparisons: A—manual-OBIA; B—manual-Random Forest; C—manual-geostatistics; D—OBIA-Random Forest; E—OBIA-geostatistics; F—Random Forest geostatistics. Green indicates agreement and red indicates disagreement.(For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)“Overall thematic classification accuracy ranged from 67% to 76% and Cohen
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