Combining pixel and object based image analysis of ultra-high resolution multibeam bathymetry and backscatter for habitat mapping in shallow marine waters |
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| Authors: | Daniel Ierodiaconou " target="_blank">Alexandre C G Schimel David Kennedy Jacquomo Monk Grace Gaylard Mary Young " target="_blank">Markus Diesing Alex Rattray |
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| Institution: | 1.School of Life and Environmental Sciences,Deakin University, Centre for Integrative Ecology (Warrnambool Campus),Warrnambool,Australia;2.National Institute of Water and Atmospheric Research (NIWA), Taihoro Nukurangi,Wellington,New Zealand;3.School of Geography,The University of Melbourne,Parkville,Australia;4.Institute of Marine and Antarctic Studies,University of Tasmania,Hobart,Australia;5.Geological Survey of Norway,Trondheim,Norway;6.Centre for Environment,Fisheries and Aquaculture Science,Lowestoft,UK |
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| Abstract: | Habitat mapping data are increasingly being recognised for their importance in underpinning marine spatial planning. The ability to collect ultra-high resolution (cm) multibeam echosounder (MBES) data in shallow waters has facilitated understanding of the fine-scale distribution of benthic habitats in these areas that are often prone to human disturbance. Developing quantitative and objective approaches to integrate MBES data with ground observations for predictive modelling is essential for ensuring repeatability and providing confidence measures for habitat mapping products. Whilst supervised classification approaches are becoming more common, users are often faced with a decision whether to implement a pixel based (PB) or an object based (OB) image analysis approach, with often limited understanding of the potential influence of that decision on final map products and relative importance of data inputs to patterns observed. In this study, we apply an ensemble learning approach capable of integrating PB and OB Image Analysis from ultra-high resolution MBES bathymetry and backscatter data for mapping benthic habitats in Refuge Cove, a temperate coastal embayment in south-east Australia. We demonstrate the relative importance of PB and OB seafloor derivatives for the five broad benthic habitats that dominate the site. We found that OB and PB approaches performed well with differences in classification accuracy but not discernible statistically. However, a model incorporating elements of both approaches proved to be significantly more accurate than OB or PB methods alone and demonstrate the benefits of using MBES bathymetry and backscatter combined for class discrimination. |
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