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      Multi-Scale Measures of Rugosity, Slope and Aspect from Benthic Stereo Image Reconstructions

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          Abstract

          This paper demonstrates how multi-scale measures of rugosity, slope and aspect can be derived from fine-scale bathymetric reconstructions created from geo-referenced stereo imagery. We generate three-dimensional reconstructions over large spatial scales using data collected by Autonomous Underwater Vehicles (AUVs), Remotely Operated Vehicles (ROVs), manned submersibles and diver-held imaging systems. We propose a new method for calculating rugosity in a Delaunay triangulated surface mesh by projecting areas onto the plane of best fit using Principal Component Analysis (PCA). Slope and aspect can be calculated with very little extra effort, and fitting a plane serves to decouple rugosity from slope. We compare the results of the virtual terrain complexity calculations with experimental results using conventional in-situ measurement methods. We show that performing calculations over a digital terrain reconstruction is more flexible, robust and easily repeatable. In addition, the method is non-contact and provides much less environmental impact compared to traditional survey techniques. For diver-based surveys, the time underwater needed to collect rugosity data is significantly reduced and, being a technique based on images, it is possible to use robotic platforms that can operate beyond diver depths. Measurements can be calculated exhaustively at multiple scales for surveys with tens of thousands of images covering thousands of square metres. The technique is demonstrated on data gathered by a diver-rig and an AUV, on small single-transect surveys and on a larger, dense survey that covers over . Stereo images provide 3D structure as well as visual appearance, which could potentially feed into automated classification techniques. Our multi-scale rugosity, slope and aspect measures have already been adopted in a number of marine science studies. This paper presents a detailed description of the method and thoroughly validates it against traditional in-situ measurements.

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          Structural complexity in mussel beds: the fractal geometry of surface topography.

          Seafloor topographic complexity is ecologically important because it provides habitat structure and alters boundary-layer flow over the bottom. Despite its importance, there is little agreement on how to define and measure surface complexity. The purpose of this investigation was to utilize fractal geometry of vertical cross-section profiles to characterize the surface topography of the soft-bottom mussel bed (Mytilus edulis L.) at Bob's Cove, ME, USA. Mussels there have been shown previously to have spatially ordered fractal characteristics in the horizontal plane. Two hypotheses were tested. The first was that the bed surface is fractal over the spatial scale of 1.44-200 mm, with fractal dimension less than or equal to 1.26, the value for the Koch curve, our model for bed profiles. The second was that bed surface topography (i.e., in vertical profile) is less complex than the mussel bed spatial pattern (i.e., aerial view in the horizontal plane). Both hypotheses were supported. Cross-sections of plaster casts of the bed produced 88 surface profiles, all of which were fractal over the entire spatial scale of more two orders of magnitude employed in the analysis. Fractal dimension values (D) for individual profiles ranged from 1.031 to 1.310. Fractal dimensions of entire casts ranged up to mean (1.242+/-0.046) and median (1.251) values similar to 1.26, the theoretical value of the Koch curve. The bed surface was less complex than the bed spatial pattern because every profile had D<1.36, the smallest value previously obtained from aerial views of the bed. The investigation demonstrated for the first time that surface topography of a soft-bottom mussel bed was fractal at a spatial scale relevant to hydrodynamic processes and habitat structure important for benthic organisms. The technique of using cross-section profiles from casts of the bed surface avoided possible underestimates of fractal dimension that can result from other profiling methods reported in the literature. The results demonstrate that fractal dimension can be useful in the analysis of habitat space and water flow over any irregular seafloor surface because it incorporates the size, shape, and scale of roughness elements into a simple, numerical metric.
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            Author and article information

            Contributors
            Role: Editor
            Journal
            PLoS One
            PLoS ONE
            plos
            plosone
            PLoS ONE
            Public Library of Science (San Francisco, USA )
            1932-6203
            2012
            12 December 2012
            : 7
            : 12
            : e50440
            Affiliations
            [1]Australian Centre for Field Robotics, University of Sydney, Australia
            The Australian National University, Australia
            Author notes

            Competing Interests: The authors have declared that no competing interests exist.

            Conceived and designed the experiments: AF OP SBW. Performed the experiments: AF OP. Analyzed the data: AF OP MJR. Contributed reagents/materials/analysis tools: AF OP SBW MJR. Wrote the paper: AF. Research supervisors: SBW OP.

            Article
            PONE-D-12-23052
            10.1371/journal.pone.0050440
            3520945
            23251370
            f018c952-410d-4dc6-928d-b5a19af5f3a7
            Copyright @ 2012

            This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

            History
            : 1 August 2012
            : 22 October 2012
            Page count
            Pages: 14
            Funding
            This work is supported by the Australian Research Council (ARC) Centre of Excellence programme, funded by the ARC and the New South Wales State Government and the Integrated Marine Observing System through the DIISR National Collaborative Research Infrastructure Scheme. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
            Categories
            Research Article
            Earth Sciences
            Environmental Sciences
            Environmental Geology
            Limnology
            Physical Limnology
            Marine and Aquatic Sciences
            Marine Biology
            Marine Ecology
            Marine Monitoring
            Engineering
            Marine Engineering
            Mechanical Engineering
            Robotics
            Signal Processing
            Image Processing
            Software Engineering
            Software Tools

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