Marine & Environmental Sciences Faculty Articles
A New Method for Ecological Surveying of the Abyss Using Autonomous Underwater Vehicle Photography
ORCID
0000-0002-8296-4780
ResearcherID
J-3058-2014
Document Type
Article
Publication Title
Limnology and Oceanography: Methods
ISSN
1541-5856
Publication Date
11-2014
Abstract
The extent and speed of marine environmental mapping is increasing quickly with technological advances, particularly with optical imaging from autonomous underwater vehicles (AUVs). This contribution describes a new deep-sea digital still camera system that takes high-frequency (>1 Hz) color photographs of the seafloor, suitable for detailed biological and habitat assessment, and the means of efficient processing of this mass imagery, to allow assessment across a wide range of spatial scales from that of individual megabenthic organisms to landscape scales (>100 km2). As part of the Autonomous Ecological Surveying of the Abyss (AESA) project, the AUV Autosub6000 obtained > 150,000 seafloor images (~160 km total transect length) to investigate the distribution of megafauna on the Porcupine Abyssal Plain (4850 m; NE Atlantic). An automated workflow for image processing was developed that corrected nonuniform illumination and color, geo-referenced the photographs, and produced 10-image mosaics ('tiles,' each representing a continuous strip of 15-20 m2 of seafloor), with overlap between consecutive images removed. These tiles were then manually annotated to generate biological data. This method was highly advantageous compared with alternative techniques, greatly increasing the rate of image acquisition and providing a 10-50 fold increase in accuracy in comparison to trawling. The method also offers more precise density and biodiversity estimates [Coefficient of variation (CV) < 10%] than alternative techniques, with a 2-fold improvement in density estimate precision compared with the WASP towed camera system. Ultimately, this novel system is expected to make valuable contributions to understanding human impact in the deep ocean.
DOI
10.4319/lom.2014.12.795
Volume
12
Issue
11
First Page
795
Last Page
809
Additional Comments
Autonomous Ecological Surveying of the Abyss project #s: NE/H021787/1, NE/H023569/1
NSUWorks Citation
Kirsty J. Morris, B. J. Bett, J. M. Durden, Veerle A. I. Huvenne, Rosanna Milligan, Daniel O. B. Jones, Stephen McPhail, Katleen Robert, David M. Bailey, and H. A. Ruhl. 2014. A New Method for Ecological Surveying of the Abyss Using Autonomous Underwater Vehicle Photography .Limnology and Oceanography: Methods , (11) : 795 -809. https://nsuworks.nova.edu/occ_facarticles/869.
Comments
©2014, by the American Society of Limnology and Oceanography, Inc.