4.6 Article

Ocean Floor Observation and Bathymetry System (OFOBS): A New Towed Camera/Sonar System for Deep-Sea Habitat Surveys

期刊

IEEE JOURNAL OF OCEANIC ENGINEERING
卷 44, 期 1, 页码 87-99

出版社

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/JOE.2018.2794095

关键词

Acoustic devices; high-resolution imaging; oceanographic techniques; terrain mapping; underwater equipment; underwater technology

资金

  1. Managing Impacts of Deep-seA reSource exploitation project - European Union [603418]
  2. ERC AdvG Project Abyss [AWI_PS101_01, 294757]

向作者/读者索取更多资源

Towed camera systems are commonly used to collect photo and video images of the deep seafloor for a wide variety of purposes, from pure exploratory research to the development of management plans. Ongoing technological developments are increasing the quantity and quality of data collected from the deep seafloor. Despite these improvements, the area of seafloor, which towed systems can survey, optically remains limited by the rapid attenuation of visible wavelengths within water. We present an overview of a new towed camera platform integrating additional acoustical devices: the ocean floor observation and bathymetry system (OFOBS). The towed system maintains continuous direct communication via fiber optic cable with a support vessel, operational at depths up to 6000 m. In addition to collecting seafloor photo and video data, OFOBS gathers sidescan data over a 100-m swath width. OFOBS functionality is further augmented by a forward looking sonar, used to aid in hazard avoidance and real-time course correction. Data collected during the first field deployments of OFOBS, at a range of seamounts on the Langseth Ridge/Gakkel Ridge intersection (86 degrees N, 61 degrees E) in the high Arctic in September 2016, are presented to demonstrate the functionality of the system. Collected from a location with near continuous ice cover, this explanatory data set highlights the advantages of the system for deep-sea survey work in environments currently difficult to access for the majority of subsurface research platforms.

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