Underwater Hyperspectral Imaging Using a Stationary Platform in the Trans-Atlantic Geotraverse Hydrothermal Field

Dumke, Ines; Ludvigsen, Martin; Ellefmo, Steinar L.; Soreide, Fredrik; Johnsen, Geir; Murton, Bramley J. ORCID: https://orcid.org/0000-0003-1522-1191. 2018 Underwater Hyperspectral Imaging Using a Stationary Platform in the Trans-Atlantic Geotraverse Hydrothermal Field. IEEE Transactions on Geoscience and Remote Sensing, 57 (5). 2947-2962. 10.1109/TGRS.2018.2878923

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Official URL: http://dx.doi.org/10.1109/TGRS.2018.2878923

Abstract/Summary

Underwater hyperspectral imaging is a relatively new method for characterizing seafloor composition. To date, it has been deployed from moving underwater vehicles, such as remotely operated vehicles and autonomous underwater vehicles. While moving vehicles allow relatively rapid surveying of several 10-1000 m², they are subjected to short-term variations in vehicle attitude that often compromise image acquisition and quality. In this study, we tested a stationary platform that was landed on the seabed and used an underwater hyperspectral imager (UHI) on a vertical swinging bracket. The imaged seafloor areas have dimensions of 2.3 m x 1 m and are characterized by very stable UHI data of high spatial resolution. The study area was the Trans-Atlantic Geotraverse hydrothermal field at the Mid-Atlantic Ridge (26° N) in water depths of 3530-3660 m. UHI data were acquired a 12 stations on an active and an inactive hydrothermal sulfide mound. Based on supervised classification, 24 spectrally different seafloor materials were detected, including hydrothermal and non-hydrothermal materials, and benthic fauna. The results show that the UHI data are able to spectrally distinguish different types of surface materials and benthic fauna in hydrothermal areas, and may therefore represent a promising tool for high-resolution seafloor exploration in potential future deep-sea mining areas.

Item Type:	Publication - Article
Digital Object Identifier (DOI):	10.1109/TGRS.2018.2878923
ISSN:	0196-2892
Date made live:	23 Jan 2019 15:41 +0 (UTC)
URI:	https://nora.nerc.ac.uk/id/eprint/522085

Item Type:

Publication - Article

Digital Object Identifier (DOI):

10.1109/TGRS.2018.2878923

ISSN:

0196-2892

Date made live:

23 Jan 2019 15:41 +0 (UTC)

URI:

https://nora.nerc.ac.uk/id/eprint/522085