Abstract
Manganese crusts (Mn-crusts) are a type of mineral deposit that exists on the surface of seamounts and guyots at depths of >800 m. We have developed a method to efficiently map their distribution using data collected by autonomous underwater vehicles and remotely operated vehicles. Volumetric measurements of Mn-crusts are made using a high-frequency subsurface sonar and a 3-D visual mapping instrument mounted on these vehicles. We developed an algorithm to estimate Mn-crust distribution by combining continuous subsurface thickness measurements with the exposed surface area identified in 3-D maps. This is applied to data collected from three expeditions at Takuyo Daigo seamount at depths of ∼1400 m. The transects add to ∼11 km in length with 12 510 m2 mapped. The results show that 52% of the surveyed area is covered by Mn-crusts with a mean thickness of 69.6 mm. The mean Mn-crust occurrence is 69.6 kg/m2 with a maximum of 204 kg/m2 in the mapped region. The results are consistent with estimates made from samples retrieved from the area, showing more detailed distribution patterns and having significantly lower uncertainty bounds for regional-scale Mn-crust inventory estimation.
Highlights
C OBALT-RICH manganese crusts (Mn-crusts) form on the slopes and shoulders of seamounts and guyots in geologically stable regions
While previous work analyzed small volumes of remotely operated vehicles (ROVs) data, the majority of data in this article have been collected using an autonomous underwater vehicles (AUVs), described in [26], with modifications made to the data acquisition system
As the AUV moves, these points will come in the illuminated region of the image; the RGB color values of the point can be identified based on the motion of the AUV
Summary
C OBALT-RICH manganese crusts (Mn-crusts) form on the slopes and shoulders of seamounts and guyots in geologically stable regions. This article presents a scalable way to determine the continuous mass distribution of Mn-crust over hectare-scale regions of the seafloor using visual and acoustic sensors This builds on the work described in [19], describing modifications to the data acquisition hardware, and presenting novel data processing methods that scale to the hectare-scale regions surveyed using this system. While previous work analyzed small volumes of ROV data, the majority of data in this article have been collected using an AUV, described in [26], with modifications made to the data acquisition system This includes real-time control of a double-gimbal system that orients the acoustic probe to be normal to the seafloor by analyzing the 3-D visual mapping data [27]. The advances in the sensor, platform, and novel algorithms described in this article allow estimates of Mn-crusts to be made over hectare-scale regions of the seafloor for the first time
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