Identification of manganese crusts in 3D visual reconstructions to filter geo-registered acoustic sub-surface measurements

Neettiyath, Umesh; Sato, Terukazu; Sangekar, Mehul; Bodenmann, Adrian; Thornton, Blair; Ura, Tamaki; Asada, Akira

doi:10.23919/oceans.2015.7404471

Cited by 9 publications

(4 citation statements)

References 2 publications

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“…However, it can be difficult to determine if acoustic signals are of Mn-crust from their acoustic signature alone. For this, visual methods can be effective if reliable automatic classification methods can be developed [20]- [25].…”

Section: Table I Specifications Of the Platform (Auv Boss-a)mentioning

confidence: 99%

Deep-Sea Robotic Survey and Data Processing Methods for Regional-Scale Estimation of Manganese Crust Distribution

Neettiyath

Thornton

Sangekar

et al. 2021

IEEE J. Oceanic Eng.

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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 m 2 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/m 2 with a maximum of 204 kg/m 2 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.

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Section: Table I Specifications Of the Platform (Auv Boss-a)mentioning

confidence: 99%

Deep-Sea Robotic Survey and Data Processing Methods for Regional-Scale Estimation of Manganese Crust Distribution

Neettiyath

Thornton

Sangekar

et al. 2021

IEEE J. Oceanic Eng.

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“…Crusts form at water depths of about 400 to 4000 m, with the thickest and most Co-rich crusts occurring at depths of about 800 to 2500 m, which may vary on a regional scale. Gravity processes, sediment cover, submerged and emergent reefs, and currents control the distribution and thickness of crusts on seamounts [1,2,3,4].…”

Section: Introductionmentioning

confidence: 99%

“…From the aspect of techniques, mapping and quantitatively estimating the volumetric distribution of these deposits needs to be done first, which is of interest to geologists, oceanographers, and industry [3]. As a key step of the assessment, the measuring of the thickness can be performed by various methods.…”

Section: Introductionmentioning

confidence: 99%

“…The acoustic probe is developed based on the parametric array principle, which has a performance of better beam directivity, narrower beamwidth, better resolution, and sidelobes compared with traditional acoustic arrays [10,11,12]. The acoustic probe employs a high-power acoustic pulse, whose sub-surface reflections are recorded [3]. The thickness can be simply determined by the time delay between the top and bottom reflection if the sound velocity within the CRCs is assumed to be known.…”

Section: Introductionmentioning

confidence: 99%

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China’s First Demonstration of Cobalt-rich Manganese Crust Thickness Measurement in the Western Pacific with a Parametric Acoustic Probe

Hong

Feng

Huang

et al. 2019

Sensors

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Cobalt-rich manganese crusts (CRCs) are important as a potential mineral source that could occur throughout the Pacific on seamounts, ridges, and plateaus. We built a prototype parametric acoustic probe to complete the task of in-situ thickness measurements to estimate the volumetric distribution of deep-sea mineral. The prototype is designed with dual-channels for receiving the primary and secondary signal, which lays a foundation for improving the thickness extraction algorithm. Considering that the signal quality is degraded by the system interference and ambient noise, some improvements to the algorithm are proposed by including the wavelet-based envelope extraction method and the adaptive estimation strategy based on the dual-channel information. Additionally, wavelet regression is applied to reduce the measuring noise assuming that the CRCs have local thickness invariability. The algorithm is suitable for the CRCs with the structure of the multilayers at the top surface and one single layer at the bottom surface. A laboratory experiment is performed to validate the effectiveness of the algorithm. The experiments carried out on the China Ocean 51th voyage in the Western Pacific Ocean on Aug 30, 2018, are described and the data obtained by using the sit-on-bottom stationary measurement are processed to validate the design of the prototype.

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A multi-proxy approach for delineation of ferromanganese mineralization from the West Sewell Ridge, Andaman Sea

Pillai

Varghese

Prasad

2022

Marine Georesources & Geotechnology

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Identification of manganese crusts in 3D visual reconstructions to filter geo-registered acoustic sub-surface measurements

Cited by 9 publications

References 2 publications

Deep-Sea Robotic Survey and Data Processing Methods for Regional-Scale Estimation of Manganese Crust Distribution

Deep-Sea Robotic Survey and Data Processing Methods for Regional-Scale Estimation of Manganese Crust Distribution

China’s First Demonstration of Cobalt-rich Manganese Crust Thickness Measurement in the Western Pacific with a Parametric Acoustic Probe

A multi-proxy approach for delineation of ferromanganese mineralization from the West Sewell Ridge, Andaman Sea

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