9:30 AM - 9:45 AM
[SCG48-03] Characterization of the ferromanganese nodules distribution around Minamitorishima Island based on an analysis of the acoustic backscatter intensity and seafloor images

Keywords:critical metals, ferromanganese nodules, acoustic survey, peak-fitting analysis, Minamitorishima Island, seafloor mineral resources
In our previous study [1], a new method was established to estimate the distribution of ferromanganese nodules very efficiently using the acoustic backscatter intensity of the seafloor. In the study, acoustic backscatter intensity data obtained by a multi-narrow beam echo sounder during seven cruises were processed and integrated into a unified data set. Analysis of the histograms of the integrated data yielded several threshold values corresponding to the change of distributional pattern of ferromanganese nodules in the study area. Sasaki et al. (2023 JpGU) [2] further discussed how the acoustic data reflects the characteristics of the seafloor surface by separating multiple peaks that appeared in the histogram of the combined data.
To consider the correspondence between the backscatter intensities and seafloor features more in detail, we performed a peak-fitting analysis using the Expectation-Maximization (EM) algorithm [3] on histograms of acoustic backscatter intensities of each cruise before coupling, as well as the previously examined coupled intensity dataset, around Minamitorishima Island. The backscatter intensity histograms were decomposed into multiple peaks, suggesting detection of different seafloor features in each dataset. Moreover, to clarify how these peaks correspond to the actual seafloor facies, the seafloor images observed by the SHINKAI 6500 was analyzed using a machine-learning-based object detection model. In the presentation, we will discuss the relationship between each peak and the distribution patterns of ferromanganese nodules on the seafloor around Minamitorishima Island.
[1] Machida et al. Mar. Georesour. & Geotec. 39(3), 267-279 (2021).
[2] Sasaki et al. JpGU2023, SCG52-P18 (2023).
[3] Matsumura et al. Sci. Technol. Adv. Mat. 20, 733–745 (2019).