Slope topography is known to control the spatial distribution of deposits on intraplate seamounts; however, relatively little is known about how slope topography changes constrain those depositional patterns. In this study, we analyse data on four lithotypes found on seamount slopes, including colloidal chemical deposits comprising mainly cobalt-rich crusts, and examine the relationships between the spatial distribution of these lithotypes and current slope topography. We use these relationships to discuss depositional patterns constrained by slope topography changes. Some depositional units in drill core samples are interpreted to have resulted from past topographic changes that created the current slope topography. Two or more types of deposits that accumulated at the same location implies that the slope topography changed over time and that the depositional patterns on seamount slopes are constrained by changes in slope topography.

The evaluation of mineral resources on seamounts by geostatistics faces two key challenges. First, the conventional distance/orientation- and the simple distance-based variogram functions used are ineffective at expressing the spatial self-correlation and continuity of cobalt-rich crust thicknesses on seamounts. Second, the sampling stations used for a single seamount are generally very sparsely distributed because of the high survey costs, which results in an insufficient number of information points for variogram fitting. Here, we present an alternative geostatistical method that uses distance/gradient- and distance/relative-depth-based variograms to process data collected from several neighboring seamounts, allowing the variogram fitting. The application example reported for the Magellan seamounts demonstrates the suitability of the method for evaluating the mineral resources of cobalt-rich crusts. The method could be effective also for the analysis of surface data obtained from mountain slopes on land (e.g., soil).

The deep-sea camera is the most intuitive and effective detection tool for seabed investigation, and the accuracy of camera positioning can ensure its data value. A bundled ultra-short baseline (USBL) positioning system is generally employed to realize the spatial positioning of an underwater camera. The influence of the underwater acoustic environment and other factors cause USBL positioning data to become unstable, leading to abnormalities, or missing data, which creates difficulties for camera positioning. In order to solve the problem, this paper selects the seabed camera data of the “XunMei” mineralization area acquired from the China south Atlantic voyage. Moreover, the USBL positioning data, combined with high-precision terrain, bathymetry, and ship-borne GPS positioning data, were analyzed and mined comprehensively. In order to eliminate the abnormal data, a four-dimensional anomaly culling model of USBL positioning data is established based on the time and space scales through the ArcGIS tool. Then, modeling, simulation, and interpolation prediction are performed for the positioning data after anomaly elimination to achieve the geographic location correction of the hydrothermal sulfide near-bottom camera and its data. This method has achieved good results in practical applications. The corrected water depth profile of the camera survey line is compatible with the high-precision terrain detected at different times in the same area. The characteristics of the corrected video images are compatible with the sample characteristics of the TV grab sampling position. A set of high-quality positioning data (sampling test 5000 points) not participating in the correction model is compared with the corrected USBL data at the same position. The following results are obtained: in the case of a confidence interval of 95%, the correlation coefficient is 1, the significance is 0, there is no significant difference between the corrected data after the simulation and its original positioning data (not participating in the model), and the correction error is below 5 m. This shows that the problem of locating a submarine camera and its data can be solved using the proposed four-dimensional anomaly elimination model established based on the USBL positioning data, high precision terrain, bathymetry and GPS data, and the corresponding cubic polynomial least-squares correction model.

The compositions of metalliferous sediments associated with hydrothermal vents can provide key geochemical data for locating seafloor sulfides. In this study, we present the geochemistry of seabed sediments from the Xunmei hydrothermal field (HF) in the South Mid-Atlantic Ridge (SMAR). The results indicate that the sediments are mainly composed of pelagic material (biogenic calcium components), basaltic debris, iron-manganese oxides, and hydrothermal components. The sediments are significantly enriched in Cu, Zn, Fe, and Co deriving from hydrothermal fluids, as well as Mn, V, Mo, U, and P, which are primarily scavenged from seawater. The northeastern Xunmei has the highest concentrations of Cu and Zn, while the northeastern, northern, and southern regions are characterized by great inputs of Fe. Manganese and Mo are mainly enriched in the western and southern parts and show a strong positive correlation, indicating that Mo is mainly scavenged by Mn oxides. Uranium, P, and Fe exhibit strong positive correlations, suggesting that they coprecipitate with Fe from hydrothermal plumes. Vanadium and Co are introduced into sediments in different ways: V is scavenged and coprecipitated by hydrothermal plumes, and Co is derived from sulfide debris. Based on the contents of Cu and Zn and Cu/Fe (0.159), Zn/Fe (0.158), and Fe/Mn (1440) ratios, it can be inferred that a high-temperature hydrothermal vent existed in northeastern Xunmei. In combination with the distribution patterns of the above elements, the hydrothermal vents in the southern part ceased erupting after a short period of activity. In addition, the high Mn anomaly and the high U/Fe ratios at the boundaries of the investigated area indicate the presence of a relatively oxidized environment in southwestern Xunmei.

The submarine camera system is one of the most effective detection methods for detecting seabed hydrothermal sulfide. The position fixing of camera equipment is generally achieved by the ultra-short baseline (USBL) positioning systems. The dynamic changes in the marine environment and the loss of acoustic signals lead to many abnormal points in the USBL positioning data. The existing methods cannot perform position fixing correction for USBL positioning data with many scattered abnormal points. This paper selects and focuses on the seabed camera data of the XunMei mineralization area acquired from the China South Atlantic voyage and employs the DTW optimization algorithm to solve this problem. This method is implemented based on Python language and an ArcGIS technical environment, and a total of 97,469 topographic profiles with 10 m spacing are extracted from the topographic data of the object area with 1m accuracy. Moreover, the highest similarity (95.9%) is obtained between the bathymetric profile of the camera survey line and the above topographic profile. The results indicate that the proposed algorithm is fast and effective, and the positioning correction accuracy of the deep-sea near-bottom camera data can reach the meter level (determined by the topographic data accuracy). Moreover, the solution can provide services for accurately position fixing near-bottom exploration equipment and its exploration data. It can also solve the problem of underwater position fixing problem that a GPS cannot solve.