Shorebased Analysis of Alvin and Sentry High-resolution Sidescan, Multibeam and Imagery Data from the 8 degree, 20' N latitude Seamounts

洋盆由基性火山岩覆盖，这些火山岩在海底喷发，起源于大洋中脊扩张中心，在那里地幔物质上涌形成洋壳、火山岛和海山。目前，尚不清楚有多少海底熔岩是从远离扩散中心的裂隙或洋壳其他地方喷发出来的。2016年，一支大型海洋考察队被派往一个神秘的海山链，该链从东太平洋北纬8°20‘的东太平洋隆起向西延伸。为了提高这次探险的产出，邮轮上增加并部署了两个深潜平台，即人占的深潜器Alvin和能够绘制深海地貌图并独立于船及其操作员操作的自主机器人Sentry。哨兵提供了高分辨率的海底地图，Alvin允许对地图中的特定位置进行采样。这使得能够有针对性地收集样本并选择最合适的地点。它还为采样地点提供了重要的地质背景。这两个平台返回了大量(~20TB)接近底部的Alvin和哨兵数据，现在需要处理这些数据。该数据集包括视觉观测和使用Alvin获取的高分辨率数字静止和视频图像，以及来自哨兵的近底部声纳数据，该数据提供了暴露在海山侧翼和山顶上的火山地形的~1米分辨率。这项研究涉及对这一独特的高分辨率数据集进行处理和部分分析，包括从快速扩张的大洋中脊的轴线到海底年龄近200万年的火山海底的广泛观测、样本和地图覆盖。处理和分析的结果对于加强探险收集的信息及其解释至关重要，特别是在评估熔岩侵位的相对年龄(S)、定量测量海底地形特征以及阐明沿海山链海底火山活动的性质方面。这些发现对我们理解发生在距离大洋中脊扩展中心轴线很远(20-200公里)的岩浆过程具有重要意义，据信大洋中的大多数岩浆活动发生在那里。这项工作的结果也将是将输入参数限制在地球动力学模型中的关键，这些模型试图描述快速扩张的洋脊上地幔的融化过程。更广泛的影响包括为一次将大大提高研究成果的大型海洋考察提供重要和补充的数据，培训一名职业生涯早期的科学家，处理用于了解海底火山过程的关键数据集，以及制作可能对军事潜艇航行具有重要意义的地图。这项研究将对2016年收集的阿尔文和哨兵数据进行处理和初步分析，这是一次重大的海洋考察，探索了东太平洋北纬8°20‘的东太平洋隆起以西的海山链。将进行的数据汇编和分析包括：对阿尔文潜水15次期间获得的约90 000张数字图像进行地理参考，并对静止图像和视频图像进行量化分析，以帮助生成每一座海山的火山相图。这些将叠加在哨兵多波束和侧扫地图上，以生成勘测地区的地质图，并提供哨兵近海底声纳数据的斜坡和海底纹理分析。这些将与火山特征、形态和沉积物分布相关联，这些将由数字静止图像分析得出。这项工作将对整个8°20‘N海山区域(约7000平方公里)的EM122多波束数据进行形态和坡度分析，从而能够定量测量海山的底径、高度、形态、是否有陨石坑/破火山口(和大小)，以及海山俯视建筑物的形状特征和纵横比。所有这些都将作为距离东太平洋隆起的距离的函数，以及距离每个主要建筑物中心的距离和距离邻近的深山断层的距离。从这一分析中，将根据区域和地方尺度上与相邻锥体/建筑物和断层的接触关系，估计整个8°20‘N海山链上地物的相对年龄。所有经过处理的数据将在两年内与所有相关元数据一起提供给公共数据档案馆。这项工作的出版物将链接到相关数据中心和档案馆的数据。

The ocean basins are underlain by mafic volcanic rocks that are erupted on the seafloor and originate at mid-ocean ridge spreading centers where upwelling of mantle material forms ocean crust and volcanic islands and seamounts. Presently, it is not known how much seafloor lava is erupted from fissures or other places in the ocean crust that are away from the spreading centers. In 2016, a major oceanographic expedition was sent out to an enigmatic seamount chain that extends to the west from the East Pacific Rise at 8° 20'N latitude in the eastern Pacific Ocean. To enhance the output of this expedition, two deep submergence platforms, the ALVIN, a human-occupied deep submergence vehicle, and SENTRY, an autonomous, robotic vehicle that is able to map deep ocean landscapes and operate independently from the ship and its operators, were added to the cruise and deployed. SENTRY provided high resolution mapping of the seafloor and the ALVIN allowed sampling of specific locations within the maps. This allowed targeted sample collection and selection of the most appropriate sites. It also provided important geologic context to where samples were taken. These two platforms returned a large volume (~20 terabytes) of near-bottom ALVIN and SENTRY data that now require processing. The dataset includes visual observations and high-resolution digital still and video imagery acquired using ALVIN, and near-bottom sonar data from SENTRY that provides ~1 m resolution of the volcanic terrain exposed on the seamount flanks and summits. This research involves the processing and partial analysis of this unique, high-resolution dataset in terms of extensive observational, sample and map coverage on volcanic seafloor away from the axis of a fast-spreading mid-ocean ridge out to seafloor ages of nearly 2 million years. The results of the processing and analysis is critical for enhancing the information collected on the expedition and its interpretation, especially with regard to evaluating relative age(s) of lava emplacement, quantitative measurement of seafloor topographic features, and illuminating the nature of seafloor volcanism along the seamount chain. Findings have important implications for our understanding of magmatic processes that occur significant distances (20-200 km) from a mid-ocean ridge spreading center axis where it is believe that most magmatism in the ocean occurs. Results of this work will also be key for constraining input parameters to geodynamic models that seek to describe melting processes in the upper mantle at fast-spreading ocean ridges. Broader impacts include providing important and complementary data for an major oceanographic expedition that will significantly enhance the research output, training of an early career scientist, processing a key dataset for understanding seafloor volcanic processes, and generating maps that could have importance for military submarine navigation. This research will process and provide preliminary analysis of the ALVIN and SENTRY data collected on the 2016, a major oceanographic expedition that explored the seamount chain that extends to the west of the East Pacific Rise at 8° 20'N latitude in the eastern Pacific Ocean. Data compilations and analyses that will be done include: georeferencing ~90,000 digital images acquired during 15 ALVIN dives and conducting quantitative analysis of the still- and video-imagery to help generate volcanic facies maps for each of the seamounts. These will be overlain on SENTRY multibeam and sidescan maps to produce geological maps of the surveyed areas and provide slope and seafloor textural analysis of SENTRY near-bottom sonar data. These will be correlated to volcanic feature morphology and sediment distribution that will be derived from digital still imagery analysis. The work will provide a morphological and slope analysis of EM122 multibeam data over the entire span of the 8° 20'N seamount area (~7000 km2) which will permit quantitative measurements of seamount basal diameters, height, morphology, presence of craters/calderas (and sizes), and seamount plan-view edifice shape characterization and aspect ratio. All of this will be done as a function of distance from the East Pacific Rise as well as the distance from each major edifice center and distance from adjacent abyssal hill faults. From this analysis, an estimation of the relative ages of features throughout the 8° 20'N seamount chain will be done, based on contact relationships with adjacent cones/edifices and faults at both regional and local scales. All processed data will be provided to a public data archive with all relevant metadata within two years. Publications from this work will be linked to data in the relevant data centers and archives.