Sediment Imaging with Autonomous Underwater Vehicles: A Community Tool

GSTDTAP

项目编号	1754419
	Sediment Imaging with Autonomous Underwater Vehicles: A Community Tool
	Ross Parnell-Turner
主持机构	University of California-San Diego Scripps Inst of Oceanography
项目开始年	2018
	2018-08-01
项目结束日期	2019-07-31
资助机构	US-NSF
项目类别	Standard Grant
项目经费	98930(USD)
国家	美国
语种	英语
英文摘要	The deepest parts of Earth's oceans are remote and difficult to explore. Thus, the geological, biological, and chemical processes taking place there remain poorly understood. Advances in autonomous underwater vehicle (AUV) technology in the past decade mean that we can now send these vehicles to the seabed in water depths of several miles where they collect data from just above the seafloor. AUVs are often equipped with a high-resolution compressed-high intensity pulse (CHIRP) sonar, which can capture centimeter-scale-resolution, cross-section images of the sediment that blankets the seafloor. These thicknesses can then be used as proxies for the length of time a feature has been exposed on the seafloor. Despite this potential, time constraints and a lack of an easily available sonar data processing scheme means that these CHIRP data are often under-utilized. This research develops a standard workflow and software for processing EdgeTech CHIRP sonar data, for use both at sea and on shore, using already existing AUV-acquired CHIRP surveys of sediment from a specific location on the Mid-Atlantic Ridge and other associated imaging data. Application of the processed data will be used to measure sediment thickness in an area where knowledge of this parameter advances our understanding of the interplay between the faulting and volcanism at mid-ocean ridge axes. Broader impacts of the research add value and capability to the existing US AUV fleet and advance our understanding of crustal formation at mid-ocean ridges. The methods and outcomes of the work will be incorporated into professional development workshops for in-service teachers in the highly diverse San Diego Unified School District, providing resources for lessons that can be widely used throughout the school system and support an early career investigator. In areas far from terrestrial sources, sediment thickness in deep sea marine environments is a rough proxy for the amount of time a feature has been exposed on the seabed. Thus, this provides a way to constrain the timing of geological events, such as volcanic eruptions and/or slip on faults. At young features, such as mid-ocean ridges axial valleys, sediment is typically only a few meters thick and so cannot be picked up by other shipboard geophysical/seismic imaging tools. These sediment thicknesses, at present, can only be imaged using near-bottom sonars such as those carried by AUVs. Use of these tools is particularly useful at slow-spreading mid-ocean ridges where the interplay between low-angle faults, know as detachments, and volcanism remains poorly understood. Although it is now clear that vast areas of seafloor are created under the influence of detachment faults, the relationships between detachments and magmatism and melt supply remain uncertain. This project uses already existing CHIRP data, acquired during fourteen dives of AUV Sentry at latitude 16.5°N on the Mid-Atlantic Ridge in 2013. Research goals are to provide new CHIRP processing protocols that can be used to more quickly process CHIRP sonar data and to use the existing data to quantitatively determine variations in sediment thickness and, thus, establish the relative timing of detachment fault slip and volcanism in the study area. The research adds significant value to an existing dataset that was acquired in an inaccessible part of the deep ocean and will deliver an open-source software tool to the scientific community and the public in a cost-effective way. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
文献类型	项目
条目标识符	http://119.78.100.173/C666/handle/2XK7JSWQ/72937
专题	环境与发展全球科技态势
推荐引用方式 GB/T 7714	Ross Parnell-Turner.Sediment Imaging with Autonomous Underwater Vehicles: A Community Tool.2018.