Optimising marine image capture and analysis from autonomous underwater vehicles (MICA)

优化自主水下航行器 (MICA) 的海洋图像捕获和分析

• 批准号: 2860055
• 金额: --
• 依托单位: University of the Highlands and Islands
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2023
• 资助国家: 英国
• 起止时间: 2023 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2860055
• 关键词: Optimising; marine; image; capture; analysis

salmon farming, in Scotland, currently encompasses >230 sites, from Loch Fyne in the south to Shetland in the North. The industry seeks to expand, doubling economic value by 2030. The detritus from salmon farms (organic matter) is dispersed around the fish-cages to an extent that is determined by the receiving environment (depth, local current regime etc) and this material variously impacts the seabed. The Scottish regulator (SEPA) and their advisors (MICA-partners, NatureScot) are required to ensure sustainability of the sector and that the receiving environment is not adversely affected beyond local scales. Of particular concern are priority marine features (PMFs) which are individual taxa/biotopes considered to be highly sensitive, rare and/or which provide critical ecosystem functions. Examples of PMFs range between individuals of the coral Swiftia sp to sensitive biogenic reefs such as mussel-beds and maerl. The sector (industry and regulators) needs non-destructive, scale-appropriate methods for identifying and mapping PMFs. The student will initially focus on developing innovative, machine-assisted approaches to mapping the locations of blue- and horse-mussel reefs, both of which are local to SAMS (https://marinescotland.atkinsgeospatial.com/nmpi/) (e.g., Lochs Levan and Creran). Our surveys will extend to maerl as surveying resources/partner input allows.

苏格兰的鲑鱼养殖目前涵盖超过 230 个地点，从南部的法恩湖到北部的设得兰群岛。该行业寻求扩张，到 2030 年将经济价值翻一番。来自鲑鱼养殖场的碎屑（有机物质）在鱼笼周围的分散程度取决于接收环境（深度、当地现状等）以及这些物质的不同程度影响海底。苏格兰监管机构 (SEPA) 及其顾问（MICA 合作伙伴、NatureScot）必须确保该行业的可持续性，并且接收环境不会受到超出当地规模的不利影响。特别值得关注的是优先海洋特征（PMF），它们是被认为高度敏感、稀有和/或提供关键生态系统功能的单个分类群/生境。 PMF 的例子范围从珊瑚 Swiftia sp 个体到敏感的生物礁，如贻贝床和 maerl。该部门（行业和监管机构）需要非破坏性、适合规模的方法来识别和绘制 PMF。学生最初将专注于开发创新的机器辅助方法来绘制蓝贻贝礁和马贻贝礁的位置图，这两种礁都属于 SAMS (https://marinescotland.atkinsgeospatial.com/nmpi/)（例如，莱文湖和克雷兰）。在调查资源/合作伙伴输入允许的情况下，我们的调查将扩展到 maerl。