Autonomous Seagrass Habitat Monitoring System (ASHMoS)

自主海草栖息地监测系统（ASHMoS）

• 批准号: 10053530
• 金额: $ 19.46万
• 依托单位: HYDROSURV UNMANNED SURVEY (UK) LTD
• 依托单位国家: 英国
• 项目类别: CR&D Bilateral
• 财政年份: 2023
• 资助国家: 英国
• 起止时间: 2023 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=10053530
• 关键词: Autonomous; Seagrass; Habitat; Monitoring; System

Collaborators HydroSurv Unmanned Survey (UK) Ltd and University of Plymouth Marine Institute are bringing together an expert team to combine HydroSurv's robotic survey technology and rapid development capabilities with an internationally recognised academic expertise in marine science to develop a groundbreaking solution for subtidal survey of submerged aquatic vegetation, putting a new end-to-end solution into the hands of UK coastal practioners for natural capital assessment and monitoring.Driven by the well-publicised successes within their previous project for acoustic ground discrimination techniques for the monitoring of seagrass, the partnership will advance the accuracy of this novel technique bringing together a series of new datasets to assess the condition of benthic habitats and provide sediment characterisation alongside seagrass biomass estimation based on the validated needs of survey commissioners and data users within public, government and local authority organisations.Central to the new approach is use of rapidly-deployable HydroSurv Uncrewed Surface Vessel (USV) platforms with electric propulsion, combined with an advanced sensor array to collect a range of hydroacoustic and observational measurements from a ground truthing instrument array. The use of deep learning algorithms is expanded from characterising the coverage, density and canopy height of seagrass to carrying out sediment analysis, whilst collecting complementary environmental datasets geolocated to the primary datasets. The data delivery builds upon HydroSurv's enterprise-scale GIS cloud application to enable users to monitor temporal changes without specialist data interrogation skills.Staying true to HydroSurv's aim to democratise ocean data, the solution will slash the cost and carbon intensity of data collection relative to established survey techniques whilst removing personnel from harms way, and will be made flexibly and conveniently accessible to the market.

HydroSurv Unmanned Survey（UK）Ltd和普利茅斯大学海洋研究所（University of Plymouth Marine Institute）正在组建一个专家团队，将HydroSurv的机器人调查技术和快速开发能力与国际公认的海洋科学学术专长相结合，开发一种突破性的水下水生植被潮下带调查解决方案，为英国海岸实践者提供了一个新的端到端解决方案，用于自然资本评估和监测。在他们以前的项目中，声学地面识别技术用于监测海草，该伙伴关系将提高这一新技术的准确性，将一系列新的数据集汇集在一起，以评估底栖生境的状况，并根据调查专员和公众内部数据用户的有效需求，新方法的核心是使用可快速部署的无人水面舰艇（USV）该平台配备了电力推进装置，结合先进的传感器阵列，从地面实况调查仪器阵列收集一系列水声和观测测量数据。深度学习算法的使用从描述海草的覆盖范围、密度和树冠高度扩展到进行沉积物分析，同时收集地理定位到主要数据集的补充环境数据集。数据交付建立在HydroSurv的企业级GIS云应用程序之上，使用户能够在没有专业数据询问技能的情况下监测时间变化。该解决方案忠实于HydroSurv的海洋数据民主化目标，相对于现有的调查技术，该解决方案将大幅削减数据收集的成本和碳强度，同时将人员从危险的方式中解脱出来，并将灵活方便地进入市场。