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The application of underwater acoustic and visual 3D mapping technologies for the study of deep ocean ecosystems.

水声和视觉 3D 测绘技术在深海生态系统研究中的应用。

基本信息

批准号：
2102509
负责人：
金额：
--
依托单位：
University of Oxford
依托单位国家：
英国
项目类别：
Studentship
财政年份：
2018
资助国家：
英国
起止时间：
2018 至无数据
项目状态：
已结题

来源：
https://gtr.ukri.org/projects?ref=studentship-2102509
关键词：
application underwater acoustic visual 3D

项目摘要

The deep ocean is the largest habitat for life on Earth, yet scientific understanding of this ecosystem remains limited. The data available shows that although deep sea biodiversity provides vital ecosystem services to support life on Earth, global anthropogenic threats are already impacting its persistence. This demonstrates the urgency to inform, create and implement a framework for sustainable deep ocean governance. Scientific understanding of the drivers of deep ocean biodiversity is essential for such a framework, but the high requirements of conducting a scientific expedition limit extensive sampling. Applying 3D mapping methodologies to deep ocean habitats can reduce the sampling time needed underwater and increase the amount of data collected from an area. Whereas acoustic mapping of sea-floor features for bathymetry is well-developed, optic 3D mapping using video material is not as common. Yet, optic maps can provide important visual details uncaptured by acoustic methods. This research will explore the potential of selected acoustic and optic technologies for the 3D mapping of deep sea habitats, with the aim of reducing precious sampling time in situ and increasing information about deep sea habitats to inform their governance. Specifically, it will aim to develop methodologies to create and analyse 3D maps of deep ocean ecosystems by combining input from multibeam sonar, photogrammetry and photomosaics. The suitability of these new technologies for marine biological science will be tested by analysing the relationship between 3D habitat heterogeneity and biological communities in the Indian Ocean at different scales and at depths between 0 and 500 m. Systematic surveying at different depths will take place at in multiple parts of the Indian Ocean. Multibeam sonar (Teledyne SeaBat T50-P) will be deployed from the ship to characterize the seafloor profile. Multibeam maps will be created using established data collection and software (Reson PDS). Post-cruise a method will be developed to analyse the maps for measures of habitat complexity (Teledyne CARIS). A new protocol will be developed to collect and process video images for photogrammetry. Different platforms will be used to collect video material (subs, ROVs, divers) and training will take place with pilots and divers on best practices for collecting and scaling. Multiple routes will be explored to convert the collected imagery to 3D visualisations using Agisoft PhotoScan. These models will be analysed for habitat complexity information following an established protocol in Rhinoceros. At each location, biological data will be collected using video surveys. Post cruise these surveys will be analysed to inform how habitat characteristics influence biodiversity in this part of the deep ocean.This research will take place in collaboration with the Nekton Foundation as part of mission 'First Descent' to improve our understanding of deep ocean biodiversity patterns and their environmental drivers in the Indian Ocean.

深海是地球上最大的生命栖息地，但对这一生态系统的科学认识仍然有限。现有数据显示，尽管深海生物多样性为支持地球上的生命提供了至关重要的生态系统服务，但全球人为威胁已经影响到其持久性。这表明迫切需要为可持续深海治理提供信息，建立和实施一个框架。对深海生物多样性驱动因素的科学理解对于这样一个框架至关重要，但进行科学考察的高要求限制了广泛的采样。将三维绘图方法应用于深海生境可以减少水下所需的采样时间，并增加从一个地区收集的数据量。虽然海底地形声学测图已很发达，但使用视频材料的光学三维测图并不常见。然而，光学地图可以提供声学方法无法捕获的重要视觉细节。这项研究将探索选定的声学和光学技术在深海生境三维测绘方面的潜力，目的是减少宝贵的现场取样时间，增加有关深海生境的信息，为深海生境的治理提供信息。具体而言，该项目的目标是制定各种方法，通过综合多波束声纳、摄影测量和摄影镶嵌的投入，制作和分析深海生态系统的三维地图。将通过分析印度洋不同尺度和0至500米深度的三维生境异质性与生物群落之间的关系，检验这些新技术对海洋生物科学的适用性。将在印度洋多个地区进行不同深度的系统测量。将从船上部署多波束声纳（Teledyne SeaBat T50-P），以确定海底剖面的特征。将使用已建立的数据收集和软件（Reson PDS）创建多波束标测图。航行后将制定一种方法，分析地图，以衡量生境复杂性（Teledyne CARIS）。将制定一项新的协议，以收集和处理摄影测量的视频图像。将使用不同的平台收集视频材料（潜艇、遥控潜水器、潜水员），并将对飞行员和潜水员进行收集和缩放的最佳做法培训。将探索多种途径，使用Agisoft PhotoScan将收集的图像转换为3D可视化。这些模型将分析栖息地的复杂性信息后，在犀牛的既定协议。在每个地点，将使用视频调查收集生物数据。巡航结束后，将对这些调查进行分析，以了解栖息地特征如何影响深海这一部分的生物多样性。这项研究将与游泳动物基金会合作进行，作为“第一次下降”使命的一部分，以提高我们对印度洋深海生物多样性模式及其环境驱动因素的理解。