The bigger picture: developing a low-cost graphical user interface to process drone imagery of tidal stream environments

Q3 Engineering
James Slingsby, B. Scott, L. Kregting, J. Mcilvenny, Jared Wilson, Marion Yanez, B. Williamson
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引用次数: 1

Abstract

Unmanned Aerial Vehicles (UAVs), or drones, offer the ability to collect cost-effective fine-scale imagery that is suitable for the capture of concurrent hydrodynamic and faunal data within tidal stream environments. This is a necessary stage of information gathering to inform tidal energy device design, advise control and maintenance strategies and better inform environmental consenting processes. For this study a total of sixty-three UAV surveys were undertaken within the Inner Sound of the Pentland Firth, Scotland, UK, over two 4-day periods in 2016 and 2018. The aims of this data collection effort were to characterise bathymetrically driven hydrodynamic features, comprising of kolk-boil distribution, presence, and area, as well as marine life such as seabird distributions, presence, and orientation relative to the flow. To achieve this, a method to extract quantifiable metrics from UAV imagery was required. This paper details the processes and methodology to create a graphical user interface (GUI) to provide these outputs rather than examining specific results. It includes an explanation of the criteria that the GUI needed to meet to be able to process the imagery, a description of the workflow and an explanation of the sub-routines required such as image registration and calibration. The outputs of the GUI, and their relevance to tidal energy developments, are also discussed. Finally, this paper details future work incorporating computer vision techniques to improve the accuracy, reliability, and processing speed of the GUI.      
更大的前景:开发一个低成本的图形用户界面来处理潮汐流环境的无人机图像
无人驾驶飞行器(uav)或无人驾驶飞机提供了收集具有成本效益的精细图像的能力,这些图像适用于潮汐流环境中同时捕获流体动力学和动物数据。这是收集信息的必要阶段,可以为潮汐能装置的设计提供信息,为控制和维护策略提供建议,并更好地为环境许可程序提供信息。在这项研究中,在2016年和2018年的两个为期4天的时间里,在英国苏格兰Pentland Firth的内湾进行了总共63次无人机调查。这项数据收集工作的目的是表征深水驱动的流体动力学特征,包括kolk-boil的分布、存在和面积,以及海洋生物,如海鸟的分布、存在和相对于水流的方向。为了实现这一点,需要一种从无人机图像中提取可量化度量的方法。本文详细介绍了创建图形用户界面(GUI)的过程和方法,以提供这些输出,而不是检查具体的结果。它包括对GUI需要满足的标准的解释,以便能够处理图像,工作流程的描述以及对所需的子例程(如图像配准和校准)的解释。还讨论了GUI的输出及其与潮汐能开发的相关性。最后,本文详细介绍了结合计算机视觉技术来提高GUI的准确性、可靠性和处理速度的未来工作。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
International Marine Energy Journal
International Marine Energy Journal Engineering-Ocean Engineering
CiteScore
1.70
自引率
0.00%
发文量
24
审稿时长
12 weeks
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