Blending bathymetry: Combination of image-derived parametric approximations and celerity data sets for nearshore bathymetry estimation

IF 4.2 2区 工程技术 Q1 ENGINEERING, CIVIL Coastal Engineering Pub Date : 2024-05-29 DOI:10.1016/j.coastaleng.2024.104546
Jonghyun Lee , Katherine DeVore , Tyler Hesser , A. Spicer Bak , Katherine Brodie , Brittany Bruder , Matthew Farthing
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引用次数: 0

Abstract

Estimation of nearshore bathymetry is important for accurate prediction of nearshore wave conditions. However, direct bathymetry data collection is expensive and time-consuming while accurate airborne lidar-based survey is limited by breaking waves and decreased light penetration affected by water turbidity. Instead, tower-based platforms or Unmanned Aircraft System (UAS) can provide indirect video-based observations such as time-series (or videos) and time-averaged (Timex) or variance enhanced (Var) images. The time-series imagery can provide wave celerity information for bathymetry estimation through the well-known dispersion relationship, for example the cBathy algorithm, or physics-based models. However, wave celerities and associated inverted water depths are sensitive to noise during image collection and processing stages or may not even be available over the entire area of interest. Timex or Var images can be used to identify persistent regions of wave breaking (for example over the sand bar and at the shoreline) so that one can create bathymetry profiles using simplified approximations based on parametric forms. However, the accuracy of this approach highly depends on the assumption of the chosen parametric form as well as the accuracy of detecting sandbars and shoreline.

In this work, we propose a rapid and improved bathymetry estimation method that takes advantage of image-derived wave celerity from cBathy and a first-order bathymetry estimate from Parameter Beach Tool (PBT), software that fits parameterized sandbar and slope forms to the nearshore imagery. Two different sources of the data, PBT and wave celerity, are combined or blended optimally based on their assumed accuracy in a statistical (i.e., Bayesian) framework. The PBT-derived bathymetry serves as “prior” coarse-scale background information and then is updated and corrected with the cBathy-derived wave data through the dispersion relationship, which results in a better bathymetry estimate that is consistent with imagery-based wave data. To illustrate the accuracy of our proposed method, imagery data sets collected in 2017 at the US Army Engineer Research and Development Center’s (ERDC) Field Research Facility (FRF) in Duck, North Carolina under different weather and wave height conditions are tested. Estimated bathymetry profiles are remarkably close to the direct survey data due to the optimal fusion of two data sets. The computational time for the estimation from PBT-based bathymetry and CBathy-derived wave celerity is only about five minutes on a free Google Cloud node with one CPU core. These promising results indicate the feasibility of reliable real-time bathymetry imaging during a single flight of UAS.

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混合水深测量:结合图像参数近似值和流速数据集进行近岸水深估算
近岸水深测量对于准确预测近岸波浪状况非常重要。然而,直接采集水深数据既昂贵又耗时,而基于机载激光雷达的精确勘测则受到破浪和水体浑浊度影响光穿透力下降的限制。取而代之的是,塔基平台或无人机系统(UAS)可提供间接视频观测,如时间序列(或视频)和时间平均(Timex)或方差增强(Var)图像。时间序列图像可通过众所周知的分散关系(如 cBathy 算法)或基于物理的模型,为水深估算提供波速信息。不过,波速和相关的反演水深对图像采集和处理阶段的噪声很敏感,甚至可能无法获得整个相关区域的波速和相关反演水深。可以使用 Timex 或 Var 图像来确定持续的破浪区域(例如沙洲和海岸线),这样就可以使用基于参数形式的简化近似值来绘制水深剖面图。在这项工作中,我们提出了一种快速、改进的水深估算方法,该方法利用了从 cBathy 获取的图像波速和从参数海滩工具(PBT)获取的一阶水深估算,参数海滩工具是一种将参数化沙洲和斜坡形式拟合到近岸图像的软件。两种不同来源的数据,即 PBT 和波速,根据其在统计(即贝叶斯)框架中的假定精确度进行优化组合或混合。PBT 导出的水深作为 "先验 "粗尺度背景信息,然后通过分散关系与 cBathy 导出的波浪数据进行更新和校正,从而获得与基于图像的波浪数据一致的更好的水深估计值。为了说明我们提出的方法的准确性,我们对 2017 年在北卡罗来纳州达克的美国陆军工程研发中心(ERDC)野外研究设施(FRF)收集的不同天气和波高条件下的图像数据集进行了测试。由于对两个数据集进行了优化融合,估算的水深剖面与直接勘测数据非常接近。在配备一个 CPU 内核的免费谷歌云节点上,根据基于 PBT 的测深数据和 CBathy 导出的波速进行估算所需的计算时间仅为 5 分钟左右。这些令人鼓舞的结果表明,在无人机系统单次飞行期间进行可靠的实时水深成像是可行的。
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来源期刊
Coastal Engineering
Coastal Engineering 工程技术-工程:大洋
CiteScore
9.20
自引率
13.60%
发文量
0
审稿时长
3.5 months
期刊介绍: Coastal Engineering is an international medium for coastal engineers and scientists. Combining practical applications with modern technological and scientific approaches, such as mathematical and numerical modelling, laboratory and field observations and experiments, it publishes fundamental studies as well as case studies on the following aspects of coastal, harbour and offshore engineering: waves, currents and sediment transport; coastal, estuarine and offshore morphology; technical and functional design of coastal and harbour structures; morphological and environmental impact of coastal, harbour and offshore structures.
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