Nearshore satellite-derived bathymetry from a single-pass satellite video: Improvements from adaptive correlation window size and modulation transfer function

IF 11.1 1区 地球科学 Q1 ENVIRONMENTAL SCIENCES
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Abstract

Accurate nearshore bathymetry estimation remains a critical challenge, impacting coastal forecasting evolution assessments through the inaccuracies in both in-situ and remote sensing surveys. This article introduces the Satellite Derived Bathymetry (SDB) temporal correlation method, showcasing its ability in deriving accurate nearshore bathymetry from one minute spaceborne videos. The approach utilises correlation of pixel intensity time series, shifted in time and space, extracted from a frame stack within a defined correlation window. The resulting correlation is then projected using the Radon Transform to infer wave characteristics (celerity and wavelength) for the estimation of depth through wave linear dispersion. Moreover, the adaptation of the correlation window based on a first wavelength estimation provided a more focused assessment of the wavefield that reveals morphological features such as sandbars in the bathymetric estimation. The method’s capabilities using adapted correlation window is illustrated through its application to a metric resolution Jilin satellite video (57 s at 5 Hz) along the Saint-Louis coast in Senegal. Through this demonstration, the temporal correlation method is among the first SDB methods to successfully capture the submerged sandbar along a beach. Comparison against in-situ measurements conducted three years prior to the video acquisition shows a good agreement with a bias of 0.97 m within the initial 2 km of the cross-shore profile. Furthermore, the application of previously developed sky-glint surface elevation analysis on video pixel intensity, prior to the bathymetry estimation, significantly reduces the bias to 0.44 m in the Saint-Louis estimation. This article highlights the potential applications of future Earth observation satellite missions that will capture image sequences (or videos) such as CO3D (CNES/Airbus).

从单通卫星视频中获取近岸卫星水深测量数据:自适应相关窗口大小和调制传递函数带来的改进
近岸水深的精确估算仍然是一个严峻的挑战,由于原位和遥感勘测的不准确性,对沿岸预报演化评估产生了影响。本文介绍了卫星推算水深(SDB)时间相关方法,展示了该方法从一分钟空间视频推算准确近岸水深的能力。该方法利用从定义的相关窗口内的帧堆栈中提取的像素强度时间序列的相关性,在时间和空间上进行移动。然后利用拉顿变换对相关结果进行投影,以推断波浪特征(流速和波长),从而通过波浪线性色散估算深度。此外,根据第一次波长估算对相关窗口进行调整,可对波场进行更有针对性的评估,从而在测深估算中揭示沙洲等形态特征。通过将该方法应用于塞内加尔圣路易沿岸的米分辨率吉林卫星视频(57 秒,5 赫兹),说明了该方法使用调整后的相关窗口的能力。通过该演示,时间相关方法是首批成功捕捉海滩水下沙洲的 SDB 方法之一。与视频采集前三年进行的现场测量结果进行比较后发现,在跨海岸剖面的最初 2 千米范围内,偏差为 0.97 米,两者吻合度很高。此外,在进行水深估算之前,对视频像素强度应用之前开发的天空燧石表面高程分析,大大减少了圣路易估算的偏差,仅为 0.44 米。本文强调了未来地球观测卫星任务的潜在应用,这些任务将捕获图像序列(或视频),如 CO3D(法国国家空间研究中心/空中客车公司)。
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
Remote Sensing of Environment
Remote Sensing of Environment 环境科学-成像科学与照相技术
CiteScore
25.10
自引率
8.90%
发文量
455
审稿时长
53 days
期刊介绍: Remote Sensing of Environment (RSE) serves the Earth observation community by disseminating results on the theory, science, applications, and technology that contribute to advancing the field of remote sensing. With a thoroughly interdisciplinary approach, RSE encompasses terrestrial, oceanic, and atmospheric sensing. The journal emphasizes biophysical and quantitative approaches to remote sensing at local to global scales, covering a diverse range of applications and techniques. RSE serves as a vital platform for the exchange of knowledge and advancements in the dynamic field of remote sensing.
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