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Assessment of submerged aquatic vegetation abundance using multibeam sonar in very shallow and dynamic environment. The Lagoon of Venice (Italy) case study

机译:在非常浅和动态的环境中,使用多束声纳评估水下水生植物的丰度。威尼斯泻湖(意大利)案例研究

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Underwater acoustic devices are widely recognized as very effective tools to remotely map and characterize the seabed and overlying habitats. Multibeam echosounder systems (MBES), in particular, deliver high-resolution co-located bathymetry and acoustic backscatter. The processing of MBES signals is a complex problem requiring knowledge of the angular dependence of the reflected signal, the bottom morphology and the water column reverberation. Especially in shallow, tidal environment, such as the lagoon of Venice (Italy), the multipath reflections and the environmental conditions affect the signal quality. Our study aims to find a repeatable methodology for submerged aquatic vegetation (SAV) imaging and its abundance assessment in a very shallow and dynamic environment. Currents, salinity and turbidity influence the acoustic characteristic of water column and benthic backscatter and the SAV detection by multibeam sonar. Combining MBES and ground truth data allowed us to estimate SAV coverage with high accuracy taking into account environmental conditions. We present the preliminary results of a 12 hours experiment in one of the channels of the Venice lagoon partly covered by SAV. The channel was repeatedly surveyed about every hour, using a Kongsberg 2040c dual head multibeam system with two frequencies: 200 kHz and 320 kHz. At the same time CTD profiles were acquired to estimate the environmental conditions, while video sampling was used for ground-truthing. New algorithms were developed for signal and image analysis of MBES signals (including water column data) for efficient and reliable SAV detection and assessment in shallow subtidal environment.
机译:水下声学设备被公认为是远程绘制海底和上覆生境特征的非常有效的工具。特别是,多波束回声测深仪系统(MBES)可以提供高分辨率的并置测深和声学反向散射。 MBES信号的处理是一个复杂的问题,需要了解反射信号的角度依赖性,底部形态和水柱混响。特别是在浅潮的环境中,例如威尼斯(意大利)的泻湖,多径反射和环境条件会影响信号质量。我们的研究旨在寻找一种可重复的方法,用于在非常浅且动态的环境中进行水下水生植物(SAV)成像及其丰度评估。电流,盐度和浑浊度会影响水柱和底栖反向散射的声学特性,并影响多波束声纳的SAV检测。结合MBES和地面真实数据,我们可以在考虑环境条件的情况下以高精度估算SAV覆盖率。我们介绍了在被SAV部分覆盖的威尼斯泻湖之一的通道中进行的12小时实验的初步结果。使用Kongsberg 2040c双头多波束系统,频率为200 kHz和320 kHz,每小时大约重复调查一次该信道。同时,获取了CTD剖面图以估算环境条件,同时使用视频采样进行地面实景拍摄。开发了用于MBES信号(包括水柱数据)的信号和图像分析的新算法,以在浅潮下环境中进行有效和可靠的SAV检测和评估。

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