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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:在非常浅的动态环境中使用Multibeam Sonar评估淹没的水生植被丰度。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:水下声学器件被广泛认可为远程映射和表征海底和覆盖栖息地的非常有效的工具。多次反震器系统(MBES),特别是提供高分辨率共同定位的沐浴络和声反向散射器。 MBES信号的处理是需要了解反射信号的角度依赖性,底部形态和水柱混响的角度依赖性的复杂问题。特别是在浅,潮汐环境中,如威尼斯(意大利)的泻湖(意大利),多径反射和环境条件影响信号质量。我们的研究旨在为淹没水生植被(SAV)成像以及其在非常浅和动态的环境中的丰富评估中找到一种可重复的方法。电流,盐度和浊度会影响水柱的声学特性和底座反向散射和Mulibeam Sonar的SAV检测。结合MBES和地面真理数据使我们估计鉴于环境条件的高精度估计救济覆盖率。我们展示了12小时实验中的12小时实验,其中一个威尼斯泻湖的渠道部分由Sav覆盖。每小时多次调查该频道,使用具有两个频率的kongsberg 2040c双头多滨系统:200 kHz和320 kHz。同时获得CTD型材以估计环境条件,而视频采样用于接地纹。开发了新的算法,用于MBES信号(包括水列数据)的信号和图像分析,以便在浅层环境中的高效可靠,可靠地检测和评估。

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