Hydroacoustic Autonomous boat for Remote fish detection in LakE (HARLE ), an unmanned autonomous surface vehicle to monitor fish populations in lakes - INRAE - Institut national de recherche pour l’agriculture, l’alimentation et l’environnement Accéder directement au contenu
Article Dans Une Revue Limnology and Oceanography: Methods Année : 2021

Hydroacoustic Autonomous boat for Remote fish detection in LakE (HARLE ), an unmanned autonomous surface vehicle to monitor fish populations in lakes

Résumé

To evaluate the aquatic ecosystem's quality and ensure the sustainable management of fisheries, it is important to monitor fish populations. Hydroacoustics uses sound waves to noninvasively scan and gather information on waterbodies including fish abundance and distribution. Unmanned surface vehicles (USV) have been increasingly used in marine and freshwater environments to enable data collection. We provide a detailed description of a new USV called Hydroacoustic Autonomous boat for Remote fish detection in LakE (HARLE), which is devoted to hydroacoustic studies in freshwater. The USV is electrically powered and equipped with the most modern fishery scientific echosounder, suitable for broadband applications, the EK80 (SIMRAD). The USV was used for a conventional hydroacoustic survey in a peri-alpine lake to investigate its potential to monitor fish populations in lakes. In the lower layer of the lake where there were numerous targets and comparisons were possible, hydroacoustic metrics and fish biomass values (kg ha(-1)) from the SIMRAD EK80 on board the USV and EK60 on board the research vessel were similar. We showed that the HARLE has great potential to be used as a tool for fish monitoring and hydroacoustic survey in freshwater.
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hal-03303946 , version 1 (28-07-2021)

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Chloé Goulon, Olivier Le Meaux, Romain Vincent‐falquet, Jean Guillard. Hydroacoustic Autonomous boat for Remote fish detection in LakE (HARLE ), an unmanned autonomous surface vehicle to monitor fish populations in lakes. Limnology and Oceanography: Methods, 2021, 19 (4), pp.280-292. ⟨10.1002/lom3.10422⟩. ⟨hal-03303946⟩
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