Gutiérrez Estrada, Juan CarlosPulido Calvo, InmaculadaCastro Gutiérrez, JairoPeregrín Rubio, AntonioLópez Domínguez, SamuelGómez Bravo, FernandoGarrocho Cruz, AlejandroRosa Lucas, Ignacio de la2022-10-102022-10-102022-01-29Gutiérrez-Estrada, J. C., Pulido-Calvo, I., Castro-Gutiérrez, J., Peregrín, A., López-Domínguez, S., Gómez-Bravo, F., Garrocho-Cruz, A., & de la Rosa-Lucas, I. (2022). Fish abundance estimation with imaging sonar in semi-intensive aquaculture ponds. Aquacultural Engineering, 97, 102235. https://doi.org/10.1016/j.aquaeng.2022.1022350144-8609http://hdl.handle.net/10272/21236To know the abundance of fishes and their size distribution in the semi-intensive rearing systems in traditional ponds is an aspect key to plan and manage efficiently the sales lots. Usually this information is obtained by means of sampling which mandatory supposes a direct catch and stressful and time consuming management of fishes. Therefore, in this work we propose the use of non-invasive procedures based on multibeam sonars or imaging sonars to count and size the fishes in the ponds. For that, we use a commercial technology portable-fixed multibeam imaging sonar and estimate the abundance in ponds of a gilt-head seabream (Sparus aurata) fishfarm from sonar image analysis and adapting statistical methodologies traditionally applied for bird abundance estimation. Additionally, a simulation software was developed to emulate the fish aggregation contained in the rearing ponds. This computer program allows the calculation of an abundance correction factor which depends on the transducer beam size in relation to the pond size. The results indicate that the estimation is as accurate as the obtained by the fishfarm manager using traditional sampling methods and additionally it is possible to obtain a realistic function of the size distribution which allows estimate the biomass by size contained in the rearing ponds.engAtribución-NoComercial-SinDerivadas 3.0 Españahttp://creativecommons.org/licenses/by-nc-nd/3.0/es/Sparus aurataImproved extensive farmingCensus stationMultibeam sonarImage analysisjournal article10.1016/j.aquaeng.2022.102235open access31 Ciencias Agrarias25 Ciencias de la Tierra y del Espacio