Kande Y. auteur aut IRD Dabo-Niang S. auteur aut IRD Diogoul N. auteur aut IRD Brehmer Patrice auteur aut IRD text conferencePaper eng text/pdf reformatted digital access In this work, we were interested in the application of functional, spatial data analysis (FSDA) on coupling acoustic (Sv) and environmental (water temperature, fluorescence, salinity and turbid-ity) data. To do this we use data from an acoustics fisheries surveys (R/V Thalassa, Ifremer, AWA campaign) carry out in West African waters using multifrequency echosounder (18, 38, 70, 120, 333 kHz) and a scanfish (high performance towed undulator). FSDA were compared to classical statistical methods namely multivariate functional principal component analysis, classical prin-cipal component analysis, classification on principal component scores, classical additive model, spatial functional additive model. The interest to improve such statistical analysis is applied here to the study the effect at fine scale of environmental parameters on the distribution of coastal sound scattered layers. We first considered an aggregated analysis of the environmental data then we considered a more complete analysis of the data via their functional characters. specialized AFRIQUE DE L'OUEST ATLANTIQUE 032 040 ICES. Working Group of Fisheries Acoustics, Science and Technology (WGFAST), Somone (SEN), 2022/04/25-28 4 54 52 Jech M. (ed.). auteur aut IRD 2022 https://www.documentation.ird.fr/hor/fdi:010089775 [F B010089464] https://www.documentation.ird.fr/hor/fdi:010089775 https://horizon.documentation.ird.fr/exl-doc/pleins_textes/2024-03/010089775.pdf IRD - Base Horizon / Pleins textes 2024-02-15 2024-03-01 fdi:010089775 fre