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. The main scope of this paper is the analysis of seafloor classification using acoustic remote sensing data. These data were acquired in a hydroacoustic survey of bathymetry and sonography using an interferometric swath bathymetry system. The study area is a sector of the internal northeast Brazilian shelf adjacent to the Ponta Negra beach - Natal (RN). The objective of the work is to identify and draw the different textural patterns, which characterize the seafloor of the study area. In addition, two approaches for textural classification of sonograms were compared and evaluated, which were: Automatic Gray Level Co-occurrence Matrix (GLCM) classification available in SonarWiz software; and the semi-automatic Maximum Likelihood, available in ArcGIS software. The comparison tested the capacity for identifying and drawing the textural patterns distribution. The automated classification identified 4 patterns while on the semi-automated 5 patterns were identified. It was made the correlation between the textural patterns found in each classification, besides the correlation between textural patterns and the levels of intensity of reflectance presents on the sonogram. Keywords: sonography, textural classification, textural patterns, hydroacoustic. RESUMO. Este trabalho foi realizado a partir da analise de dados geofisicos adquiridos em levantamento hidroacustico de batimetria e sonografia utilizando um sonar interferometrico EdgeTech 4600. A area de estudo e uma porcao da plataforma interna do nordeste brasileiro adjacente Natal (RN). O objetivo deste trabalho e identificar e delimitar os diferentes padroes texturais que caracterizam o substrato marinho da area de estudo. Adicionalmente, sao avaliadas e comparadas duas abordagens distintas de classificacao textural de sonogramas, sendo elas: a classificacao automatica GLCM disponivel no software SonarWiz, e a classificacao semi-automatica maxima verossimilhanca (Maximum Likelihood) disponivel no software ArcGIS. A comparacao foi realizada com base na capacidade de identificacao e delimitacao da distribuicao dos padroes texturais. A utilizacao da classificacao automatica identificou 4 padroes, enquanto que, na classificacao semi-automatica 6 padroes foram identificados. Foi feita a correlacao entre os padroes texturais encontrados em cada classificacao, alem da correlacao entre os padroes texturais e os niveis de intensidade de reflectância presente no sonograma. Palavras-chave: sonografia, classificacao textural, padroes de textura, hidroacustica.

COMPARISON OF AUTOMATIC AND SEMI-AUTOMATIC METHODS FOR CLASSIFICATION OF SIDE SCAN SONAR IMAGERY