Aplicação de métodos hidroacústicos na classificação textual do fundo marinho

This work shows a bathymetric mapping and a textural mapping using side scan sonar and sediment data of a sector of the continental shelf adjacent to Ponta Negra beach and Barreira D’água beach located at Natal /RN. The Bathymetric data were collected with different methodologies to calculating t...

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Autore principale: Pereira, Tiago Rafael de Barros
Altri autori: Vital, Helenice
Natura: Dissertação
Lingua:por
Pubblicazione: Brasil
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Accesso online:https://repositorio.ufrn.br/jspui/handle/123456789/25297
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Riassunto:This work shows a bathymetric mapping and a textural mapping using side scan sonar and sediment data of a sector of the continental shelf adjacent to Ponta Negra beach and Barreira D’água beach located at Natal /RN. The Bathymetric data were collected with different methodologies to calculating the depth: The direct wave and the interferometry. A comparative between these data was performed and the result showed different mean depth values. The interferometry methodology was used to map the entire study area. This mapping showed that the depht varies from 3m to 13m along the study area. The interpretation of bathymatric data allowed identify seafloor features such as: sand banks parallel to the shoreline, sand dunes and the rocky cluster. The interpretation of sonography data allowed identify 6 differents patterns of backscatter. Moreover in some cases was possible to correlate the seafloor features and the patterns of backscatter with the active hydrodynamic standard. Furthermore was done a comparative study between the automatic textural classification and the supervised textural classification using the backscatter data. This comparison is based on the sediment data using the granulometry features. The comparative show different results in the identification of backscatter’s patterns. The automatic textural classification identified 4 patterns while the supervised textural classification identified 6 patterns. The analysis of sediment data is in accordance with the supervised classification as have been identified six size fractions of sediment in the bottom samples.