An estimate of depth from a bathimetric survey and IKONOS II data by means of artifitial neural network

• Autor(a) principal: Ribeiro, Selma Regina Aranha
• Data de Publicação: 2008
• Outros Autores: Centeno, Antonio Silva, Krueger, Cláudia Pereira
• Tipo de documento: Artigo
• Idioma: por
• Título da fonte: Boletim de Ciências Geodésicas
• Texto Completo: https://revistas.ufpr.br/bcg/article/view/11814
• topic: Bathimetric survey; Artificial Neural Network; Bathimetry; Levantamentos Batimétricos; Redes Neurais Artificiais; Batimetria

In this article, we describe a methodology for the estimate of bathimetry usingsatellite imagery (IKONOS II) based on the neural network approach. The inputvariables of the model are the digital values of two spectral bands and the positionof the pixel, given by its N, E coordinates. The proposed model consists of anartificial feed forward neural network with two hidden layers. The study reveals thatthe proposed methodology is able to produce results that reach technicalspecifications of Diretoria de Hidrologia e Navegação (DHN), in charge of for thebathimetric surveys in Brazil, for class 1 surveys, as the maximum error lies bellow0,5m. However, it was also verified that the methodology is effcient only forrestricted depths, from 0,80 to 3,00 meters, where the spectral response of the watercolumn prevails on the spectral response of the bottom and it is not stronglyaffected by absorption.