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

Selma Regina Aranha Ribeiro, Antonio Silva Centeno, Cláudia Pereira Krueger


In this article, we describe a methodology for the estimate of bathimetry using
satellite imagery (IKONOS II) based on the neural network approach. The input
variables of the model are the digital values of two spectral bands and the position
of the pixel, given by its N, E coordinates. The proposed model consists of an
artificial feed forward neural network with two hidden layers. The study reveals that
the proposed methodology is able to produce results that reach technical
specifications of Diretoria de Hidrologia e Navegação (DHN), in charge of for the
bathimetric surveys in Brazil, for class 1 surveys, as the maximum error lies bellow
0,5m. However, it was also verified that the methodology is effcient only for
restricted depths, from 0,80 to 3,00 meters, where the spectral response of the water
column prevails on the spectral response of the bottom and it is not strongly
affected by absorption.


Bathimetric survey; Artificial Neural Network; Bathimetry; Levantamentos Batimétricos; Redes Neurais Artificiais; Batimetria

Copyright (c)