Method to the oceanic bottom relief modelling using Artificial Neural Network

Abstract

The main purpose of this investigation is to generate a three-dimensional model of the ocean relief from bathymetric data, based on the concept of Artificial Neural Networks (ANN). The data used in the investigation were collected by “Polarstern” ship (AWI-Germany) with the multibeam system Hydrosweep DS-2. The area is located between Ireland an United Kingdom (Pelagia Province). In this first stage of the processings, as entrance variables for the training of the net, it was adopted the horizontal positions of the dephts (coordinates E, N); and also linear weights were attributed to the angles of incidence of the beams. In a second stage it was also used the horizontal coordinates E, N of a grid generated by the interpolation algorithm, the Inverse Distance to a Power. This way, the grids were to generalized by the net
in the same positions of the grid Inverse Distance to a Power which was adopted as being the reference model “field truth”, aiming at obtaining the RNA grid in the same positions of the Inverse Distance to a Power grid. The processing verifications
were made by qualitative and quantitative analyses, of the behavior of the interpolated depths and of the generalizen grids by the net. For such analyses it was used verification elements. The study shows that the proposed method is able to produce results that satisfy the precision of the equipament (multibeam), according to the manufacturer and also according to specifications of the International Organization of Hydrographic that indicates an aceptable error of being 17 m the maximum error allowed for this case. The ANN showed results with a maximum error of 14 m.