RBF network for spatial mapping of wave heights

Satellite-based information on significant waves is increasingly being made available to ocean scientists and engineers at low costs. While such measurements have a number of useful applications the manner with which the satellites sense the waves limits their applications to nearshore locations. This paper discusses an approach based on the radial basis function (RBF) type of artificial neural networks to map remote-sensed deep-water waves with the coastal waves. Significant wave heights at a number of locations over a track parallel to the coastline are used to estimate the significant wave heights at a nearshore site. The success of the method adopted was confirmed from the satisfactory error measures it produced during the testing carried out following the network training. It was also found that the satellite data need a 'local tuning' as done in the RBF before their further use in network computations. This work also highlighted importance of innovative approaches to calibrate a network on the basis of a given data set.