GICS-GA SERVICIO GRID DE CLASIFICACIÓN DE IMÁGENES LANDSAT QUE UTILIZA EL SISTEMA CLASIFICADOR INTELIGENTE XCS giCs-ga landsat image ClassiFiCatiOn grid serviCe tHat uses lear - ning ClassiFier sYstem XCs

This document describes the GICS-GA Project which explores the application of Grid technology to support training and research, through (the promotion of) a satellite image classification system to a Grid environment by a Grid Service implementation, which will be available by RENATA community through a Grid portal developed for this purpose. The advent of high-speed networks and the increasing development of communication technologies, have given a great impetus to grid computing, and have encouraged the comprising of scientific communities who would share resources both physical and knowledge even though those resources are spread geographically resources such as hardware, software, processing and storage [6]. One area that could benefit from this new infrastructure is related to the satellite images processing, and more specifically the classification process, taking into account the vast amount of processing and storage resources that this process requires. This document presents the results within the research project, consisting of implementing a Landsat images classification Grid Service that has the functionality defined by the standards of the Open Geospatial Consortium (OGC) and that for training and classification operations uses the Learning Classifier System XCS, which like most of the Learning Classifier Systems makes the use of genetic algorithms as evolutionary mechanism.