HOW CAN NEURAL NETWORKS SPEED UP ECOLOGICAL REGIONALIZATION FRIENDLY?

摘要

The aim of this work is to present an application of the Radial Basis Functions Nets (RBFs) for simplifying and reducing the cost of ecological regionalization. The process speeds up and replaces the classic means of obtaining ecological variables through field studies. The radial basis function networks were applied to estimate field data remotely, using data captured by the Landsat satellite and correlating it with ecological variables in order to substitute for them in the regionalization process. This approach substantially reduces the time and cost of ecological regionalization, limiting field studies and automating the generation of the ecological variables. The technique could be applied without restriction to map vegetation in any other area for which satellite coverage exists.