Monitoring the deforestation of the Amazon region with neural networks

We deal with the problem of automating the interpretation of satellite images of the Amazon region for deforestation monitoring. Our approach is based on a combination of image segmentation and classification techniques, the latter employing a neural-network architecture that works on a fuzzy model of classification. The architecture implements a relaxation mechanism on top of a network trained by the backpropagation algorithm, in order to take advantage of the interrelations among neighboring image segments. Results obtained on varied portions of the Amazon region indicate a great potential for the automation of the monitoring task.