Application of Self-Organizing Maps at Change Detection in Amazon Forest

This paper presents a change detection of aerial images algorithm based on Kohonen self-organizing maps. In this study, a set of images from different period of time from Tapajós National Forest at Amazon forest in Pará, Brazil, has been employed. As input of the self-organizing maps, used as an unsupervised neural network, it was obtained features from the images using three different size of square windows and as output, a map of 16 colors, as 16 groupings. The results are obtained through the comparison between the outputs obtained with these different sizes of windows.