Amazon rainforest has been subject to intensive deforestation in the last decades, for example, illegal logging and creating pasture areas. A characteristic pattern of deforestation seen from space is the “fishbone” shape, which usually appears near roads, rivers and its tributaries. Indeed, others, more subtle, still need to be identified. These fishbone images are spatiotemporal patterns that need to be more explored with feature extraction methods. In computer vision, morphological features such as flatness, compactness, circularity, perimeter, area, and centroid are well-known to characterize the appearance of an object. In this work, we aim to characterize the shapes of deforestation in its early stages and its evolution in time, particularly in the Amazon rainforest. Thus, we propose to analyze satellite images of these regions to crop and segment by using shape features.