  The Amazon rainforests have been suffering widespread damage, both via
natural and artificial means. Every minute, it is estimated that the world
loses forest cover the size of 48 football fields. Deforestation in the Amazon
rainforest has led to drastically reduced biodiversity, loss of habitat,
climate change, and other biological losses. In this respect, it has become
essential to track how the nature of these forests change over time. Image
classification using deep learning can help speed up this process by removing
the manual task of classifying each image. Here, it is shown how convolutional
neural networks can be used to track changes in land patterns in the Amazon
rainforests. In this work, a testing accuracy of 96.71% was obtained. This can
help governments and other agencies to track changes in land patterns more
effectively and accurately.
