  Global environment monitoring is a task that requires additional attention in
the contemporary rapid climate change environment. This includes monitoring the
rate of deforestation and areas affected by flooding. Satellite imaging has
greatly helped monitor the earth, and deep learning techniques have helped to
automate this monitoring process. This paper proposes a solution for observing
the area covered by the forest and water. To achieve this task UNet model has
been proposed, which is an image segmentation model. The model achieved a
validation accuracy of 82.55% and 82.92% for the segmentation of areas covered
by forest and water, respectively.
