Forest and Water Bodies Segmentation Through Satellite Images Using U-Net

Abstract

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 as an element of global environment monitoring. To achieve this task UNet model has been proposed, which is an image segmentation model. Our model achieved a validation accuracy of 82.55% and 82.92% for the segmentation of areas covered by forest and water, respectively.