Automatic delimitation of volcanic ash in satellite images using Deep Learning
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Abstract
Artificial Intelligence has had a big impact in recent years, this field of Informatics is increasingly used to solve geological problems. One of the main applications is the detection and segmentation of volcanic ash in satellite images. For this purpose, we propose a Deep Learning model based on a Convolutional Neural Network (CNN), trained with a satellite image dataset where the "ash" filter is applied, which provides a reddish-pink coloration to the ash, facilitating the segmentation process. The results show an accuracy of 99%, which is suitable for the segmentation of the ash emitted by Sangay Volcano, which has presented periods of volcanic activity in recent years. Our model generated segmented images that are consistent with the studies published by the IG-EPN.
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