Oil Spill Detection and Visualization from UAV Images using Convolutional Neural Networks

Marine oil spills may have devastating consequences for the environment, the economy, and society. The 2019 oil spill crisis along the northeast Brazilian coast required immediate actions to control and mitigate the impacts of the pollution. In this paper, we propose an approach based on Deep Learning to efficiently inspect beaches and assist response teams using UAV imagery through an inexpensive visual system. Images collected by UAVs through an aerial survey are split and evaluated by a Convolutional Neural Network. The results are then integrated into heatmaps, which are exploited to perform geospatial visual analysis. Experiments were carried out to validate and evaluate the classifiers, achieving an accuracy of up to 93.6% and an F1 score of 78.6% for the top trained models. We also describe a case study to demonstrate that our approach can be used in real-world situations.