Identifying marine oil spills with hyperspectral, thermal and multispectral UAV imagery – capabilities and challenges (Invited Paper)

Remote sensing technologies have substantial potential in detecting marine oil spill incidents effective for emergency response and mitigation efforts. Offshore and onshore oil spill incidents remain underreported yet are frequently occurring and challenges remain around effective targeting of oil-type specific mitigation efforts. Here we demonstrate an approach of classifying imagery acquired from RGB, thermal, multi-spectral and hyperspectral data collected from UAV platforms of simulated oil spill incidents implemented in an outdoor environment. Each dataset was classified using SVM, RF and NN The methods are being compared and assessed for accuracy using Kappa coefficient. This paper demonstrates that combining the use of hyperspectral, multispectral and thermal infrared sensors proved to effectively improve the recognition accuracy of oil types in seawater which provide key insights about the oil spill incident necessary for mitigation efforts.