Remote sensing technologies and machine learning (ML) algorithms play an increasingly
important role in accurate detection and monitoring of oil spill slicks, assisting scientists in …

Marine oil spills pose a significant threat to ocean and coastal ecosystems. In addition to
costs incurred by response activities, an economic burden could be experienced by …

Oil spill detection has attracted increasing attention in recent years, since marine oil spill
accidents severely affect environments, natural resources, and the lives of coastal …

The method's development to detect oil-spills, and concentration monitoring of marine
environments, are essential in emergency response. To develop a classification model, this …

Oil spills pose a major threat of the oceanic and coastal environments, hence, an automatic
detection and a continuous monitoring system comprises an appealing option for minimizing …

Oil spill pollution comprises a significant threat of the oceanic and coastal ecosystems. A
continuous monitoring framework with automatic detection capabilities could be valuable as …

Oil spill monitoring in optical remote sensing (RS) images is a challenging task due to the
complexity of target discrimination in an oil spill scenario. Differently from traditional oil spill …

In this work, a genetic algorithm is applied for the automatic detection of oil spills. The
procedure is implemented using sequences from RADARSAT-2 SAR ScanSAR Narrow …

Numerical oil spill models, which predict the transport and behavior of oil spills, are an
essential tool for risk assessment and clean-up during an actual accident. The existing …

Natural crude-oil seepages, together with the oil released into seawater as a consequence
of oil exploration/production/transportation activities, and operational discharges from …