Oil spill detection and mapping using deep learning (OSDMDL) is crucial for assessing its
impact on coastal and marine ecosystems. A novel approach was employed in this study to …

Oceans cover approximately 71% of the Earth's surface and provide numerous services to
the environment and humans. Precise, real-time, and large-scale monitoring of the …

Marine oil spills can cause severe damage to the marine environment and biological
resources. Using satellite remote sensing technology is one of the best ways to monitor the …

Oil spills are the main threats to marine and coastal environments. Due to the increase in the
marine transportation and shipping industry, oil spills have increased in recent years …

Oil spills cause tremendous damage to marine, coastal environments, and ecosystems.
Previous deep learning-based studies have addressed the task of detecting oil spills as a …

This paper presents an extensive evaluation of the Deep Image Prior (DIP) technique for
image inpainting on Synthetic Aperture Radar (SAR) images. SAR images are gaining …

Healthy coasts have a high ecological service value. However, many coastal areas are
faced with oil spill risks. The Synthetic Aperture Radar (SAR) remote sensing technique has …

In 1978, the SEASAT satellite was launched, carrying the first civilian synthetic aperture
radar (SAR). The mission was the monitoring of ocean: application to land was also studied …

With the rise of electronic data, particularly Earth observation data, data-based geospatial
modelling using machine learning (ML) has gained popularity in environmental research …

Awareness of the marine area is very important for crisis management in the event of an
accident. Oil spills are one of the main threats to the marine and coastal environments and …