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 …

In recent years, convolutional neural networks (CNNs) have drawn considerable attention
for the analysis of synthetic aperture radar (SAR) data. In this study, major subareas of SAR …

Oil spill discharges from operational maritime activities like ships, oil rigs and other
structures, leaking pipelines, as well as natural hydrocarbon seepage pose serious threats …

The visual similarity of oil slick and other elements, known as look-alike, affects the reliability
of synthetic aperture radar (SAR) images for marine oil spill detection. So far, detection and …

Despite the significant negative impact of marine pollution on the ecosystem and humans, its
automated detection and tracking from the broadly available satellite data is still a major …

Oil spills have caused serious harm to the marine environment. Remote sensing technology
is one of the important tools for marine environment monitoring. Synthetic aperture radar …

Colour-thresholding digital imaging methods are generally accurate for measuring the
percentage of foliar area affected by disease or pests (severity), but they perform poorly …

Coastal ecosystems offer substantial support and space for the sustainable development of
human society, and hence the ecological risk evaluation of coastal ecosystems is of great …

Oil spill accidents can cause severe ecological disasters; hence, the timely and effective
detection of oil spills on the marine surface is of great significance. Synthetic aperture radar …

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 …