AIMC Topic: Petroleum Pollution

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Ocean oil spill detection from SAR images based on multi-channel deep learning semantic segmentation.

Marine pollution bulletin
One of the major threats to marine ecosystems is pollution, particularly, that associated with the offshore oil and gas industry. Oil spills occur in the world's oceans every day, either as large-scale spews from drilling-rig or tanker accidents, or ...

A novel deep learning method for marine oil spill detection from satellite synthetic aperture radar imagery.

Marine pollution bulletin
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 to marine ecosystems and fisheries. Satellite synthetic aperture radar...

Concentration-Emission Matrix (CEM) Spectroscopy Combined with GA-SVM: An Analytical Method to Recognize Oil Species in Marine.

Molecules (Basel, Switzerland)
The establishment and development of a set of methods of oil accurate recognition in a different environment are of great significance to the effective management of oil spill pollution. In this work, the concentration-emission matrix (CEM) is formed...

Single spectral imagery and faster R-CNN to identify hazardous and noxious substances spills.

Environmental pollution (Barking, Essex : 1987)
The automatic identification (location, segmentation, and classification) by UAV- based optical imaging of spills of transparent floating Hazardous and Noxious Substances (HNS) benefits the on-site response to spill incidents, but it is also challeng...

Electrochemical inhibition bacterial sensor array for detection of water pollutants: artificial neural network (ANN) approach.

Analytical and bioanalytical chemistry
This work reports on further development of an inhibition electrochemical sensor array based on immobilized bacteria for the preliminary detection of a wide range of organic and inorganic pollutants, such as heavy metal salts (HgCl, PbCl, CdCl), pest...

Oil species identification technique developed by Gabor wavelet analysis and support vector machine based on concentration-synchronous-matrix-fluorescence spectroscopy.

Marine pollution bulletin
Concentration-synchronous-matrix-fluorescence (CSMF) spectroscopy was applied to discriminate the oil species by characterizing the concentration dependent fluorescence properties of petroleum related samples. Seven days weathering experiment of 3 cr...

The use of diagnostic ratios, biomarkers and 3-way Kohonen neural networks to monitor the temporal evolution of oil spills.

Marine pollution bulletin
Oil spill identification relies usually on a wealth of chromatographic data which requires advanced data treatment (chemometrics). A simple approach based on Kohonen neural networks to handle three-dimensional arrays is presented. A suite of 28 diagn...

Application of machine learning in microwave remediation of total petroleum hydrocarbon contaminated soil: Prediction and key factor identification.

Journal of environmental management
Microwave thermal remediation (TPH) is a promising remediation method for petroleum hydrocarbon contaminated soils due to its high energy efficiency and rapid heating capacity. However, the complexity of influencing factors and their nonlinear intera...

Evaluating marine environmental pollution using Fuzzy Analytic Hierarchy Process (FAHP): A comprehensive framework for sustainable coastal and oceanic management.

Marine pollution bulletin
Marine pollution poses a significant threat to ecosystems, biodiversity, and human health, necessitating a structured evaluation framework. This study applies the Fuzzy Analytic Hierarchy Process (FAHP) to prioritize five major marine pollution sourc...