AIMC Topic: Petroleum Pollution
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A comparative study of fully automatic and semi-automatic methods for oil spill detection using Sentinel-1 data.
Environmental monitoring and assessment
Jun 26, 2025
The oil spill detection and assessment study conducted in the Banten Province of Indonesia involves the application of Sentinel-1 satellite data and machine learning tools in the year 2024. Synthetic Aperture Radar (SAR) data were used with VV polari...
A spatial interpolation method based on 3D-CNN for soil petroleum hydrocarbon pollution.
PloS one
Jan 24, 2025
Petroleum hydrocarbon pollution causes significant damage to soil, so accurate prediction and early intervention are crucial for sustainable soil management. However, traditional soil analysis methods often rely on statistical methods, which means th...
Enhancing shipboard oil pollution prevention: Machine learning innovations in oil discharge monitoring equipment.
Marine pollution bulletin
Sep 18, 2024
Maritime operations face significant challenges in environmental stewardship, particularly in managing oil discharges from tankers as mandated by the International Convention for the Prevention of Pollution from Ships (MARPOL) Annex I, Regulation 34....
Utilizing deep learning algorithms for automated oil spill detection in medium resolution optical imagery.
Marine pollution bulletin
Jul 30, 2024
This study evaluates the performance of three typical convolutional neural network based deep learning algorithms for oil spill detection using medium-resolution optical satellite imagery from Sentinel-2 MSI, Landsat-8 OLI, and Landsat-9 OLI2. Oil sl...
Marine oil spill detection and segmentation in SAR data with two steps Deep Learning framework.
Marine pollution bulletin
Jun 8, 2024
Marine oil spills pose significant ecological and economic threats worldwide, requiring effective decision-making tools. In this study, the optimal parameters, and configurations for Deep Learning models in oil spill classification and segmentation u...
Ocean oil spill detection from SAR images based on multi-channel deep learning semantic segmentation.
Marine pollution bulletin
Feb 1, 2023
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
Apr 29, 2022
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)
Nov 4, 2020
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)
Dec 2, 2019
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
Jun 3, 2019
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...
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