Environmental monitoring and assessment
Oct 16, 2025
Marine oil spills pose severe threats to marine ecosystems, where rapid and accurate oil spill region segmentation is crucial for emergency response to disasters. Synthetic Aperture Radar (SAR), with its all-weather and day-night observation capabili...
Environmental monitoring and assessment
Sep 26, 2025
The Niger Delta region of Nigeria is a major oil-producing area which experiences frequent oil spills that severely impacts the local environment and communities. Effective environmental monitoring and management remain inadequate in this area due to...
Environmental monitoring and assessment
Jul 28, 2025
This study aims to evaluate the applicability of existing machine learning and deep learning techniques for the rapid prediction of hydrocarbon contamination in soils using hyperspectral data. Soil samples of three types, i.e., clayey, silty, and san...
Oil spills pose a serious threat to marine communities, and there is an urgent need for an effective technique to monitor and assess the impacts on biological communities. While traditional methods with low sensitivity, being time-consuming and limit...
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...
Ecotoxicology and environmental safety
Jun 21, 2025
With the intensification of oil extraction activities, total petroleum hydrocarbons (TPHs) and toxic elements contamination in soil around oil wells have become severe environmental problems. This paper proposed a novel method based on machine learni...
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...
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....
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 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...
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