Results 51 to 60 of about 42,245 (206)
In this paper, infrared polarization detection information acquisition technology is proposed, and the polarization characteristics of oil spills are modeled and studied.
Hongyu Sun +8 more
doaj +1 more source
An object‐oriented methodology to detect oil spills
A new automated methodology for oil spill detection is presented, by which full synthetic aperture radar (SAR) high‐resolution image scenes can be processed. The methodology relies on the object‐oriented approach and profits from image segmentation techniques to detected dark formations.
KARATHANASSI Vassilia +3 more
openaire +2 more sources
Detection and quantification of oil under sea ice : the view from below [PDF]
© The Author(s), 2014. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Cold Regions Science and Technology 109 (2015): 9-17, doi:10.1016/j.coldregions.2014.08.004 ...
Boyd, Tim +7 more
core +1 more source
Multi-source knowledge graph reasoning for ocean oil spill detection from satellite SAR images
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 sea surface in near real-time to obtain oil spill information.
Xiaojian Liu +7 more
doaj +1 more source
Remote sensing monitoring of oil spills is essential for ecological and environmental management. Polarimetric synthetic aperture radar (PolSAR) data have been extensively utilized for oil spill detection owing to the advantages of multi-polarization ...
Dongmei Song +5 more
doaj +1 more source
Bioaccumulation surveillance in Milford Haven Waterway [PDF]
Biomonitoring of contaminants (metals, organotins, PAHs, PCBs) was carried out along the Milford Haven Waterway (MHW) and at a reference site in the Tywi Estuary during 2007-2008. The species used as bioindicators encompass a variety of uptake routes -
Davey, M. +8 more
core +1 more source
Large-Scale Detection and Categorization of Oil Spills from SAR Images with Deep Learning
We propose a deep-learning framework to detect and categorize oil spills in synthetic aperture radar (SAR) images at a large scale. Through a carefully designed neural network model for image segmentation trained on an extensive dataset, we obtain state ...
Filippo Maria Bianchi +2 more
doaj +1 more source
Given that the recent rapid growth of offshore production, especially in the Arctic region of the Russian Federation, is causing increased concern about oil spills on the water surface, this issue is especially relevant and important today.
Artem Alekseevich Khalturin +2 more
doaj +1 more source
Oil Spill Detection And Contingency Planning Using Radar Imagery and GIS [PDF]
Shipping casualties often resulted in serious accidental spills as experienced in the Straits of Malacca in the past decade. Operational remote sensing and geographic information system (GIS) are important tools for oil spill research and development ...
Assilzadeh, Hamid
core
Marine oil spill pollution has caused serious impacts on marine ecological environments, ecological resources and marine economy. Synthetic Aperture Radar (SAR), especially polarmetric SAR (PolSAR), has been proven to be a powerful and efficient tool for
Dongmei Song +7 more
doaj +1 more source

