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Oil Spill Detection in Hybrid-Polarimetric SAR Images
IEEE Transactions on Geoscience and Remote Sensing, 2014Oil spill detection in SAR images operating in a hybrid-polarimetric mode is examined. We propose and review several strategies for oil spill detection in hybrid-polarimetric SAR data. The retrieved measures are successfully applied to SAR data covering oil spill experiments outside Norway and the Deepwater Horizon incident in the Gulf of Mexico. It is
Arnt-Børre Salberg +2 more
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Automatic detection of oil spills in ERS SAR images
IEEE Transactions on Geoscience and Remote Sensing, 1999The authors present algorithms for the automatic detection of oil spills in SAR images. The developed framework consists of first detecting dark spots in the image, then computing a set of features for each dark spot, before the spot is classified as either an oil slick or a "lookalike" (other oceanographic phenomena which resemble oil slicks).
Anne H. Schistad Solberg +3 more
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Field performance of a laser fluorosensor for the detection of oil spills
Applied Optics, 1980An airborne laser fluorosensor is described that was designed to detect and identify targets by means of the characteristic fluorescence emission spectrum. The first field trials of the sensor over marine oil and dye spills are reported. A correlation technique has been developed that, when applied to the data collected during these field trials ...
R A, O'Neil +2 more
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Oil Spill Detection in Radarsat and Envisat SAR Images
IEEE Transactions on Geoscience and Remote Sensing, 2007We present algorithms for automatic detection of oil spills in synthetic aperture radar (SAR) images. The algorithms consist of three main parts, namely: 1) detection of dark spots; 2) feature extraction from the dark spot candidates; and 3) classification of dark spots as oil spills or look-alikes. The algorithms have been trained on a large number of
Anne H. Schistad Solberg +2 more
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Method and Implementation of Oil Spill Detection in SAR Image
2012The Ocean is an important component part of the earth; it provides people the richest and the most valuable material resources. However, it is under various degrees of pollution every year. One of the most harmful pollution among them is the pollution by oil, and these oil pollutions are mainly come from ships oil leakage and explosions of oil ...
Zhuowei Hu, Lai Wei, Meichen Guo
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A multitemporal change detection solution to oil spill monitoring
2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 2016This paper develops a novel oil spill detection approach by using the multitemporal optical remote sensing images. Differently from the traditional oil spill detection methods that mainly carried out on a monotemporal image, the proposed approach opens a new perspective to solve the considered oil spill detection problem in a multitemporal domain by ...
Sicong Liu 0001 +3 more
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Satellite oil spill detection and monitoring in the optical range
2010 IEEE International Geoscience and Remote Sensing Symposium, 2010Timely detection and continuously updated information are fundamental in reducing oil spill environmental impact. In particular meteorological satellite, thanks to an high temporal resolution and to an easy data delivery, can be profitably used for a near real time sea monitoring.
Caterina Livia Sara Grimaldi +5 more
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Oil Spill Detection Technique with Automatic Updating Using Deep Learning and Oil Spill Index
IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium, 2023Dae-Woon Shin +2 more
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The application of laser‑induced fluorescence in oil spill detection
Environmental Science and Pollution ResearchOver the past two decades, oil spills have been one of the most serious ecological disasters, causing massive damage to the aquatic and terrestrial ecosystems as well as the socio-economy. In view of this situation, several methods have been developed and utilized to analyze oil samples.
Shubo Zhang +3 more
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Detection of Oil Spill Through Fully Convolutional Network
2018In this paper, a deep learning classification model is proposed for automatically detecting the marine oil spill in Lanset-7 and Lanset-8 images, which can combine fully convolutional network (FCN) with Resnet and Googlenet respectively. The classification algorithms, i.e. FCN-Googlenet and FCN-ResNet are compared to the state-of-the-art Support Vector
Yan Li 0040 +6 more
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