Oil spill detection by satellite remote sensing

Brekke, Camilla; Solberg, Anne

doi:10.1016/j.rse.2004.11.015

Cited by 880 publications

(507 citation statements)

References 23 publications

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“…These may be low wind areas, shear zones, grease ice, upwelling, rain cells, biological films (surfactants), algae blooms or the internal and atmospheric gravity waves etc. The main problem in the identification of oil pollution is to discriminate these natural effects from the oil pollution (Brekke and Solberg 2005). For this purpose, the oil slick properties (shape, size, location relative to infrastructure, contrast, texture, form of the boundaries of slicks) can be used as well, as meteorological and oceanographic information or satellite data in the visible and infrared ranges .…”

Section: Envisat (Asar)mentioning

confidence: 99%

“…Oil and oil products come into the sea as a result of small accidents, routine manufacturing operations, illegal discharges from ships ballast and bilge water, fishing activity (fishery waste), as a result of washing tanks, river runoff, accidents involving oil tankers, or during the oil offshore exploration and production (Bernem and Lübbe 1997;Alpers 2002, Brekke andSolberg 2005). It should be noted that crude oil intrusion into the water is quite rare, as it only happens because of accidents on oil rigs and tankers, leaking pipelines as well natural seeps.…”

Section: Introductionmentioning

confidence: 99%

“…This distinguishes them from films, such as biological surfactants (produced by plankton and fish), that are able to spread monomolecular layers. This means that the more viscous and difficult oily mixture can be observed on radar images at higher wind speeds as well, while the surfactant films will disappear (Ivanov et al 2004a, b;Brekke and Solberg 2005).…”

Section: Introductionmentioning

confidence: 99%

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Oil spill detection in the Kazakhstan sector of the Caspian Sea with the help of ENVISAT ASAR data

et al. 2018

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Oil pollution in the world's oceans is predominantly caused by operational discharges from tankers (predominant oil dumped during cleaning operations). These discharges result in over 2 million tons of oil which are introduced annually comparable to one full-tanker disaster per week. Land-based sources such as urban waste and industrial discharges, which compass the ocean via rivers, are also a major contamination factor. The Caspian Sea is the largest inland water body on Earth without a direct connection to the world's oceans, which makes it a unique water reservoir. This fact makes the Caspian Sea particularly vulnerable and subject to human influence, for example, pollution from shipping activities and oil transports by ships. The research study shows results from a monitoring campaign in northern and central parts of the Caspian Sea (Kazakhstan sector) for the period from 2005 to 2012 (April-October), based on visual interpretation of radar images from ASAR ENVISAT. Radar data (529 radar images) such as ASAR_WSM_1P and ASAR_IM_1P were obtained from the archives of the European Space Agency. In 529 ASAR ENVISAT images, 160 images were selected, on which 329 oil spills were detected. Examples of individual slicks were analyzed by visual image interpretation. The total surface of contamination for the entire study period was estimated by 822.66 km 2 . The average size of the oil spills ranged from 1.09 to 10.62 km 2 , in different years. The monitoring of oil spills over the Kazakhstan sector of the Caspian Sea could show that it is possible to state with certainty that the main source of oil pollution is shipping (confirmed by analysis of slicks form and clusters along shipping routes) and the most contaminated area is its southern part, where there is more intensive navigation in the direction of Aktau-Baku (Azerbaijan), Aktau-Turkmenbashi (Turkmenistan), and Aktau-Neka (Iran). In the northern part of the Caspian Sea, it was determined that a low number of spills could have been caused by fishing and marine activities in the development area of the Kashagan oil field. The result is based on comparing the contamination map and the map of navigation, as well as through an analysis of the geometry of the slicks. Monitoring results largely coincided with the results of work carried out in the region, and at different times for some of its sites. These findings based on the radar data showed advantages of ASAR ENVISAT satellite monitoring for the control of oil pollution on the sea surface.

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Section: Envisat (Asar)mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Oil spill detection in the Kazakhstan sector of the Caspian Sea with the help of ENVISAT ASAR data

et al. 2018

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“…Yearly, 48 % of oil contamination in the oceans is due to fuels and 29 % by crude oil (Brekke and Solberg 2005). Annually, approximately 35 million barrels petroleum has been transport across the world which is an important source of oil contamination (Zaki et al 2015).…”

Section: Bioremediation Of Oilmentioning

confidence: 99%

Green remediation. Tool for safe and sustainable environment: a review

et al. 2016

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Nowadays, the bioremediation of toxic pollutants is a subject of interest in terms of health issues and environmental cleaning. In the present review, an ecofriendly, cost-effective approach is discussed for the detoxification of environmental pollutants by the means of natural purifier, i.e., blue-green algae over the conventional methods. Industrial wastes having toxic pollutants are not able to eliminate completely by existing the conventional techniques; in fact, these methods can only change their form rather than the entire degradation. These pollutants have an adverse effect on aquatic life, such as fauna and flora, and finally harm human life directly or indirectly. Cyanobacterial approach for the removal of this contaminant is an efficient tool for sustainable development and pollution control. Cyanobacteria are the primary consumers of food chain which absorbed complex toxic compounds from environments and convert them to simple nontoxic compounds which finally protect higher food chain consumer and eliminate risk of pollution. In addition, these organisms have capability to solve secondary pollution, as they can remediate radioactive compound, petroleum waste and degrade toxins from pesticides.

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“…SAR imagery has proved very effective for observing, measuring and quantifying oceanographic phenomena such as fronts, waves, eddies, winds, storms, oil spills, algae blooms, currents, and boundary layer rolls [1,2]. The ability of SAR sensors in retrieving data in almost all weather conditions, independently of sunlight surface, is extremely important for oceanographic studies.…”

Section: Introductionmentioning

confidence: 99%

Incidence angle normalization of Wide Swath SAR data for oceanographic applications

2016

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A backscattering trend in the range direction of the signal received by Synthetic Aperture Radar (SAR) in Wide Swath (WS) mode results in a progressive reduction of brightness over images from near to far range, which affects the detection and classification of sea surface features on wide swath SAR images. The aim of the present paper is to investigate methods for limiting the issue of Normalized Radar Cross-Section (NRCS or σ 0 ) variation due to the incidence angle. Two sensor independent functions are investigated: a theoretical backscattering shape function derived from a minimum wind speed and an empirical range fit of NRCS against incidence angle θ. The former method exploits only the modeled NRCS values while the latter only the image content. The results were compared with the squared cosine correction, the most widely applied method for normalization, using six newly developed comparison factors. The results showed that the cosine squared normalization has the lowest efficiency while the proposed methods have similar behaviors and comparable results. Nevertheless, after the log-transformation and summation of the comparison factors, it was clearly shown that theoretical normalization performance is superior to the empirical one since it has the highest accuracy and requires less computational time.

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Oil spill detection by satellite remote sensing

Cited by 880 publications

References 23 publications

Oil spill detection in the Kazakhstan sector of the Caspian Sea with the help of ENVISAT ASAR data

Oil spill detection in the Kazakhstan sector of the Caspian Sea with the help of ENVISAT ASAR data

Green remediation. Tool for safe and sustainable environment: a review

Incidence angle normalization of Wide Swath SAR data for oceanographic applications

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