Review of oil spill remote sensing

Fingas, Mervin F.; Brown, Carl E.

doi:10.1016/s1353-2561(98)00023-1

Cited by 223 publications

(129 citation statements)

References 17 publications

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“…Thus, the calming effect of oil can be confused with low-wind areas. In addition, other naturally occurring phenomena, including biogenic surfactants, can cause dark areas in SAR imagery and produce false positives (i.e., areas that look like oil but are not) [Fingas and Brown, 1997;Nunziata et al, 2009].…”

Section: Polarimetric Sar Observationmentioning

confidence: 99%

Polarimetric synthetic aperture radar utilized to track oil spills

et al. 2012

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The continued demand for crude oil and related petroleum products along with the resulting upward spiral of the market price of oil have forced oil exploration and production companies to seek out new reserves farther offshore and in deeper waters. The United States is among the top five nations globally in terms of estimated offshore oil reserves and petroleum production. Yet deepwater drilling to extract these reserves is a major engineering challenge for oil companies. Moreover, such drilling activity also comes with a significant environmental risk, and the extremely high pressures associated with deepwater oil wells mean that the mitigation of accidental releases from a deepwater spill is truly a challenging endeavor.

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Section: Polarimetric Sar Observationmentioning

confidence: 99%

Polarimetric synthetic aperture radar utilized to track oil spills

et al. 2012

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“…The Landsat technology was the first remote sensing method adopted in the analysis of hydrocarbons however, with improvements in technology, the microwave technology became a more preferred remote sensing method. Active microwave sensors like Synthetic Aperture Radars (SAR) capture two-dimensional images of oils [18][19]. Prior studies reveal that ultraviolet (UV) ranges of the spectrum have shown a wider geological application [20][21][22], although its major challenge lies in the intense absorption of UV radiation by the atmosphere i.e.…”

Section: Introductionmentioning

confidence: 99%

Thermal Infrared Remote Sensing of Hydrocarbon in Lagos- Southern Nigeria: Application of the Thermographic Model

Emetere¹

2017

GEOMATE

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ABSTRACT:The paper presents a technique for investigating remote sensing imagery to explore hydrocarbon sites, oil traps and spills. This research adopts a model approach to oil exploration against conventional or traditional methods. The model used here is the Environmental Thermographic Model (ETM). Key parameters such as surface emissivity, surface temperature, long wave radiation and geological mapping which constitute the model were used alongside data generated from the Moderate Resolution Imaging Spectro-radiometer (MODIS) in order to identify the location of prospective oil or gas reservoir in Lagos-Southern Nigeria. MODIS data generated over a period of ten years was analyzed. The ETM model and a temperature polynomial expansion scheme (TPES) were used to validate the remote sensing data by using calculated surface emissivity and long wave technique. Two thermal infrared sources were deployed to aid oil field investigations. The consistency of the Landsat 8 OLI and ETM imagery further confirms the reliability of the method in determining the characteristics of the hydrocarbon habitat, as well as the lineaments.

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“…There is an increasing need for monitoring large oil spills, estimating the location and extent of the spill (Fingas & Brown, 1997;Fingas & Brown, 2014). Remote sensing is an important part of oil spill response, as oil spills can be monitored on the open sea or ocean on a 24h basis (Fingas & Brown, 2014).…”

Section: Introductionmentioning

confidence: 99%

Large Oil Spill Classification Using Sar Images Based on Spatial Histogram

Schvartzman¹,

Havivi²,

Maman³

et al. 2016

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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Commission VIII, WG VIII/9KEY WORDS: Non-linear filter, Unsupervised Automatic Classification, Natural Hazards ABSTRACT:Among the different types of marine pollution, oil spill is a major threat to the sea ecosystems. Remote sensing is used in oil spill response. Synthetic Aperture Radar (SAR) is an active microwave sensor that operates under all weather conditions and provides information about the surface roughness and covers large areas at a high spatial resolution. SAR is widely used to identify and track pollutants in the sea, which may be due to a secondary effect of a large natural disaster or by a man-made one . The detection of oil spill in SAR imagery relies on the decrease of the backscattering from the sea surface, due to the increased viscosity, resulting in a dark formation that contrasts with the brightness of the surrounding area. Most of the use of SAR images for oil spill detection is done by visual interpretation. Trained interpreters scan the image, and mark areas of low backscatter and where shape is a-symmetrical. It is very difficult to apply this method for a wide area. In contrast to visual interpretation, automatic detection algorithms were suggested and are mainly based on scanning dark formations, extracting features, and applying big data analysis. We propose a new algorithm that applies a nonlinear spatial filter that detects dark formations and is not susceptible to noises, such as internal or speckle. The advantages of this algorithm are both in run time and the results retrieved. The algorithm was tested in genesimulations as well as on COSMO-SkyMed images, detecting the Deep Horizon oil spill in the Gulf of Mexico (occurred on 20/4/2010). The simulation results show that even in a noisy environment, oil spill is detected. Applying the algorithm to the Deep Horizon oil spill, the algorithm classified the oil spill better than focusing on dark formation algorithm. Furthermore, the results were validated by the National Oceanic and Atmospheric Administration (NOAA) data.

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Review of oil spill remote sensing

Cited by 223 publications

References 17 publications

Polarimetric synthetic aperture radar utilized to track oil spills

Polarimetric synthetic aperture radar utilized to track oil spills

Thermal Infrared Remote Sensing of Hydrocarbon in Lagos- Southern Nigeria: Application of the Thermographic Model

Large Oil Spill Classification Using Sar Images Based on Spatial Histogram

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