Surface oil footprint and trajectory of the Ixtoc-I oil spill determined from Landsat/MSS and CZCS observations

Sun, Shaojie; Hu, Chuanmin; Tunnell, John W.

doi:10.1016/j.marpolbul.2015.10.036

Cited by 50 publications

(32 citation statements)

References 21 publications

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“…Risk modeling suggests that an event the size of the Deepwater Horizon incident can be broadly predicted to occur on an interval between 8 and 91 years, or a rough average of once every 17 years (Eckle et al, 2012). Several major offshore oil blowouts have occurred, including the IXTOC-1 well in the Bahia de Campeche, Mexico where 3.5 million barrels of oil were released at a water depth of 50 m over 9 months (Jernelov and Linden, 1981;Sun et al, 2015) and the Ekofisk blowout where 200,000 barrels (32 million liters) of oil were released at a water depth of 70 m (Law, 1978). While all of these examples represent accidental discharges, the frequency at which they occur in offshore waters suggests that they can be expected during "typical" operations.…”

Section: Effects Of Accidental Dischargesmentioning

confidence: 99%

Environmental Impacts of the Deep-Water Oil and Gas Industry: A Review to Guide Management Strategies

Cordes

Jones

Schlacher

et al. 2016

Front. Environ. Sci.

277

170

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Section: Effects Of Accidental Dischargesmentioning

confidence: 99%

Environmental Impacts of the Deep-Water Oil and Gas Industry: A Review to Guide Management Strategies

Cordes

Jones

Schlacher

et al. 2016

Front. Environ. Sci.

277

170

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“…Due to the strong light absorption characteristic of clear water and crude oil at near‐infrared wavelengths [ Lammoglia and de Souza Filho , ; Wettle et al ., ], the backscattering radiance from oil or clear water was ignored in this study. Oil slicks are often observed in and around the sunglint region within various optical imagery of the sea surface [ Hu et al ., ; Jackson and Alpers , ; Lu et al ., ; Sun and Hu , ; Sun et al ., ]. When oil slicks or the seawater surface are illuminated by sunlight, the Fresnel reflection of the directly incident sunlight at the smooth surface can be described by Fresnel's law.…”

Section: Polarized Optical Model Of the Oil Slicksmentioning

confidence: 99%

“…[], and Lu et al . []), including optical sensors [ Chust and Sagarminaga , ; Giammona et al ., ; Hu et al ., ; Lu et al ., ; Sugioka et al ., ; Sun and Hu , ; Sun et al ., ], synthetic aperture radar (SAR) [ Brekke and Solberg , ; Garcia‐Pineda et al ., ; Hodgins et al ., ; Keramitsoglou et al ., ; Zheng et al ., ], thermal sensors [ Asanuma et al ., ; Cai et al ., ; Cross , ; Innman et al ., ; Leifer et al ., ; Lu et al ., ; Salisbury et al ., ; Tseng and Chiu , ], and laser fluorescence [ Brown et al ., ; Brown and Fingas , ]. These different technologies possess unique characteristics, theoretical bases, related data processing techniques, and quantitative remote sensing models.…”

Section: Introductionmentioning

confidence: 99%

“…Oil slicks on the ocean surface can be detected by employing multiple different types of remote sensing approaches (e.g., see the reviews by Brekke and Solberg [2005], Leifer et al [2012], and Lu et al [2013a]), including optical sensors [Chust and Sagarminaga, 2007;Giammona et al, 1995;Hu et al, 2003Hu et al, , 2009Lu et al, 2011Lu et al, , 2012Lu et al, , 2013aLu et al, , 2013bSugioka et al, 1999;Sun et al, 2015, synthetic aperture radar (SAR) [Brekke and Solberg, 2005;Garcia-Pineda et al, 2013;Hodgins et al, 1996;Keramitsoglou et al, 2006;Zheng et al, 2001], thermal sensors [Asanuma et al, 1986;Cai et al, 2007;Cross, 1992;Innman et al, 2010;Leifer et al, 2012;Lu et al, 2016b;Salisbury et al, 1993;Tseng and Chiu, 1994], and laser fluorescence [Brown et al, 1996;Brown and Fingas, 2003]. These different technologies possess unique characteristics, theoretical bases, related data processing techniques, and quantitative remote sensing models.…”

Section: Introductionmentioning

confidence: 99%

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Using remote sensing to detect the polarized sunglint reflected from oil slicks beyond the critical angle

Zhou

Liu

et al. 2017

JGR Oceans

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The critical angle at which the brightness of oil slicks and oil‐free seawater is reversed occurs under sunglint and is often shown as an area of uncertainty due to different roughness and surface Fresnel reflection parameters. Consequently, differentiating oil slicks from the seawater in these areas using optical sensors is a challenge. Polarized optical remote sensing techniques provide complementary information for intensity imagery with different physical properties and, thus, possess the ability to resolve this difficult problem. In the polarized reflectance model, the degree of linear polarization (DOLP) of sunglint depends on accurately knowing the Stokes parameter for the reflected light, and varies with the refractive index of the surface layer and viewing angles. For the polarized detection of oil slicks, the highest sensitivity of the DOLP to the refractive index is located within the specular reflection direction where the sum of the solar and sensor zenith angles is 82.6°. The modeled results clearly indicate that the DOLP of oil slicks is weaker in comparison with oil‐free seawater under sunglint. Using measurements from the space‐borne Polarization and Anisotropy of Reflectances for Atmospheric Sciences coupled with Observations from a Lidar (PARASOL) over the Deepwater Horizon oil spill in the Gulf of Mexico, we illustrate that the PARASOL‐derived DOLP difference between the oil spill and seawater is obvious and is in accordance with the modeled results. These preliminary results suggest that the potential of multiangle measurement and feasibility of deriving refractive index of ocean surface from space‐borne sensors need further researches.

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“…Remote sensing is a detection technology that can provide macro and dynamic observations and is not limited by geographical location and human factors, and is one of the most effective means to monitor the diffusion range and oil thickness following an oil spill [5][6][7]. Commonly used oil-spill monitoring technologies include the synthetic aperture radar [8], optical remote sensing [9], and laser fluorescence [10]. The synthetic aperture radar is widely used in oil-spill detection because of its all-day and all-weather capabilities [11].…”

Section: Introductionmentioning

confidence: 99%

Thermal Infrared Spectral Characteristics of Bunker Fuel Oil to Determine Oil-Film Thickness and API

Guo

Liu

2020

JMSE

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Remote sensing is an important method for monitoring marine oil-spill accidents. However, methods for measuring oil-film thickness remain insufficient. Due to the stable differences in the surface emissivity and temperature of oil and water, the oil film can be detected using thermal infrared. This study measured emissivity of seven different oil-film thicknesses and seven different American Petroleum Institute (API) densities, and analyzed the spectral characteristics. Results show an optimal wavelength position for oil-film thickness and fuel API density monitoring is 12.55 µm. Principal component analysis and continuum removal methods were used for data processing. Stepwise multiple linear regression was used to establish relationships between emissivity and oil slick thicknesses and API densities. Oil-film thickness and fuel API density data were analyzed by principal component analysis and continuum removal before regression analysis. The spectral emissivity data was convolved into Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) and Advanced Very High Resolution Radiometer (AVHRR) thermal bands to determine potential of the sensor in oil-film detection. The result shows that neither could be used to estimate thickness. The AVHRR-4 band and band 12 and 13 of the ASTER could be used to separate oils from water and have potential to distinguish different oil types. deficiencies in measuring fuel thickness [12]. Thermal infrared analysis distinguishes oil on the sea surface by thermal comparison. Because the emissivity of water and oil are different, thermal contrast is generated, and the emissivity depends on the thickness of the oil slick [15]. During the daytime, thick oil slicks become warmer than the surrounding water while thinner, detectable slicks appear cooler. This reverses at nighttime [16,17]. A thin film interference theory-based model is used to describe the thickness-dependent contrast between the background water and the sea surface covered by crude oil [18,19]. The thermal infrared emissivity of fuels was measured and analyzed using statistical methods [20][21][22]. At the same time, the different emission spectra of the fuels were detected, and a relationship between the fuel emissivity and the American Petroleum Institute (API) density was obtained.At present, thermal infrared technology is widely used in vegetation and soil detection. Among these [23], the relationship between the emissivity spectrum of the thermal infrared region and the leaf area index is obtained. The thermal infrared region is used to study soil moisture [24], and it has been proven that the long-wave infrared band is more accurate than visible-near infrared and shortwave infrared for the prediction of soil properties [25]. Some studies have applied thermal infrared technology to fuel-oil measurements, using regression analyses, to test the degree of soil oil pollution [26], and through experiments have identified midday as the optimal detection time for oil slicks [27]. The relationship between the...

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Surface oil footprint and trajectory of the Ixtoc-I oil spill determined from Landsat/MSS and CZCS observations

Cited by 50 publications

References 21 publications

Environmental Impacts of the Deep-Water Oil and Gas Industry: A Review to Guide Management Strategies

Environmental Impacts of the Deep-Water Oil and Gas Industry: A Review to Guide Management Strategies

Using remote sensing to detect the polarized sunglint reflected from oil slicks beyond the critical angle

Thermal Infrared Spectral Characteristics of Bunker Fuel Oil to Determine Oil-Film Thickness and API

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