Tracking an Oil Tanker Collision and Spilled Oils in the East China Sea Using Multisensor Day and Night Satellite Imagery

Sun, Shaojie; Lu, Yingcheng; Liu, Yongchao; Wang, Mengqiu; Hu, Chuanmin

doi:10.1002/2018gl077433

Cited by 53 publications

(23 citation statements)

References 26 publications

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“…The spectra of very thick oil spills exhibited poor reflection when compared with the other types of oil spills; the thin oil spills showed high reflectance. This study suggests that the spectral bands 3 and 4 of MSI are best to use for image processing and discriminate oil spills [ 19 , [21] , [22] , [23] , [24] , [25] , [26] , [27] , [28] ]. The spectral bands acquired in these wavelengths by other satellites can also discriminate oil spills.…”

Section: Details Of Methodsmentioning

confidence: 99%

Sentinel-2 image transformation methods for mapping oil spill – A case study with Wakashio oil spill in the Indian Ocean, off Mauritius

et al. 2021

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Although several indices have been constructed and available at the Index database (IDB) for Sentinel-2 satellite to map and study several earth resources, no indices have been developed to map oil spill. We constructed band ratios (5 + 6)/7, (3 + 4)/2, (11+12)/8 and 3/2, (3 + 4)/2, (6 + 7)/5 using the high-resolution MSI (multi-spectral instrument) visible-near infrared-shortwave infrared spectral bands of Sentinel-2 by summing-up the bands representing the shoulders of absorption features as numerator and the band located nearest to the absorption feature as denominator to discriminate oil spill, and demonstrate the potential of this method to map the Wakashio oil spill which occurred in the Indian Ocean, off Mauritius. The resulted images discriminated the oil spill well. We also decorrelated the spectral bands 4, 3 and 2 by studying the spectral band absorptions and discriminated the spill as very thick, thick and thin. The results of decorrelation stretch method exhibited the distribution of types of oil spill in a different tone, distinctly. Both the image transformation methods (band ratios and decorrelation stretch methods) showed their capability to map oil spills, and these methods are recommended to use for similar spectral bands of other sensors to map oil spills. This study demonstrated the application of band ratios and decorrelation stretch methods to map oil spill. The methods discriminated the oil spill off Mauritius, and showed spill thicknesses from the Sentinel-2 data. The new methods are recommended to use for the spectral bands of other sensors to map oil spill.

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Section: Details Of Methodsmentioning

confidence: 99%

Sentinel-2 image transformation methods for mapping oil spill – A case study with Wakashio oil spill in the Indian Ocean, off Mauritius

et al. 2021

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“…The problem of large oil spills is well known-for example, there was a very large oil spill in the Gulf of Mexico in 2010. After that oil spill, various space-borne remote sensors were investigated as possibly suitable for oil detection or oil slick tracking [1][2][3][4][5][6]. Fortunately, there have been fewer oil spills lately.…”

Section: Introductionmentioning

confidence: 99%

Modelling the Visibility of Baltic-Type Crude Oil Emulsion Dispersed in the Southern Baltic Sea

2021

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This paper analyses the radiance reflectance modelling of a sea area and the case of a water column polluted with an oil emulsion in relation to various depths of the occurrence of an oil-in-water emulsion in all azimuth and zenith angles. For the radiance reflectance modelling, the simulation of large numbers of solar photons in water was performed using a Monte Carlo simulation. For the simulations, the optical properties of seawater for the open sea typical of the southern Baltic Sea were used and Petrobaltic-type crude oil (extracted in the Baltic Sea) was added. Oil pollution in the sea was considered for oil droplet concentrations of 10 ppm, which were optically represented by spectral waveforms of absorption and scattering coefficients, as well as by angular light scattering distribution determined using the Mie theory. The results of the radiance reflectance modelling in the whole spectrum of both angles, azimuth and zenith, allowed us to select 555 nm as the optimal wavelength for oil emulsion detection. Moreover, the parameter contrast was defined and determined using radiance reflectance results for eight light wavelengths in the range of 412-676 nm. The contrast is discussed in relation to the various thicknesses of polluted water layers. Changes in contrast for a thickness layer 5 m under the sea surface were noted, whereas for thicker layers the contrast remained unchanged.

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“…The path and position can also be built as a numerical model, with an average error from the origin < 15 km. While high-resolution optical images taken 4 days after the tanker sank show a much larger area of oil spill (> 350 km 2 ). In this case the VIIRS night data is the only satellite data that has proven effective in detecting the orbital drift and daily position of the ship, while all other sensor satellites can not observe or obscured.…”

Section: Introductionmentioning

confidence: 99%

Application of machine learning method–decision tree to classification of oil use sentinel 2

Doan¹,

Nguyen²,

Tran³

et al. 2021

VNJHM

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Decision tree classification algorithms have significant potential in classifying remote sensing data. This article's approach method using decision tree technology to classify remote sensing images with the representative object as oil spill. First, this paper discusses the algorithmic structure and algorithmic theory of the decision tree. Second, the build of decision tree classification algorithm with 10 branches for oil spill classification using Sentinel 2 image data based on the JavaScript application's online interface (API) called Code Editor. Decision tree technology has several advantages for remote sensing applications due to their relatively simple, clear and intuitive classification structure.

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Tracking an Oil Tanker Collision and Spilled Oils in the East China Sea Using Multisensor Day and Night Satellite Imagery

Cited by 53 publications

References 26 publications

Sentinel-2 image transformation methods for mapping oil spill – A case study with Wakashio oil spill in the Indian Ocean, off Mauritius

Sentinel-2 image transformation methods for mapping oil spill – A case study with Wakashio oil spill in the Indian Ocean, off Mauritius

Modelling the Visibility of Baltic-Type Crude Oil Emulsion Dispersed in the Southern Baltic Sea

Application of machine learning method–decision tree to classification of oil use sentinel 2

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