A method for quantitative mapping of thick oil spills using imaging spectroscopy

Clark, R. N.; Swayze, Gregg A.; Leifer, Ira; Livo, Keith E.; Kokaly, Raymond F.; Hoefen, Todd M.; Lundeen, S.; Eastwood, Michael L.; Green, Robert O.; Pearson, N.; Sarture, Charles M.; McCubbin, Ian B.; Roberts, Dar A.; Bradley, Eliza S.; Steele, Denis; Ryan, Thomas; Dominguez, Roseanne

doi:10.3133/ofr20101167

Cited by 92 publications

(140 citation statements)

References 16 publications

Supporting

Mentioning

137

Contrasting

Order By: Relevance

“…The remote sensing effort of the NASA ER/2 equipped with Airborne Visible InfraRed Imaging Spectrometer (AVIRIS) surveyed about 30% of the core area of the surface spill on May 17, 2010. Extrapolating the examined area to the whole slick, Clark et al (2010) estimated that a minimum of floating oil of between 66,000 and 120,000 bbl. Limitations of the instruments do not allow measurement of very thick oil.…”

Section: Previous Experience -The Ixtoc Spillmentioning

confidence: 99%

Effects of Macondo Canyon 252 Oil (Naturally and Chemically Dispersed) on LarvalCrassostrea virginica(Gmelin, 1791)

Laramore

Krebs²,

Garr³

2014

Journal of Shellfish Research

View full text Add to dashboard Cite

Section: Previous Experience -The Ixtoc Spillmentioning

confidence: 99%

Effects of Macondo Canyon 252 Oil (Naturally and Chemically Dispersed) on LarvalCrassostrea virginica(Gmelin, 1791)

Laramore

Krebs²,

Garr³

2014

Journal of Shellfish Research

View full text Add to dashboard Cite

“…The goal when building the spectral libray was to reproduce the observations presented in (Clark et al, 2010) and to extend the measurements on other products. The library includes the transmittance and reflectance spectra of thin layers of seven mineral…”

Section: A Spectral Librarymentioning

confidence: 99%

“…Hyperspectral remote sensing has shown some interesting results in the VNIR range (400 to 1000nm) for a rough estimation of thickness and the evaluation of volume at sea using airborne sensors (Lennon et al, 2006, Otremba and Piskozub, 2004, Wettle et al, 2009. During the Deepwater Horizon oil spill, Clark et al (2010) have shown in (Clark et al, 2010) the high potential of hyperspectral data in the SWIR range (1000nm to 2500nm) for the estimation of high thickness ranges (over a millimetre) and emulsion rates. They proceed by associating shape parameters of reflectance spectra of the data to those from a spectral library.…”

Section: Introductionmentioning

confidence: 99%

Estimation of the Thickness and Emulsion Rate of Oil Spilled at Sea Using Hyperspectral Remote Sensing Imagery in the Swir Domain

Sicot¹,

Lennon²,

Miegebielle

et al. 2015

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

View full text Add to dashboard Cite

ABSTRACT:The thickness and the emulsion rate of an oil spill are two key parameters allowing to design a tailored response to an oil discharge. If estimated on per pixel basis at a high spatial resolution, the estimation of the oil thickness allows the volume of pollutant to be estimated, and that volume is needed in order to evaluate the magnitude of the pollution, and to determine the most adapted recovering means to use. The estimation of the spatial distribution of the thicknesses also allows the guidance of the recovering means at sea. The emulsion rate can guide the strategy to adopt in order to deal with an offshore oil spill: efficiency of dispersants is for example not identical on a pure oil or on an emulsion. Moreover, the thickness and emulsion rate allow the amount of the oil that has been discharged to be estimated. It appears that the shape of the reflectance spectrum of oil in the SWIR range (1000-2500nm) varies according to the emulsion rate and to the layer thickness. That shape still varies when the oil layer reaches a few millimetres, which is not the case in the visible range (400-700nm), where the spectral variation saturates around 200 µm (the upper limit of the Bonn agreement oil appearance code). In that context, hyperspectral imagery in the SWIR range shows a high potential to describe and characterize oil spills. Previous methods which intend to estimate those two parameters are based on the use of a spectral library. In that paper, we will present a method based on the inversion of a simple radiative transfer model in the oil layer. We will show that the proposed method is robust against another parameter that affects the reflectance spectrum: the size of water droplets in the emulsion. The method shows relevant results using measurements made in laboratory, equivalent to the ones obtained using methods based on the use of a spectral library. The method has the advantage to release the need of a spectral library, and to provide maps of thickness and emulsion rate values per pixel. The maps obtained are not composed of regions of thickness ranges, such as the ones obtained using discretized levels of measurements in the spectral library, or maps made from visual observations following the Bonn agreement oil appearance code.

show abstract

“…Work from Clark (Clark, 2010), Sicot (Sicot 2014) and others seem to indicate that the NIR-SWIR domains (0.7 -2.5 µm wavelength) offer better opportunities to detect and characterize thick oil slicks. This paper will focus on this domain.…”

Section: Introductionmentioning

confidence: 99%

Detection and Discrimination of the Thick Oil Patches on the Sea Surface

Dubucq

Sicot

Lennon³

et al. 2016

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

View full text Add to dashboard Cite

Commission VIII, WG VIII/5 KEY WORDS: Oil slick thickness, offshore slick, SWIR, VNIR, optical multispectral data, hyperspectral characterization, reflectance spectra ABSTRACT:Detection of natural or accidental oil slick at sea surface is important both for exploration purposes and for environment protection. Radar imagery, either satellite or airborne is the prime tool to detect those slicks. Radar is widely used by the national agencies to monitor their maritime areas for accidental pollutions or boat discharges. Radar images can detect oil slick even in the presence of clouds. However the sea surface back scattered energy is rather insensitive to oil thickness. On the contrary several studies tend to prove that optical data may be used to estimate the oil thickness. These data may be in the form of hyperspectral data or thermal infrared data. The objective of this study is to show that SWIR satellite data which are more widely available than hyperspectral data, better resolved than thermal data and available at a very limited cost, can be used to detect and qualitatively assess the thickness of oil slicks. This is important to assess volumes of naturally release oil in the oceans and in case of a crisis to send intervention teams where oil is thickest.

show abstract

A method for quantitative mapping of thick oil spills using imaging spectroscopy

Cited by 92 publications

References 16 publications

Effects of Macondo Canyon 252 Oil (Naturally and Chemically Dispersed) on LarvalCrassostrea virginica(Gmelin, 1791)

Effects of Macondo Canyon 252 Oil (Naturally and Chemically Dispersed) on LarvalCrassostrea virginica(Gmelin, 1791)

Estimation of the Thickness and Emulsion Rate of Oil Spilled at Sea Using Hyperspectral Remote Sensing Imagery in the Swir Domain

Detection and Discrimination of the Thick Oil Patches on the Sea Surface

Contact Info

Product

Resources

About