Radar signatures of marine mineral oil spills measured by an airborne multi-frequency radar

Wismann, V.; Gade, Martin; Alpers, Werner; Hühnerfuß, Heinrich

doi:10.1080/014311698213849

Cited by 110 publications

(73 citation statements)

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“…13 Biogenic slicks are less likely to be present under wind conditions above 7-10 m/s because of entrainment. 13 Wisman et al 14 found the damping ratio to increase with oil thickness in a mineral oil slick, which is consistent with variability seen with UAVSAR during the Deepwater Horizon spill. 15 In the work reported here, the high spatial resolution of the UAVSAR data is used to measure variations in the damping ratio within the slicks (zoning) to determine whether areas of possible thicker oil are evident within the different slicks and for how long the zoning persists.…”

Section: Overviewsupporting

confidence: 57%

Characterization and discrimination of evolving mineral and plant oil slicks based on L-band synthetic aperture radar (SAR)

et al. 2016

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Evolution of the damping ratio for Bragg wavenumbers in the range 32-43 rad/m is evaluated for oil slicks of different composition released in the open ocean and allowed to develop naturally. The study uses quad-polarimetric L-band airborne synthetic aperture radar data acquired over three mineral oil emulsion releases of different, known oil-to-water ratio, and a near-coincident release of 2-ethylhexyl oleate that served as a biogenic look-alike. The experiment occurred during the 2015 Norwegian oil-on-water exercise in the North Sea during a period of relatively high winds (~12 m/s). NASA's Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) was used to repeatedly image the slicks over a period of eight hours, capturing the slicks' early development and providing a time series from which to track the evolution of the slicks' size, position, and radiometric characteristics. Particular emphasis is given in this analysis to identification of zones of higher damping ratio within the slicks (zoning) as potential indicators of thicker oil, and to comparison of the evolution of emulsion and plant oil damping ratios. It was found that all mineral oil slicks initially exhibited zoning apparent in VV, HH, and HV intensities, and that the areas of higher damping ratio persisted the longest for the highest oil content emulsion (80% oil by volume). In contrast, zoning was not unambiguously evident for plant oil at any time from 44 minutes to 8.5 hours after release.

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Section: Overviewsupporting

confidence: 57%

Characterization and discrimination of evolving mineral and plant oil slicks based on L-band synthetic aperture radar (SAR)

et al. 2016

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“…with increasing wind speed and to increase with frequency (Bragg wavenumber), oil viscosity, and thickness [41] [42]. The damping ratio is a function of the Bragg coefficients and the 2-D wavenumber spectral density of the ocean surface roughness [1].…”

Section: A Full-polarimetric Featuresmentioning

confidence: 99%

Analysis of Evolving Oil Spills in Full-Polarimetric and Hybrid-Polarity SAR

Espeseth

Skrunes

Jones

et al. 2017

IEEE Trans. Geosci. Remote Sensing

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Abstract-Oil spill detection using a time series of images acquired off Norway in June 2015 with the Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) is examined. The relative performance of a set of features derived from quadpolarization vs. hybrid-polarity modes in detection of various types of slicks as they evolve on a high wind driven sea surface is evaluated. It is shown that the hybrid-polarity mode is comparable to the full-polarimetric mode in its ability to distinguish the various slicks from open water for challenging conditions of high winds (9-12 m/s), small release volumes (0.2 -0.5m3 ), and during the period 0-9 hours following release. The features that contain the cross-polarization component are better for distinguishing the various slicks from open water at later and more developed stages. Although these features are not available in the hybrid-polarity mode, we identify alternative features to achieve similar results. In addition, a clear correlation between the results of individual features and their dependence on particular components within the two-scale Bragg scattering theory is identified. The features that show poor detectability of the oil slicks are those that are independent of the small-scale roughness, while the features resulting in good separability were dependent on several factors in the two-scale Bragg scattering model. We conclude that the hybrid-polarity mode is a viable alternative for SAR-based oil spill detection and monitoring that provides comparable results to those from quad-polarimetric SAR.

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“…SAR is widely used to identify and track pollutants in the sea, which may be due to secondary effect of a large natural disaster or by a manmade one (e.g., a ship wreck). The detection of oil spill by SAR imagery relies on the decreased backscattering from the sea surface, due to the increased viscosity, resulting in a dark formation that contrasts with the brightness of the surrounding area (Wismann, 1998). A common way of observing an oil spill event is by visual inspection, by skilled observers seeking for changes between past images and current images, or looking for spatial patterns (Jones, 2001).…”

Section: Introductionmentioning

confidence: 99%

Large Oil Spill Classification Using Sar Images Based on Spatial Histogram

Schvartzman

Havivi

Maman

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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Radar signatures of marine mineral oil spills measured by an airborne multi-frequency radar

Cited by 110 publications

References 0 publications

Characterization and discrimination of evolving mineral and plant oil slicks based on L-band synthetic aperture radar (SAR)

Characterization and discrimination of evolving mineral and plant oil slicks based on L-band synthetic aperture radar (SAR)

Analysis of Evolving Oil Spills in Full-Polarimetric and Hybrid-Polarity SAR

Large Oil Spill Classification Using Sar Images Based on Spatial Histogram

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