Multi-Frequency Approach for Oil Spill Remote Sensing Detection

Hammoud, Bilal; Mazeh, F.; Jomaa, Kassem; Ayad, Hussam; Ndadijimana, F.; Faour, Ghaleb; Fadlallah, M.; Jomaah, J.

doi:10.1109/hpcs.2017.53

Cited by 12 publications

(9 citation statements)

References 2 publications

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“…However, the periodicity of such signals would again disrupt detection for higher thickness levels (for example at d = 7.8 mm at 11 GHz). Here comes the idea of using algorithms where a combination of frequencies for the oil detection is implemented as developed [11,12] . we notice that although at different thickness values there exists some noticeable difference in reflectivity values at the same frequency for different dielectric constants.…”

Section: B Simulation Results Analysismentioning

confidence: 99%

“…Furthermore, although at high frequencies (11 and 12 GHz) the experimental values present the highest error (1 dB) from the theoretical value, this will not move the data to the region where it could be misinterpreted as oil-free region. is possible to perform oil spill detection that can be implemented using different advanced algorithms as mentioned in [11] and 12] . In addition, this technique may be used to remotely estimate the oil dielectric constant for material characterization, but this is beyond the scope of this journal.…”

Section: Methodsmentioning

confidence: 99%

“…The formula of the reflectivity (power reflection coefficient) for the three-layer structure is previously developed [11] . It is given by…”

Section: Theoretical Modelmentioning

confidence: 99%

“…dual and multi-frequency advanced algorithms that target oil spill detection for unknown oil thicknesses based on the statistical distribution of the reflectivity values [11,12] . The effectiveness of the approach was tested numerically using Monte-Carlo simulations, but to be able to move forward to prototypes and real applications, the results needed to be validated experimentally.…”

Section: Introductionmentioning

confidence: 99%

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Reflection-coefficient experimental extraction from S21- parameter for radar oil-spill detection application

Hammoud

Ndagijimana

Faour

et al. 2018

som

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Oil spill in sea water is one of the main accidents that affect significantly the maritime environment over a long period of time. Knowing the severe influence of oil spills on the ecosystem, it is crucial to have oil spill detecting and monitoring systems for quick intervention and danger containment. In our project, we propose the usage of drones as an oil spill detection system. The drones will be implementing different previously developed multi-frequency approaches for the detection. The effectiveness of such techniques is based on the accuracy of the data collected and their match to the theory. This journal presents a method for the remote extraction of reflection coefficients from multilayer structure modeling an oil spill in sea water. The experimental results for the reflectivity extraction validate the theoretical calculations and allow the implementation of different algorithms based on the statistical information taken directly from the site.

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Section: B Simulation Results Analysismentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

“…The formula of the reflectivity (power reflection coefficient) for the three-layer structure is previously developed [11] . It is given by…”

Section: Theoretical Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Reflection-coefficient experimental extraction from S21- parameter for radar oil-spill detection application

Hammoud

Ndagijimana

Faour

et al. 2018

som

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“…Hammoud et al studied oil spill detection as a possibility from a drone platform [12]. In examining the possibilities, they calculated the reflectivities of the microwave signals (i.e., radar) from slicks of various thicknesses.…”

Section: Microwave Reflectivitymentioning

confidence: 99%

The Challenges of Remotely Measuring Oil Slick Thickness

Fingas¹

2018

Remote Sensing

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The thickness of oil spills on the sea is an important but poorly studied topic. Means to measure slick thickness are reviewed. More than 30 concepts are summarized. Many of these are judged not to be viable for a variety of scientific reasons. Two means are currently available to remotely measure oil thickness, namely, passive microwave radiometry and time of acoustic travel. Microwave radiometry is commercially developed at this time. Visual means to ascertain oil thickness are restricted by physics to thicknesses smaller than those of rainbow sheens, which rarely occur on large spills, and thin sheen. One can observe that some slicks are not sheen and are probably thicker. These three thickness regimes are not useful to oil spill countermeasures, as most of the oil is contained in the thick portion of a slick, the thickness of which is unknown and ranges over several orders of magnitude. There is a continuing need to measure the thickness of oil spills. This need continues to increase with time, and further research effort is needed. Several viable concepts have been developed but require further work and verification. One of the difficulties is that ground truthing and verification methods are generally not available for most thickness measurement methods.

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