scholarly journals Performance Analysis of Detector Algorithms Using Drone-Based Radar Systems for Oil Spill Detection

Proceedings ◽  
2018 ◽  
Vol 2 (7) ◽  
pp. 370 ◽  
Author(s):  
Bilal Hammoud ◽  
Ghaleb Faour ◽  
Hussam Ayad ◽  
Fabien Ndagijimana ◽  
Jalal Jomaah
Keyword(s):  
Performance Analysis ◽  
Oil Spill ◽  
Single Frequency ◽  
Dual Frequency ◽  
Statistical Characterization ◽  
Oil Spill Detection ◽  
Multiple Observations ◽  
Radar Systems ◽  
Sea Area

In this paper, we develop algorithms for oil spill detection using radar remote sensing. The algorithms take into account both the mathematical and the physical modeling of the sea surface covered by oil slicks. We use the statistical characterization of the power reflectivity and its distribution under various oil thicknesses and electromagnetic wave frequencies. We first introduce a single frequency (SF) oil spill detector that uses single or multiple observations (SO or MO) of power reflection coefficients over several scanning iterations for the sea area. Then, using Monte Carlo simulations we address the correctness of this detector by choosing different frequencies. Results show the inability of this detector to effectively distinguish between oil slicks and oil-free slicks for the total range of possible thicknesses. Nevertheless, increasing the number of observations leads to an increase in the effectiveness of the detector. An upgrade of this detector is the dual-frequency (DF) detector using single and multiple observations where two electromagnetic frequencies are used at the same time. Performance analysis of this detector proves its ability to overcome the drawbacks of the first detector by providing accurate detection especially for multiple observations.

Characterization of Stable and Transient Cavitation in a Dual-Frequency Acoustic Field Using a Hydrophone

MRS Advances ◽  
2016 ◽  
Vol 1 (31) ◽  
pp. 2247-2253
Author(s):  
Mingrui Zhao ◽  
Anfal Alobeidli ◽  
Xi Chen ◽  
Petrie Yam ◽  
Claudio Zanelli ◽  
...  
Keyword(s):  
Removal Efficiency ◽  
Low Frequency ◽  
Ultrasonic Field ◽  
Single Frequency ◽  
Particle Removal ◽  
Dual Frequency ◽  
Frequency Spectra ◽  
Calculated Ratio ◽  
Cavitation Pressure

ABSTRACTSonication is a commonly used method for particle removal from various surfaces. There has been a growing interest in the use of combination of two or more acoustic frequencies for cleaning as it is expected to achieve better particle removal efficiency and lower feature damage compared to a single frequency acoustic system. In this study, stable and transient cavitation characteristics in de-ionized water subjected to dual-frequency irradiation have been illustrated using experimentally obtained absolute values of cavitation pressures and pressure-frequency spectra. Comparison of the calculated ratio of stable cavitation pressure to transient cavitation pressure suggests that dual-frequency mode has the potential to reduce feature damage while maintaining the particle removal efficiency compared to low frequency ultrasonic field. These observations are further confirmed from the results of damage studies conducted on aluminum coated glass samples.

Dual-frequency oil spill detection algorithm

2017 ◽  
Author(s):  
Bilal Hammoud ◽  
Fatima Mazeh ◽  
Kassem Jomaa ◽  
Hussam Ayad ◽  
Fabien Ndagijimana ◽  
...  
Keyword(s):  
Oil Spill ◽  
Detection Algorithm ◽  
Dual Frequency ◽  
Oil Spill Detection

Application of Ground-based and Air/Spaceborne Radars for Oil Spill Detection in Sea Areas

1997 ◽  
Vol 51 (1) ◽  
pp. 1-8
Author(s):  
Ye. N. Belov ◽  
V. B. Yefimov ◽  
A. I. Kalmykov ◽  
I. A. Kalmykov ◽  
A. S. Kurekin ◽  
...  
Keyword(s):  
Oil Spill ◽  
Oil Spill Detection

scholarly journals Marine Oil Slick Detection Based on Multi-Polarimetric Features Matching Method Using Polarimetric Synthetic Aperture Radar Data

Sensors ◽  
2019 ◽  
Vol 19 (23) ◽  
pp. 5176
Author(s):  
Guannan Li ◽  
Ying Li ◽  
Bingxin Liu ◽  
Peng Wu ◽  
Chen Chen
Keyword(s):  
Computational Complexity ◽  
Synthetic Aperture Radar ◽  
Oil Spill ◽  
Similarity Measures ◽  
Synthetic Aperture ◽  
Matching Method ◽  
Polarimetric Synthetic Aperture Radar ◽  
Spectral Similarity ◽  
Oil Spill Detection ◽  
Aperture Radar

Polarimetric synthetic aperture radar is an important tool in the effective detection of marine oil spills. In this study, two cases of Radarsat-2 Fine mode quad-polarimetric synthetic aperture radar datasets are exploited to detect a well-known oil seep area that collected over the Gulf of Mexico using the same research area, sensor, and time. A novel oil spill detection scheme based on a multi-polarimetric features model matching method using spectral pan-similarity measure (SPM) is proposed. A multi-polarimetric features curve is generated based on optimal polarimetric features selected using Jeffreys–Matusita distance considering its ability to discriminate between thick and thin oil slicks and seawater. The SPM is used to search for and match homogeneous unlabeled pixels and assign them to a class with the highest similarity to their spectral vector size, spectral curve shape, and spectral information content. The superiority of the SPM for oil spill detection compared to traditional spectral similarity measures is demonstrated for the first time based on accuracy assessments and computational complexity analysis by comparing with four traditional spectral similarity measures, random forest (RF), support vector machine (SVM), and decision tree (DT). Experiment results indicate that the proposed method has better oil spill detection capability, with a higher average accuracy and kappa coefficient (1.5–7.9% and 1–25% higher, respectively) than the four traditional spectral similarity measures under the same computational complexity operations. Furthermore, in most cases, the proposed method produces valuable and acceptable results that are better than the RF, SVM, and DT in terms of accuracy and computational complexity.

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