Open Journal Systems

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

Bilal Hammoud 1,2, Fabien Ndagijimana 2, Ghaleb Faour 3, Hussam Ayad 1, Majida Fadlallah 1, Jalal Jomaah 1

Article ID: 647
Vol 3, Issue 2, 2018, Article identifier:

VIEWS - 485 (Abstract) 273 (PDF)


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.


Oil spill; radar; reflection coefficient; reflectivity; dielectric constant; parameter extraction.

Full Text:


Included Database


ESA. Oil pollution monitoring. Remote Sensing Exploitation Division. p. 2, ESRIN- European Space Agency.

Laneve G, Luciani R. Developing a satellite optical sensor based automatic system for detecting and monitoring oil spills. Environment and Electrical Engineering (EEEIC), 2015 IEEE 15th International Conference on, pp. 1653–1658, IEEE, 2015.

Dan W, Jifeng S, Yongzhi Z, et al. Application of the marine oil spill surveillance by satellite remote sensing. Environmental Science and Information Application Technology, 2009. ESIAT 2009. International Conference on, vol. 1, pp. 505–508, IEEE, 2009.

Rocca F. Remote sensing from space for oil exploration. Geoscience and Remote Sensing Symposium (IGARSS), 2015 IEEE International, pp. 2876–2879, IEEE, 2015.

Minchew B, Jones CE, Holt B. Polarimetric analysis of backscatter from the deepwater horizon oil spill using l-band synthetic aperture radar. IEEE Transactions on Geoscience and Remote Sensing 2012; 50(10): 3812–3830.

Frost JD, Barnes CF. Assessment and enhancement of sar noncoherent change detection of sea-surface oil spills. IEEE Journal of Oceanic Engineering 2018; 43(1): 211–220.

Xu L, Wong A, Clausi DA. An enhanced probabilistic posterior sampling approach for synthesizing sar imagery with sea ice and oil spills. IEEE Geoscience and Remote Sensing Letters 2017; 14(2): 188–192.

Collins MJ, Denbina M, Minchew B, et al. On the use of simulated airborne compact polarimetric sar for characterizing oil–water mixing of the deepwater horizon oil spill. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 2015; 8(3): 1062–1077.

Hensley S, Jones C, Lou Y. Prospects for operational use of airborne polarimetric sar for disaster response and management. Geoscience and Remote Sensing Symposium (IGARSS), 2012 IEEE International, pp. 103–106, IEEE, 2012.

Lecomte E. En fevrier 2017, des drones vont traquer la pollution maritime, 2017.

Hammoud B, Mazeh F, Jomaa K, et al. Multi-frequency approach for oil spill remote sensing detection. High Performance Computing & Simulation (HPCS), 2017 International Conference on, pp. 295–299, IEEE, 2017.

Hammoud B, Mazeh F, Jomaa K, et al. Dual-frequency oil spill detection algorithm. Computing and Electromagnetics International Workshop (CEM) 2017, pp. 27–28, IEEE, 2017.

Skrunes S, Brekke C, Eltoft T. Oil spill characterization with multi-polarization c-and x-band sar. Geoscience and Remote Sensing Symposium (IGARSS), 2012 IEEE International, pp. 5117–5120, IEEE, 2012.

Marzialetti P, Laneve G. Oil spill monitoring on water surfaces by radar l, c and x band sar imagery: A comparison of relevant characteristics. Geoscience and Remote Sensing Symposium (IGARSS), 2016 IEEE International, pp. 7715– 7717, IEEE, 2016.

Jha MN, Levy J, Gao Y. Advances in remote sensing for oil spill disaster management: State-of-the-art sensors technology for oil spill surveillance. Sensors 2008; 8(1): 236–255.

Ulaby FT, Long DG, Blackwell WJ, et al. Microwave radar and radiometric remote sensing, vol. 4. University of Michigan Press Ann Arbor, 2014.

Vrba J, Vrba D. Temperature and frequency dependent empirical models of dielectric properties of sunflower and olive oil. Radioengineering 2013; 22(4): 1281–1287.

Maruska HP, Forster EO. Dielectric processes in heavy oils. Electrical Insulation & Dielectric Phenomena-Annual Report 1984, Conference on, pp. 334–342, IEEE, 1984.

Muntini MS, Pramono YH, Minarto E, et al. Modeling and simulation of microwave propagation on crude oil heating. Sensors, Instrumentation, Measurement and Metrology (ISSIMM), 2017 International Seminar on, pp. 46–50, IEEE, 2017.

(485 Abstract Views, 273 PDF Downloads)


  • There are currently no refbacks.

Copyright (c) 2018 Satellite Oceanography and Meteorology