Analysis on Adaptability of Monitoring Methods for Oil Spill by Using SAR Imagery

Abstract:

As is well known, the ocean plays a key role in global ecological environment. In this paper, we introduced the basic principle of monitoring oil spill by using SAR images. On the basis of that, we systematically analyzed the applicability of various methods for monitoring oil spill by using SAR images. The conclusion shows that the ANN method and the OTSU method have the advantages of timeliness and efficiency in oil spill monitoring, while the Markov Chain method cost more time due to its capability in reducing the effect of internal ocean wave.

• Periodical: Advanced Materials Research (Volumes 1030-1032)
• Pages: 1653-1656
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.1030-1032.1653
• Online since: September 2014
• Authors: Qi Yao*, Zhan Qiang Chang, Xiao Meng Liu, Li Yan Zhang, Chao Zhao
• Keywords: Oil Slick, Pollution Detection, Synthetic Aperture Radar

References

[1] J.B. An, Y.N. Zhang, The analysis of oil spill monitoring by use remote sensing in developed countries,. Environmental Protection in Transportation, Vol. 23 (2002), p.28– 30.

[2] W.J. Stringer, K.G. Dean, R.M. Guritz, H.M. Garbeil, J.E. Groves, K. Ahlnaes, Detection of Petroleum Spilled from the MV Exxon Valdez , International Journal of Remote Sensing, Vol. 13(1992), p.799– 824.

DOI: 10.1080/01431169208904155

[3] Z.Y. Yan, D.Q. Xiong, P.H. Duan, The reviewed of weathering of oil spill model, Journal of Dalian Maritime University, Vol. 27 (2001), p.36– 38.

[4] P. Sebastiao, S.C. Guedes, Modeling the Fate of Oil Spill at Sea, Spill Science & Technology Bulletin, Vol. 2(1995), p.121– 131.

DOI: 10.1016/s1353-2561(96)00009-6

[5] Y.N. Zhang，Q. Ding，C. Gao, The analysis of spectral characteristic of oil film and remote sensing monitoring oil film, Marine Environmental Science, Vol. 19 (2000), p.5–10.

[6] M. Marghany, Radarsat Automatic Algorithms for Detecting Coastal Oil Spill Pollution, Asian Journal of Geoinformatics, Vol. 3 (2001), p.191– 196.

DOI: 10.1016/s0303-2434(01)85011-x

[7] P. Trivero, B. Fiscella, F. Gomez, P. Pavese, SAR Detection and Characterization of Sea surface Slicks, International Journal of Remote Sensing, Vol. 19(1988), p.543– 548.

DOI: 10.1080/014311698216161

[8] Y.S. Yang Z.J. Zhang, A kind of suitable method for large oil spill sea segmentation by SAR image, Marine Environmental Science, Vol. 29(2010), pp.913-916.

[9] Frate F D, Salvatori L. Oil Spill Detection by means of Neural Networks,. IEEE(2004).

[10] OTSU N. A Threshold Selection Method from Gray-Level Histograms,. IEEE Transactions on Systems, Man, and Cybernetics, (1979).

DOI: 10.1109/tsmc.1979.4310076

[11] Y.L. Zhang, S.X. Zhu, G. Fu, The mathematical model of oil spill pollution and its application research,. Research of Environmental Sciences, Vol. 4 (1991), p.8– 9.

[12] H. Yang, B. Hong, S. Chen, The model of ocean oil spill and the application research, Transactions of Oceanology and Limnology, Vol. 2 (2007), p.157 – 160.

[13] A.Q. Yin X.C. Guo H.W. Guo, Markov chain in the application of the weather forecast, Journal of Shandong Agricultural University, Vol. 32(2001), p.191– 196.

[14] P. Daniel, The numerical simulation of the Aegean Sea ship oil spill,. Environmental Protection in Transportation, Vol. 16 (1995), p.45– 46.

[15] G. Mercier, S. Derrode, W. Pieczynski, Multiscale Oil Slick Segmentation with Markov Chain Model, IEEE(2003).

DOI: 10.1109/igarss.2003.1294834