Skip to main content

Advertisement

Log in

A theoretical framework for optimal observability and detectability of spilled oil in aquatic environment

  • Theoretical Article
  • Published:
OPSEARCH Aims and scope Submit manuscript

Abstract

A departure from ecosystem quality objectives can be defined as effects, which may vary in magnitude and occur over different time scales. Some effects may be reversible while others may persist for long periods. Thus, compared with other sources of pollution in the oceans, the risk of crude oil spillage to the sea presents the major threat for the marine ecology. This study considers the combination of information from diverse sources relating to a similar endpoint in formulating an operational research model to tackle the problem of false alarm from the use of remote sensing in spill detection. A common rubric for this combination is to apply a meta-analysis. The term suggests a move past an analysis of standalone data to one incorporating and synthesizing information from many associated sources.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1

Similar content being viewed by others

References

  1. Bassey, K.J.: On optimality of marine oil spill pollution control. Int. J. Oper. Res. Optim. 2(2), 215–238 (2011)

    Google Scholar 

  2. Bassey, K.J., Chigbu, P.E.: On optimal control theory of marine oil spill management: a markovian decision approach. Eur. J. Oper. Res. 217(2), 470–478 (2012)

    Article  Google Scholar 

  3. Congalton, R.G.: A review of assessing the accuracy of classifications of remotely sensed data. Remote. Sens. Environ. 37, 35–46 (1991)

    Article  Google Scholar 

  4. Egberongbe, F.A.O., Nwilo, P.C. and Badejo, O.T. (2006): Oil spill disaster monitoring along Nigerian coastline. Promoting land administration and good governance, 5th FIG Regional Conference, Accra, Ghana:1-26

  5. Engelhardt, F.R.: Remote sensing for oil spill detection and response. Pure Appl. Chem. 71(1), 103–111 (1999)

    Article  Google Scholar 

  6. Fleming, W.H., Rishel, R.W.: Deterministic and stochastic optimal control, pp. 1–222. Springer, New York (1975)

    Book  Google Scholar 

  7. Gade, M., Alpers, W.: Using ERS-2 SAR images for routine observation of marine pollution in European coastal waters. Sci. Total Envir. 237–238, 441–448 (1999)

    Article  Google Scholar 

  8. Goodman, R. (1992): Client needs for surveillance and tracking during oil spill. In Proceedings of the First Thematic Conference: Remote Sensing For Marine And Coastal Environments, SPIE 1930: 69-78

  9. Hoveland, E., Johannessen, H.A. and Digranes, J.A. (1994): Slicks detection in SAR images. Proc. of IGARSS’99, Homburg, Germany

  10. Joel, J. (2004): Remote sensing. http://maps.unomaha.edu

  11. Johannessen, H.A., Digranes, J.A., Expedal, G., Samuel, O.M., Browne, P. and Vachon, D.P. (1994): SAR ocean feature catalogue. Esa-Sp-1174

  12. Keramitsoglou, I., Cartalis, C., Kiranoudis, C.: Automatic identification of oil spills on satellite images. Environ. Model. Softw. 21, 640–652 (2006)

    Article  Google Scholar 

  13. Karathanassi, V., Topouzelis, K., Pavlakis, P., Rokos, D.: An object-oriented methodology to detect oil spills. Int. J. Remote. Sens. 27, 5235–5251 (2006)

    Article  Google Scholar 

  14. Mansor, S.B., Assilzadeh, H., Ibrahim, H.M., Mohamed, A.R.: Oil spill detection and monitoring from satellite image. Spill Technol. Newsl. 15(3) (2010)

  15. Marghany, M., Shattri, M. and Ibrahim, Z.Z. (1996): On the application of radarsoft to extract infrastructure details from radarsat. Proc. Of Seminar: Malaysian Remote Sensing Society Conf. on Remote Sensing and GIS.,Lumpur

  16. Marghany, M.: RADARSAT for oil spill trajectory model. Environ. Model. Softw. 19, 473–483 (2004)

    Article  Google Scholar 

  17. Mercier, G., Girard-Ardhuin, F.: Partially supervised oil-slick detection by SAR imagery using kernel expansion. IEE Trans. Geosci. Remote Sens. 44(10), 2839–2846 (2006)

    Article  Google Scholar 

  18. Pavlakis, P. (1996): Investigation of the potential of ERS-1/2 SAR images for monitoring oil spills on the sea surface. Joint Research Centre, European Commission Report EUR 16351EN

  19. Redondo, J.M., Platonov, A.K.: Self-similar distribution of oil spills in european coastal waters. Environ. Res. Lett. 4, 1–10 (2009)

    Article  Google Scholar 

  20. Suter II, G.W.: Ecological risk assessment. Lewis Publishers, Chelsea (1993)

    Google Scholar 

  21. Topouzelis, K.N.: Oil spill detection by SAR images: dark formation detection, feature extraction and classification algorithms. Sensors 8, 6642–6659 (2008)

    Article  Google Scholar 

  22. Woodcock, C.E.: Uncertainty in remote sensing. In: Foody, G.M., Atkinson, P.M. (eds.) Uncertainty in remote sensing and GIS, pp. 18–24. John Wiley & Sons Ltd, Chichester (2002)

    Google Scholar 

  23. Xiaobo, C., Shanker, N.J., Wang, S.S.Y.: Development and application of oil spill model for singapore coastal waters. J. Hydraul. Eng. 129(7), 495–503 (2003)

    Article  Google Scholar 

  24. Xu, X., Pang, S.: Briefing of activities relating to the studies on environmental behaviour and economic toxicity of toxic organics. J. Environ. Sci. 4(4), 3–9 (1992)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Kufre J. Bassey.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Bassey, K.J. A theoretical framework for optimal observability and detectability of spilled oil in aquatic environment. OPSEARCH 49, 430–441 (2012). https://doi.org/10.1007/s12597-012-0090-5

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12597-012-0090-5

Keywords

Navigation