Method and Implementation of Oil Spill Detection in SAR Image

  • Zhuowei Hu
  • Lai Wei
  • Meichen Guo
Part of the Advances in Intelligent and Soft Computing book series (AINSC, volume 133)

Abstract

The Ocean is an important component part of the earth; it provides people the richest and the most valuable material resources. However, it is under various degrees of pollution every year. One of the most harmful pollution among them is the pollution by oil, and these oil pollutions are mainly come from ships oil leakage and explosions of oil platforms or submarine pipelines etc. The direct economic losses of each time accidents caused could be millions or tens of millions of upper and lower, so the action of monitoring oil leakage with regard to the ocean becomes significantly important. This paper aims the monitoring of oil leakage of the ocean which based on the ASAR DATA of ENVISAT remote sensing data. It contains introductions to the basic steps and implementations of monitoring oil leakage by SAR image, and also analysis of them. By comparing different methods of filtering, the enhanced Lee filter is ultimately been selected and settled as the filtering method, and then we extract and contract the area of oil leakage by using single threshold method, maximum entropy method and unsupervised classification method respectively. Finally, we bring up the developmental direction of oil spill detection in SAR image.

Keywords

SAR filter enhanced Lee oil spill detection single threshold maximum entropy unsupervised classification 

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References

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Copyright information

© Springer-Verlag GmbH Berlin Heidelberg 2012

Authors and Affiliations

  • Zhuowei Hu
    • 1
    • 2
    • 3
  • Lai Wei
    • 1
    • 2
    • 3
  • Meichen Guo
    • 1
    • 2
    • 3
  1. 1.College of Resources Environment and TourismCapital Normal UniversityBeijingChina
  2. 2.Lab of Resources Environment and GISBeijingChina
  3. 3.Key Lab of Integrated Disaster Assessment and Risk Governance of the Ministry of Civil AffairsBeijingChina

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