MODIS Based Spectral and Texture Integration Oil Spill Detection Method

  • 1. Key Laboratory of Coastal Zone Environmental Processes, Yantai Institute of Coastal Zone Research(YIC), CAS, Shandong Provincial Key Laboratory of Coastal Zone Environmental Processes, YICCAS, Yantai Shandong 264003, China;
    2. State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China;
    3. Graduate University of Chinese Academy of Sciences, Beijing 100049, China

Received date: 2013-08-28

  Revised date: 2013-09-22

  Online published: 2014-03-10


Marine oil spill detection has become a worldwide issue. Traditional oil spill detection algorithm only depended on the spectral or texture has low detection accuracy. This paper presents a new method of the oil spill detection based on spectral and texture from optical remote sensing data. The spectral feature is oil slick sensitive band of the optical remote sensing data and the texture feature is got by gray level co-occurrence matrix. The model used support vector machine method to establish the spectrum and texture oriented oil spill detection method with these features. This paper used the MODIS optical remote sensing data to detect the oil spill in China Bohai Sea in 2006. The oil spill information can be shown on this band clearly because the variance of the sea water spectrum is less than the contrast of oil-water spectrum in the MODIS band 2, so we called the MODIS band 2 is the oil slick sensitive band, which we selected as the spectral feature. We obtained eight texture eigenvalues of oil slick and sea by gray level co-occurrence matrix in the MODIS band 2. Then three texture eigenvalues include mean, contrast and correlation were selected by analysis. Based on the selected sample, the detection accuracy was up to 91.32% and the Kappa coefficient is 0.7125. In contrast with spectral and texture integration Maximum Likelihood method and SVM method only use the spectral feature, the detection method we proposed is superior to these methods. The results showed that the method to combine the spectral feature and textural feature of MODIS data can effectively extract the oil slick in the Bohai Sea, and has a strong ability to suppress noise.

Key words: MODIS; oil spill; SVM; spectral; texture

Cite this article

SU Weiguang, SU Fenzhen, DU Yunyan . MODIS Based Spectral and Texture Integration Oil Spill Detection Method[J]. Journal of Geo-information Science, 2014 , 16(2) : 299 -306 . DOI: 10.3724/SP.J.1047.2014.00299


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