Title | ||
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Ocean Oil Spill Classification with RADARSAT-2 SAR Based on an Optimized Wavelet Neural Network. |
Abstract | ||
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Oil spill accidents from ship or oil platform cause damage to marine and coastal environment and ecosystems. To monitor such spill events from space, fully polarimetric (Pol-SAR) synthetic aperture radar (SAR) has been greatly used in improving oil spill observation. Aiming to promote ocean oil spill classification accuracy, we developed a new oil spill identification method by combining multiple fully polarimetric SAR features data with an optimized wavelet neural network classifier (WNN). Two sets of RADARSAT-2 fully polarimetric SAR data are applied to test the validity of the developed method. The experimental results show that: (1) the convergence ability of optimized WNN can be enhanced, improving overall classification accuracy of ocean oil spill, in comparison to the classification results based on a common un-optimized WNN classifier; and (2) the joint use of the multiple fully Pol-SAR features as the inputs of the classifier can achieve better classification result than that only with single fully Pol-SAR feature. The developed method can improve classification accuracy by 4.96% and 7.75%, compared with the classification results with un-optimized WNN and only with one single fully polarimetric SAR feature. The classification overall accuracy based on the proposed approach can reach 97.67%. Experimental results have proven that the proposed approach is effective and applicable to classify the ocean oil spill. |
Year | DOI | Venue |
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2017 | 10.3390/rs9080799 | REMOTE SENSING |
Keywords | Field | DocType |
oil spill,wavelet neural network,fully polarimetric SAR,RADARSAT-2 | Convergence (routing),Wavelet neural network,Oil spill,Polarimetry,Synthetic aperture radar,Remote sensing,Polarimetric sar,Classifier (linguistics),Geology | Journal |
Volume | Issue | ISSN |
9 | 8 | 2072-4292 |
Citations | PageRank | References |
3 | 0.42 | 25 |
Authors | ||
5 |
Name | Order | Citations | PageRank |
---|---|---|---|
Dongmei Song | 1 | 10 | 2.21 |
Yaxiong Ding | 2 | 3 | 0.42 |
Xiaofeng Li | 3 | 336 | 79.94 |
Biao Zhang | 4 | 97 | 23.66 |
Mingyu Xu | 5 | 11 | 1.86 |