Research on polarization of oil spill and detection

详细信息    查看全文

• 作者：Yang Cai ; Yarong Zou ; Chao Liang ; Bin Zou
• 关键词：oil spill ; polarization ; detection ; SAR
• 刊名：Acta Oceanologica Sinica
• 出版年：2016
• 出版时间：March 2016
• 年：2016
• 卷：35
• 期：3
• 页码：84-89
• 全文大小：1,258 KB
• 参考文献：Migliaccio M, Gambardella A, Tranfaglia M. 2007. SAR polarimetry to observe oil spills. IEEE Transactions on Geoscience and Remote Sensing, 45(2): 506–511CrossRef
  Migliaccio M, Nunziata F, Gambardella A. 2009. On the co-polarized phase difference for oil spill observation. International Journal of Remote Sensing, 30(6): 1587–1602CrossRef
  Migliaccio M, Nunziata F, Montuori A, et al. 2011. A multifrequency polarimetric SAR processing chain to observe oil fields in the Gulf of Mexico. IEEE Transactions on Geoscience and Remote Sensing, 49(12): 4729–4737CrossRef
  Nunziata F, Gambardella A, Migliaccio M. 2007. Dual-polarized SAR data for oil spill detection. In: ESA eds. Proc ‘Envisat Symposium 2007’. Montreux, Switzerland: ESA SP-636, 23–27
  Salberg A B, Rudjord O, Solberg A H S. 2012. Model based oil spill detection using polarimetric SAR. In: Proc IGARSS, 5884–5887
  Skrunes S, Brekke C, Eltoft T, et al. 2012. An experimental study on oil spill characterization by multi-polarization SAR. In: EUSAR, eds. 9th European Conference on Topic (s): Fields, Waves & Electromagnetics. EUSAR, 139–142
  Velotto D, Lehner S, Soloviev A, et al. 2012. Analysis of oceanic features from dual-polarization high resolution x-band SAR imagery for oil spill detection purposes. In: 2012 IEEE International Geoscience and Remote Sensing Symposium (IGARSS). Munich: IEEE, 2841–2844CrossRef
  Velotto D, Migliaccio M, Nunziata F, et al. 2010. Oil-slick observation using single look complex TerraSAR-X dual-polarized data. In: IGARSS, eds. 2010. IEEE International Geoscience and Remote Sensing SymposiumI. Honolulu: IEEE, 3684–3687CrossRef
  Velotto D, Migliaccio M, Nunziata F, et al. 2011. Dual-polarized TerraSAR- X data for oil-spill observation. IEEE Transactions on Geoscience and Remote Sensing, 49(12): 4751–4762CrossRef
  Wang Chao, Zhang Hong, Chen Xi, et al. 2008. Full polarization synthetic a perture radar image pro cessing Beijing: Science Press
  Wang Wenguang, Lu Fei, Wu Peng, et al. 2010. Oil spill detection from polarimetric SAR image. In: Int Conf Signal Process, 832–835
  Zhang Biao, Perrie W, Li Xiaofeng, et al. 2011. Mapping sea surface oil slicks using Radarsat-2 quad-polarization SAR image. Geophys Res Lett, 38(10), doi: 10.1029/2011GL047013
  
• 作者单位：Yang Cai (1)
  Yarong Zou (2) (3)
  Chao Liang (2) (3)
  Bin Zou (2) (3)
  
  1. South China Sea Forecast Center, State Oceanic Administration, Guangzhou, 510310, China
  2. National Satellite Ocean Application Services, Beijing, 100081, China
  3. Key Laboratory of Space Ocean Remote Sensing and Application, State Oceamic Administration, Beijing, 100081, China
  
• 刊物主题：Oceanography; Climatology; Ecology; Engineering Fluid Dynamics; Marine & Freshwater Sciences; Environmental Chemistry;
• 出版者：Springer Berlin Heidelberg
• ISSN：1869-1099

文摘

The SAR (Synthetic Aperture Radar) has the capabilities for all-weather day and night use. In the case of determining the effects of oil spill dumping, the oil spills areas are shown as dark spots in the SAR images. Therefore, using SAR data to detect oil spills is becoming progressively popular in operational monitoring, which is useful for oceanic environmental protection and hazard reduction. Research has been conducted on the polarization decomposition and scattering characteristics of oil spills from a scattering matrix using allpolarization of the SAR data, calculation of the polarization parameters, and utilization of the CPD (Co-polarized Phase Difference) of the oil and the sea, in order to extract the oil spill information. This method proves to be effective by combining polarization parameters with the characteristics of oil spill. The results show that when using Bragg, the oil spill backscattering machine with Enopy and a mean scatter α parameter. The oil spill can be successfully identified. However, the parameter mechanism of the oil spill remains unclear. The use of CPD can easily extract oil spill information from the ocean, and the polarization research provides a base for oil spill remote sensing detection.