Abstract
In this chapter, the oil spill scattering mechanism and characteristics are analyzed, and the oil spill extraction in a multimode dual-polarization SAR image is comprehensively discussed. The results show that under the same sensing conditions, the images with low incidence angles exhibit a higher signal-to-noise ratio compared to the images with high incidence angles. The images with high incidence angles exhibit higher randomness and complexity compared to the seawater with low incidence angles. Among various dual-polarization SAR modes, the HH-VV mode performs the best. Its oil spill scattering mechanism is similar to that of fully polarization SAR, but its recognition performance is slightly poorer. Overall, it is superior to the other two dual-polarization modes and can be used as an alternative to fully polarization systems when fully polarization information cannot be obtained. In addition, the VV-VH mode is generally superior to the HH-VH mode. This chapter also proposes an oil spill extraction method for multitemporal dual-polarization SAR images. Based on the frequency results of hidden dark regions in the time-series SAR images, oil spill region locking is achieved, and the look-alikes caused by random ocean phenomena can be effectively eliminated. In addition, based on the importance scores of polarization texture feature sets under different boundary complexity conditions, the advantage feature parameters of oil spill detection under different complexity boundary conditions were analyzed. On this basis, an oil spill detection method that takes into account the dominant characteristics of different oil and water boundary complexities is constructed using the random forest module, based on which the annual spatial-temporal changes of oil spills in the middle of the Caspian Sea are analyzed.
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