Abstract
The estimation of oil spill coverage is an important part of monitoring of oil spills at sea. The spatial resolution of images collected by airborne hyper-spectral remote sensing limits both the detection of oil spills and the accuracy of estimates of their size. We consider at-sea oil spills with zonal distribution in this paper and improve the traditional independent component analysis algorithm. For each independent component we added two constraint conditions: non-negativity and constant sum. We use priority weighting by higher-order statistics, and then the spectral angle match method to overcome the order nondeterminacy. By these steps, endmembers can be extracted and abundance quantified simultaneously. To examine the coverage of a real oil spill and correct our estimate, a simulation experiment and a real experiment were designed using the algorithm described above. The result indicated that, for the simulation data, the abundance estimation error is 2.52% and minimum root mean square error of the reconstructed image is 0.030 6. We estimated the oil spill rate and area based on eight hyper-spectral remote sensing images collected by an airborne survey of Shandong Changdao in 2011. The total oil spill area was 0.224 km2, and the oil spill rate was 22.89%. The method we demonstrate in this paper can be used for the automatic monitoring of oil spill coverage rates. It also allows the accurate estimation of the oil spill area.
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Supported by the National Scientific Research Fund of China (No. 31201133)
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Han, Z., Wan, J., Zhang, J. et al. Abundance quantification by independent component analysis of hyperspectral imagery for oil spill coverage calculation. Chin. J. Ocean. Limnol. 35, 978–986 (2017). https://doi.org/10.1007/s00343-017-5301-8
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DOI: https://doi.org/10.1007/s00343-017-5301-8