Research on UV Reflective Spectrum of Floating Transparent Oil
HUANG Hui1, ZHANG De-jun1, WANG Chao1, ZHAN Shu-yue1*, SONG Hong1, WANG Hang-zhou1, ZHU Wei-ning1, CHEN Jiang1, LIU Cai-cai2, XU Ren2, JIANG Xiao-shan2
1. Ocean College, Zhejiang University, Zhoushan 316021, China
2. East China Sea Environmental Monitoring Center, Ministry of Natural Rosources, Shanghai 201206, China
Abstract：The increasing amount of petroleum products has increased the risk of the pollution accidents, which could pose an acute threat to ecological safety. The leakage accidents often have the characteristics of suddenness, contingency and large pollution. The traditional chemical sampling detection method is not suitable for on-site emergency monitoring and quantitative warning. The development of satellite remote sensing and airborne imaging technology provides effective methods for the detection of accidents. However, the color characteristics of the floating transparent oil product are not obvious, and it seriously affects the imaging monitoring effect and poses a great threat to ecological security. According to the difference of the spectral reflectance characteristics of the water surface and the oil product, selecting a suitable operating band to improve the imaging effect is a common method for oil spill monitoring. For the spectral measurement of floating oil products, the existing researches were often carried out in the experimental containers, which have different optical characteristics in natural water. It is difficult to provide corresponding data support for the monitoring of on-site leakage accidents. In order to simulate the actual leakage scene, UV-Visible spectroscopic characteristics of transparent oils such as gasoline and xylene were investigated on the surface of artificial lake in this paper. Spectral measurement results show that the spectral angle cosine of the sample and water in each band interval is close to 1, but the spectral reflectance difference is significantly larger than the other band in the ultraviolet band, indicating the spectral characteristics of transparent oil were similar to the lake water in shape, but there is the largest difference in amplitude in the ultraviolet wavelength. To further demonstrate the results of spectral feature analysis, four ultraviolet-visible band filters of 365, 436, 546 and 700 nm were selected for imaging verification. The results show that the difference between the spectral reflectance curve of transparent oils such as floating gasoline and xylene and the amplitude of lake water is the largest at the ultraviolet wavelength, and the overall grayscale contrast of the two floating transparent oils and lake water at the ultraviolet wavelength is made. The difference between value and texture features is significantly higher than that in other visible wavelengths. Therefore, the use of the ultraviolet wavelength for imaging monitoring of floating oil products can effectively improve the imaging contrast between oil and natural water surface. The experiments were carried out under the conditions of natural light and natural water on the lake surface, which greatly simulated the actual transparent oil spill pollution scenarios and provided the most representative theoretical and data support for transparent oil imaging band optimization for airborne remote sensing monitoring.
[1] Niziolek A M, Onel O, Floudas C A. AIChE Journal, 2016, 62(5): 1531.
[2] Sekhar P K, Subramaniyam K. ECS Electrochemistry Letters, 2014, 3(2): B1.
[3] Li D, Qu L, Zhai W, et al. Environmental Science & Technology, 2011, 45(9): 4046.
[4] Alonso M, Sanchez J M. TrAC Trends in Analytical Chemistry, 2013, 44: 78.
[5] Jones C E C E, Minchew B B, Holt B B, et al. Monitoring and Modeling the Deepwater Horizon Oil Spill: A Record-Breaking Enterprise, 2011. 33.
[6] Giri C, Long J, Tieszen L. Journal of Coastal Research, 2011, 27(6): 1059.
[7] Leifer I, Lehr W J, Simecek-Beatty D, et al. Remote Sensing of Environment, 2012, 124: 185.
[8] YE Zhou, LIU Li, WEI Chuan-xin, et al(叶 舟, 刘 力, 魏传新, 等). Spectroscopy and Spectral Analysis(光谱学与光谱分析), 2015, 35(6): 1695.
[9] Campbell J B, Wynne R H. Introduction to Remote Sensing. Guilford Press, 2011.
[10] Chaugule A, Mali S N. Journal of Engineering, 2014: Article ID 617263.
