基于耀光反射差异的海面溢油遥感识别提取

朱小波; 沈亚峰; 刘建强; 丁静; 焦俊男; 居为民; 陆应诚

doi:10.11834/jrs.20221688

生态灾害遥感监测应用 | 浏览量 : 0 下载量: 1524 CSCD: 1

R-PDF
PDF
导出
分享
收藏
专辑

基于耀光反射差异的海面溢油遥感识别提取
Optical extraction of oil spills based on sunglint reflection difference in HY-1C CZI images
2023年27卷第1期页码：197-208
收稿：2021-10-29，

纸质出版：2023-01-07
DOI： 10.11834/jrs.20221688
稿件说明：

移动端阅览

朱小波，沈亚峰，刘建强，丁静，焦俊男，居为民，陆应诚.2023.基于耀光反射差异的海面溢油遥感识别提取.遥感学报，27（1）： 197-208 DOI： 10.11834/jrs.20221688.

Zhu X B，Shen Y F，Liu J Q，Ding J，Jiao J N，Ju W M and Lu Y C. 2023. Optical extraction of oil spills based on sunglint reflection difference in HY-1C CZI images. National Remote Sensing Bulletin， 27（1）：197-208 DOI： 10.11834/jrs.20221688.

摘要

溢油是海洋环境监测的重要目标之一。近年来，光学遥感对海面溢油不同污染类型的识别、分类与估算原理得到阐明，其技术优势获得认可；能为海面溢油监测提供颠覆性的技术支持，提高了溢油的识别精度，实现精细化定量探测。随着中国海洋水色业务卫星—HY-1C/D（Haiyang-1C/D）的投入应用，其搭载的海岸带成像仪CZI（Coastal Zone Imager）在中国近海溢油监测中体现了较好的效能；但HY-1C/D星CZI载荷开展中国近海溢油业务化监测应用，还需要不断丰富并发展溢油识别提取算法。在HY-1C/D星CZI载荷的高空间分辨率影像中，不同的海面溢油污染类型具有明确的光谱响应特征和形态特征；太阳耀光反射差异，有助于海面溢油的遥感检测，同时也给溢油污染的识别分类与定量估算带来不确定性影响。本研究在CZI载荷数据对海面溢油波段响应基础上，通过溢油海面与背景干扰的耀光反射特征分析，厘清CZI图像中海面耀光干扰的空间分布特点；进一步在优选波段的移动窗口分割及其参数统计基础上，通过对不同分割窗间的耀光形态特征及其相关性判断，实现了CZI图像上海面溢油较高精度的识别与提取。其中，弱耀光条件下油膜提取的平均精度为90.24%、乳化油的平均精度为80.55%；强耀光条件下溢油提取总体效果也较好。面向国产自主海洋水色业务卫星数据，发展溢油光学遥感识别、分类、提取与估算，不仅能促进国产海洋光学卫星的业务化应用，更能为全面掌握中国近海溢油污染状况提供数据参考。

Abstract

After an oil spill accident

it is essential to quickly detect the location

spatial coverage

pollution type

and amount of oil spills

so as to measure the impacts of different oil spill types

clean up the oil

and help the ocean recover. Although the mechanism and characteristics of optical remote sensing of oil spills have been basically clarified

the research on automatic oil spill extraction algorithms is still insufficient

which still needs to be addressed. The main challenge is that the significant variation of sunglint is helpful to the oil spill identification

but also brings many uncertainties to the extraction. Hence

the marine remote-sensing community is always committed to developing remote-sensing methods for improving the performance of aspects

such as preprocessing

segmentation

and classification. The scale of extraction is deemed the key to eliminating sunglint interference. As the conventional extraction method cannot be applied on the optical images directly for the reasons outlined in the context

a new man-machine interactive oil spill extraction method (more specific an oil–water mixture detector)

which is able to eliminate sunglint interference was introduced. It accomplishes this by splitting the oil spill global region into adjacent sub-windows

as the sunglint can be considered constant in a small region. The proposed method and density-based clustering is used cooperatively in the method. The detector first discretizes different types of oil spills in images based on the specific optical detection principle of oil spills. Then the clustering uses the auxiliary information of multispectral images to achieve high confidence clustering output. The Coastal Zone Imager (CZI) onboard China’s HaiYang-1C/D (HY-1C/D) satellites can provide multispectral images with high spatial resolution and wide coverage for operational monitoring of oil spills. The proposed method was applied to HY/CZI oil spill dataset and other optical images of several oil spill events. The spatial differentiation of sunglint and remote sensing response characteristics of different oil spills in CZI were analyzed

and the accurate identification and extraction of oil spills in CZI images were realized. The results show that the optical remote sensing extraction method considering the variation of sunglint can effectively identify and extract the oil spills

and has good anti-interference ability. Based on testing of CZI data covering different areas

the method was proved to be effective in removing interference caused by sunglint

image interference (e.g. cloud

rough surface texture

ship wakes

illumination

shadowing)

and so on. In addition

the method can further distinguish oil slicks and oil emulsions under the condition of weak sunglint

showing the ability to identify different oil spills

which can provide a reference for the operational application in oil spill monitoring. The results show stable variable-scale extraction accuracies of approximately 90.24% and 80.55% for oil slicks and oil emulsions

respectively. It is also applicable for the optical images with lower resolution

but the effect is inferior to that in CZI because of the influence of mixed pixels. As aforementioned

the accurate results are attributed to appropriate parameter adjustment under different spatial resolutions

oil spil types

and sunglint reflections. The satisfactory transfer applicability is mainly attributed to the variable-scale detector for sunglint reflection differences. In summary

the precondition for accurate oil spill extraction is to eliminate the sunglint interference

which depends on not only the sunglint model but also appropriate local scale

not global. Without a doubt

to what extent the coordination and utilization of sunglint and spectral information is the key to breakthrough for accurate oil spill extraction and quantification.

关键词

Keywords

references

Brekke C and Solberg A H S . 2005 . Oil spill detection by satellite remote sensing . Remote Sensing of Environment , 95 ( 1 ): 1 - 13 [ DOI: 10.1016/j.rse.2004.11.015 http://dx.doi.org/10.1016/j.rse.2004.11.015 ]

Clark R N , Swayze G A , Leifer I , Livo K E , Kokaly R , Hoefen T , Lundeen S , Eastwood M , Green R O , Pearson N , Sarture C , McCubbin I , Roberts D , Bradley E , Steele D , Ryan T , Dominguez R and The Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) Team . 2010 . A Method for Quantitative Mapping of Thick Oil Spills Using Imaging Spectroscopy/ /Open-File Report 2010 — 1167 . SurveyUGeological. S .: 1 - 51 .

Ester M , Kriegel H P , Sander J and Xu X W . 1996 . A density-based algorithm for discovering clusters in large spatial databases with noise // Proceedings of the Second International Conference on Knowledge Discovery and Data Mining . Portland : AAAI Press: 226 - 231

Hu C M , Feng L , Holmes J , Swayze G A , Leifer I , Melton C , Garcia O , MacDonald I , Hess M , Muller-Karger F , Graettinger G and Green R . 2018 . Remote sensing estimation of surface oil volume during the 2010 Deepwater Horizon oil blowout in the Gulf of Mexico: scaling up AVIRIS observations with MODIS measurements . Journal of Applied Remote Sensing , 12 ( 2 ): 026008 [ DOI: 10.1117/1.JRS.12.026008 http://dx.doi.org/10.1117/1.JRS.12.026008 ]

Hu C M , Li X F , Pichel W G and Muller-Karger F E . 2009 . Detection of natural oil slicks in the NW Gulf of Mexico using MODIS imagery . Geophysical Research Letters , 36 ( 1 ): L 01604 [ DOI: 10.1029/2008gl036119 http://dx.doi.org/10.1029/2008gl036119 ]

Hu C M , Lu Y C , Sun S J and Liu Y X . 2021 . Optical remote sensing of oil spills in the ocean: what is really possible? Journal of Remote Sensing , 2021 : 9141902 [ DOI: 10.34133/2021/9141902 http://dx.doi.org/10.34133/2021/9141902 ]

Jackson C R and Alpers W . 2010 . The role of the critical angle in brightness reversals on sunglint images of the sea surface . Journal of Geophysical Research : Oceans , 115 ( C9 ): C 09019 [ DOI: 10.1029/2009JC006037 http://dx.doi.org/10.1029/2009JC006037 ]

Kessler J D , Valentine D L , Redmond M C , Du M R , Chan E W , Mendes S D , Quiroz E W , Villanueva C J , Shusta S S , Werra L M , Yvon-Lewis S A and Weber T C . 2011 . A persistent oxygen anomaly reveals the fate of spilled methane in the deep Gulf of Mexico . Science , 331 ( 6015 ): 312 - 315 [ DOI: 10.1126/science.1199697 http://dx.doi.org/10.1126/science.1199697 ]

Kolokoussis P and Karathanassi V . 2018 . Oil spill detection and mapping using sentinel 2 imagery . Journal of Marine Science and Engineering , 6 ( 1 ): 4 [ DOI: 10.3390/jmse6010004 http://dx.doi.org/10.3390/jmse6010004 ]

Kvenvolden K A and Cooper C K . 2003 . Natural seepage of crude oil into the marine environment . Geo-Marine Letters , 23 ( 3/4 ): 140 - 146 [ DOI: 10.1007/s00367-003-0135-0 http://dx.doi.org/10.1007/s00367-003-0135-0 ]

Leifer I , Lehr W J , Simecek-Beatty D , Bradley E , Clark R , Dennison P , Hu Y X , Matheson S , Jones C E , Holt B , Reif M , Roberts D A , Svejkovsky J , Swayze G and Wozencraft J . 2012 . State of the art satellite and airborne marine oil spill remote sensing: application to the BP Deepwater Horizon oil spill . Remote Sensing of Environment , 124 : 185 - 209 [ DOI: 10.1016/j.rse.2012.03.024 http://dx.doi.org/10.1016/j.rse.2012.03.024 ]

Lu Y C , Hu C M , Sun S J , Zhang M W , Zhou Y , Shi J and Wen Y S . 2016 . Overview of optical remote sensing of marine oil spills and hydrocarbon seepage . Journal of Remote Sensing , 20 ( 5 ): 1259 - 1269

陆应诚 , 胡传民 , 孙绍杰 , 张民伟 , 周杨 , 石静 , 温颜沙 . 2016 . 海洋溢油与烃渗漏的光学遥感研究进展 . 遥感学报 , 20 ( 5 ): 1259 - 1269 [ DOI: 10.11834/jrs.20166122 http://dx.doi.org/10.11834/jrs.20166122 ]

Lu Y C , Li X , Tian Q J and Han W C . 2012 . An optical remote sensing model for estimating oil slick thickness based on two-beam interference theory . Optics Express , 20 ( 22 ): 24496 - 24504 [ DOI: 10.1364/OE.20.024496 http://dx.doi.org/10.1364/OE.20.024496 ]

Lu Y C , Li X , Tian Q J , Zheng G , Sun S J , Liu Y X and Yang Q . 2013 . Progress in marine oil spill optical remote sensing: detected targets, spectral response characteristics, and theories . Marine Geodesy , 36 ( 3 ): 334 - 346 [ DOI: 10.1080/01490419.2013.793633 http://dx.doi.org/10.1080/01490419.2013.793633 ]

Lu Y C , Liu J Q , Ding J , Shi J , Chen J Y and Ye X M . 2019 . Optical remote identification of spilled oils from the SANCHI oil tanker collision in the East China Sea . Chinese Science Bulletin , 64 ( 31 ): 3213 - 3222

陆应诚 , 刘建强 , 丁静 , 石静 , 陈君颖 , 叶小敏 . 2019 . 中国东海“桑吉”轮溢油污染类型的光学遥感识别 . 科学通报 , 64 ( 31 ): 3213 - 3222 [ DOI: 10.1360/N972019-00094 http://dx.doi.org/10.1360/N972019-00094 ]

Lu Y C , Shi J , Hu C M , Zhang M W , Sun S J and Liu Y X . 2020 . Optical interpretation of oil emulsions in the ocean – part II: applications to multi-band coarse-resolution imagery . Remote Sensing of Environment , 242 : 111778 [ DOI: 10.1016/j.rse.2020.111778 http://dx.doi.org/10.1016/j.rse.2020.111778 ]

Lu Y C , Shi J , Wen Y S , Hu C M , Zhou Y , Sun S J , Zhang M W , Mao Z H and Liu Y X . 2019 . Optical interpretation of oil emulsions in the ocean – part I: laboratory measurements and proof-of-concept with AVIRIS observations . Remote Sensing of Environment , 230 : 111183 [ DOI: 10.1016/j.rse.2019.05.002 http://dx.doi.org/10.1016/j.rse.2019.05.002 ]

Lu Y C , Sun S J , Zhang M W , Murch B and Hu C M . 2016a . Refinement of the critical angle calculation for the contrast reversal of oil slicks under sunglint . Journal of Geophysical Research: Oceans , 121 ( 1 ): 148 - 161 [ DOI: 10.1002/2015JC011001 http://dx.doi.org/10.1002/2015JC011001 ]

Lu Y C , Tian Q J and Li X . 2011 . The remote sensing inversion theory of offshore oil slick thickness based on a two-beam interference model . Science China : Earth Sciences , 54 ( 5 ): 678 - 685 [ DOI: 10.1007/s11430-010-4154-1 http://dx.doi.org/10.1007/s11430-010-4154-1 ]

Lu Y C , Tian Q J , Song P F and Li S S . 2009 . Study on extraction methods of offshore oil stick by hyperspectral remote sensing . Journal of Remote Sensing , 13 ( 4 ): 686 - 695

陆应诚 , 田庆久 , 宋鹏飞 , 李姗姗 . 2009 . 海面油膜高光谱遥感信息提取 . 遥感学报 , 13 ( 4 ): 686 - 695 [ DOI: 10.11834/jrs.20090411 http://dx.doi.org/10.11834/jrs.20090411 ]

Lu Y C , Tian Q J , Wang J J , Wang X C and Qi X P . 2008 . Experimental study on spectral responses of offshore oil slick . Chinese Science Bulletin , 53 ( 24 ): 3937 - 3941 [ DOI: 10.1007/s11434-008-0515-y http://dx.doi.org/10.1007/s11434-008-0515-y ]

Lu Y C , Zhan W F and Hu C M . 2016b . Detecting and quantifying oil slick thickness by thermal remote sensing: a ground-based experiment . Remote Sensing of Environment , 181 : 207 - 217 [ DOI: 10.1016/j.rse.2016.04.007 http://dx.doi.org/10.1016/j.rse.2016.04.007 ]

Mariano A J , Kourafalou V H , Srinivasan A , Kang H , Halliwell G R , Ryan E H and Roffer M . 2011 . On the modeling of the 2010 Gulf of Mexico oil spill . Dynamics of Atmospheres and Oceans , 52 ( 1/2 ): 322 - 340 [ DOI: 10.1016/j.dynatmoce.2011.06.001 http://dx.doi.org/10.1016/j.dynatmoce.2011.06.001 ]

Mou L , Zou H P , Wu S Q , Song J , Li H , Xu L L and Zhao R X . 2011 . Numerical model research on the ocean oil spill . Marine Science Bulletin , 30 ( 4 ): 473 - 480

牟林 , 邹和平 , 武双全 , 宋军 , 李欢 , 徐玲玲 , 赵如箱 . 2011 . 海上溢油数值模型研究进展 . 海洋通报 , 30 ( 4 ): 473 - 480 [ DOI: 10.3969/j.issn.1001-6392.2011.04.019 http://dx.doi.org/10.3969/j.issn.1001-6392.2011.04.019 ]

Shen Y F , Liu J Q , Ding J , Jiao J N , Sun S J and Lu Y C . 2020 . HY-1C COCTS and CZI observation of marine oil spills in the South China Sea . Journal of Remote Sensing , 24 ( 8 ): 933 - 944

沈亚峰 , 刘建强 , 丁静 , 焦俊男 , 孙绍杰 , 陆应诚 . 2020 . 海洋一号C星光学载荷对海面溢油的识别能力分析 . 遥感学报 , 24 ( 8 ): 933 - 944 [ DOI: 10.11834/jrs.20209475 http://dx.doi.org/10.11834/jrs.20209475 ]

Shi J , Jiao J N , Lu Y C , Zhang M W , Mao Z H and Liu Y X . 2018 . Determining spectral groups to distinguish oil emulsions from Sargassum over the Gulf of Mexico using an airborne imaging spectrometer . ISPRS Journal of Photogrammetry and Remote Sensing , 146 : 251 - 259 [ DOI: 10.1016/j.isprsjprs.2018.09.017 http://dx.doi.org/10.1016/j.isprsjprs.2018.09.017 ]

Sun S J and Hu C M . 2019 . The challenges of interpreting oil–water spatial and spectral contrasts for the estimation of oil thickness: examples from satellite and airborne measurements of the Deepwater Horizon oil spill . IEEE Transactions on Geoscience and Remote Sensing , 57 ( 5 ): 2643 - 2658 [ DOI: 10.1109/TGRS.2018.2876091 http://dx.doi.org/10.1109/TGRS.2018.2876091 ]

Sun S J and Hu C M . 2016 . Sun glint requirement for the remote detection of surface oil films . Geophysical Research Letters , 43 ( 1 ): 309 - 316 [ DOI: 10.1002/2015GL066884 http://dx.doi.org/10.1002/2015GL066884 ]

Sun S J , Hu C M , Feng L , Swayze G A , Holmes J , Graettinger G , MacDonald I , Garcia O and Leifer I . 2016 . Oil slick morphology derived from AVIRIS measurements of the Deepwater Horizon oil spill: implications for spatial resolution requirements of remote sensors . Marine Pollution Bulletin , 103 ( 1/2 ): 276 - 285 [ DOI: 10.1016/j.marpolbul.2015.12.003 http://dx.doi.org/10.1016/j.marpolbul.2015.12.003 ]

Sun S J , Hu C M , Garcia-Pineda O , Kourafalou V , Le Hénaff M and Androulidakis Y . 2018a . Remote sensing assessment of oil spills near a damaged platform in the Gulf of Mexico . Marine Pollution Bulletin , 136 : 141 - 151 [ DOI: 10.1016/j.marpolbul.2018.09.004 http://dx.doi.org/10.1016/j.marpolbul.2018.09.004 ]

Sun S J , Hu C M and Tunnell Jr J W . 2015 . Surface oil footprint and trajectory of the Ixtoc-I oil spill determined from Landsat/MSS and CZCS observations . Marine Pollution Bulletin , 101 ( 2 ): 632 - 641 [ DOI: 10.1016/j.marpolbul.2015.10.036 http://dx.doi.org/10.1016/j.marpolbul.2015.10.036 ]

Sun S J , Lu Y C , Liu Y X , Wang M Q and Hu C M . 2018b . Tracking an oil tanker collision and spilled oils in the East China Sea using multisensor day and night satellite imagery . Geophysical Research Letters , 45 ( 7 ): 3212 - 3220 [ DOI: 10.1002/2018GL077433 http://dx.doi.org/10.1002/2018GL077433 ]

Suo Z Y , Lu Y C , Liu J Q , Ding J , Yin D Y , Xu F F and Jiao J N . 2021 . Ultraviolet remote sensing of marine oil spills: a new approach of Haiyang-1C satellite . Optics Express , 29 ( 9 ): 13486 - 13495 [ DOI: 10.1364/OE.423702 http://dx.doi.org/10.1364/OE.423702 ]

Wen Y S , Wang M Q , Lu Y C , Sun S J , Zhang M W , Mao Z H , Shi J and Liu Y X . 2018 . An alternative approach to determine critical angle of contrast reversal and surface roughness of oil slicks under sunglint . International Journal of Digital Earth , 11 ( 9 ): 972 - 979 [ DOI: 10.1080/17538947.2018.1470687 http://dx.doi.org/10.1080/17538947.2018.1470687 ]

Wettle M , Daniel P J , Logan G A and Thankappan M . 2009 . Assessing the effect of hydrocarbon oil type and thickness on a remote sensing signal: a sensitivity study based on the optical properties of two different oil types and the HYMAP and Quickbird sensors . Remote Sensing of Environment , 113 ( 9 ): 2000 - 2010 [ DOI: 10.1016/j.rse.2009.05.010 http://dx.doi.org/10.1016/j.rse.2009.05.010 ]

Zhong Z X and You F Q . 2011 . Oil spill response planning with consideration of physicochemical evolution of the oil slick: a multi objective optimization approach . Computers and Chemical Engineering , 35 ( 8 ): 1614 - 1630 [ DOI: 10.1016/j.compchemeng.2011.01.009 http://dx.doi.org/10.1016/j.compchemeng.2011.01.009 ]

Zhu X B , Lu Y C , Liu J Q , Ju W M , Ding J , Li M C , Suo Z Y , Jiao J J and Wang L F . 2022 . Optical Extraction of Oil Spills from Satellite Images under Different Sunglint Reflections . IEEE Transactions on Geoscience and Remote Sensing . [ DOI: 10.1109/TGRS.2022.3213590 http://dx.doi.org/10.1109/TGRS.2022.3213590 ]

文章被引用时，请邮件提醒。

提交

基于时序Sentinel-2和Landsat 8影像的入侵植物互花米草治理方式识别与动态监测

多源光学遥感数据对近海溢油的监测效能分析

顾及地理位置特征的近海水深遥感反演方法

光学遥感机理建模：回顾与展望