基于GOCI的2017年南黄海浒苔演变遥感分析
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摘要
本文应用GOCI高时间分辨率遥感影像,提取浒苔敏感波段并构建合适的评价指标,对NDVI、IGAG、KOSC绿潮主流算法探测能力进行比较,结合目视解译和阈值分割法,对2017年南黄海浒苔信息进行提取并进行演变特征分析。结果表明:NDVI算法的探测能力和稳定性显著优于其他两种, GOCI影像7、8近红外波段的选择对浒苔提取结果存在一定影响,最优为7、5波段组合; 2017年浒苔总体经历了"出现-发展-暴发-衰退-消亡"五个阶段,持续时间约为68d,影像中浒苔最早出现在5月13日的盐城外海海域,最后出现在7月12日,最大覆盖面积出现在6月4日,为2363.12km2,在风、流场共同作用下,先向北移动,后在6月下旬沿山东半岛南侧转向东北,前锋位置最终停滞于青岛-烟台-威海一线并逐渐消亡。其发展规律与运移路径与往年相似,但持续时间与暴发时期最大覆盖面积显著少于往年, GOCI影像高时间分辨率的优势使浒苔灾害的逐小时动态监测成为可能。
Based on the visual interpretation and threshold segmentation method, we evaluated the difference of green tide detection algorithms including NDVI, IGAG, and KOSC by building suitable indices, and monitored the outbreak of green tide in the South Yellow Sea, 2017 and its evolution. The results show that NDVI is significantly better than the other two methods in both extraction capability and stability, and the selection of 7 or 8 NIR band in GOCI may affect the final extraction result somewhat while the best band combination is 5 and 7. The outbreak of a green tide in 2017 lasted for 65 days in five stages: appearance, development, outbreak, recession, and disappearance. The outbreak started in the open waters near Yancheng, Jiangsu Province on May 16, reached the maximum coverage area of 2363.12 km~2 on June 4 and disappeared from the remote sensing image on July 12. Under the combined action of the airflow field, the migration path moved northward first and then shifted northeastward along the southern flank of the Shandong Peninsula in late June and its frontline stayed in Qingdao-Yantai-Weihai until it died out. The development and migration path of the green tide is similar to those in previous years, while the duration time of the whole period and the maximum coverage area were significantly less. Our work shows that the GOCI image of high temporal resolution is applicable to the study on the migration path and speed of a green tide.
Based on the visual interpretation and threshold segmentation method, we evaluated the difference of green tide detection algorithms including NDVI, IGAG, and KOSC by building suitable indices, and monitored the outbreak of green tide in the South Yellow Sea, 2017 and its evolution. The results show that NDVI is significantly better than the other two methods in both extraction capability and stability, and the selection of 7 or 8 NIR band in GOCI may affect the final extraction result somewhat while the best band combination is 5 and 7. The outbreak of a green tide in 2017 lasted for 65 days in five stages: appearance, development, outbreak, recession, and disappearance. The outbreak started in the open waters near Yancheng, Jiangsu Province on May 16, reached the maximum coverage area of 2363.12 km~2 on June 4 and disappeared from the remote sensing image on July 12. Under the combined action of the airflow field, the migration path moved northward first and then shifted northeastward along the southern flank of the Shandong Peninsula in late June and its frontline stayed in Qingdao-Yantai-Weihai until it died out. The development and migration path of the green tide is similar to those in previous years, while the duration time of the whole period and the maximum coverage area were significantly less. Our work shows that the GOCI image of high temporal resolution is applicable to the study on the migration path and speed of a green tide.
引文
马艳,郭丽娜,黄容等,2015.2008-2010年青岛近海浒苔暴发气象条件及其漂移特征.气象与环境学报,31(4):89-96
衣立,张苏平,殷玉齐,2010.2009年黄海绿潮浒苔暴发与漂移的水文气象环境.中国海洋大学学报,40(10):15-23
孙松,于志刚,李超伦等,2012.黄、东海水母暴发机理及其生态环境效应研究进展.海洋与湖沼,43(3):401-405
孙慧,谢小平,2016.基于MODIS数据的日照市近海浒苔监测及影响因子分析.国土资源遥感,28(1):144-151
李曰嵩,潘灵芝,肖文军等,2014.风对黄海绿潮藻漂移的影响.海洋环境科学,33(5):772-776
李德萍,杨育强,董海鹰等,2009.2008年青岛海域浒苔大爆发天气特征及成因分析.中国海洋大学学报,39(6):1165-1170
杨静,张思,刘桂梅,2017.基于卫星遥感监测的2011-2016年黄海绿潮变化特征分析.海洋预报,34(3):56-61
杨佰娟,郑立,陈军辉等,2009.黄、渤海漂移浒苔(Enteromorpha prolifera)脂肪酸组成及聚类分析的研究.海洋与湖沼,40(5):627-632
吴传庆,马万栋,王雪蕾等,2015.基于环境卫星CCD数据的黄海浒苔遥感监测.中国环境科学,31(3):161-165
吴孟泉,郭浩,张安定等,2014.2008年-2012年山东半岛海域浒苔时空分布特征研究.光谱学与光谱分析,34(5):1312-1318
吴玲娟,曹丛华,高松等,2013.我国绿潮发生发展机理研究进展.海洋科学,37(12):118-121
邱亚会,卢剑波,2015.浒苔遥感监测研究进展.生态学报,35(15):4977-4985
范士亮,傅明珠,李艳等,2012.2009-2010年黄海绿潮起源与发生过程调查研究.海洋学报,34(6):187-194
郑向阳,邢前国,李丽等,2011.2008年黄海绿潮路径的数值模拟.海洋科学,35(7):82-87
赵文静,张杰,崔廷伟等,2009.水下悬浮浒苔海面光谱响应的辐射传输模拟.光谱学与光谱分析,29(6):1656-1660
赵英时,2013.遥感数据源.见:赵英时.遥感应用分析原理与方法.2版.北京:科学出版社,34-35
夏深圳,2016.基于遥感的黄海浒苔漂移速度与驱动机制研究.南京:南京大学硕士学位论文,62-63
梁宗英,林祥志,马牧等,2008.浒苔漂流聚集绿潮现象的初步分析.中国海洋大学学报,38(4):601-604
Hu C M,2009.A novel ocean color index to detect floating algae in the global oceans.Remote Sensing of Environment,113(10):2118-2129
Hu C M,Li D Q,Chen C S et al,2010.On the recurrent Ulva prolifera blooms in the Yellow Sea and East China Sea.Journal of Geophysical Research:Oceans,115(C5):C05017
Liu D Y,Keesing J K,Xing Q G et al,2009.World’s largest macroalgal bloom caused by expansion of seaweed aquaculture in China.Marine Pollution Bulletin,58(6):888-895
Lou X L,Hu C M,2014.Diurnal changes of a harmful algal bloom in the East China Sea:observations from GOCI.Remote Sensing of Environment,140:562-572
Shi W,Wang M H,2009.Green macroalgae blooms in the Yellow Sea during the spring and summer of 2008.Journal of Geophysical Research:Oceans,114(C12):C12010
Son Y B,Min J E,Ryu J H,2012.Detecting massive green algae(Ulva prolifera)blooms in the Yellow Sea and East China Sea using Geostationary Ocean Color Imager(GOCI)data.Ocean Science Journal,47(3):359-375
Xing Q G,Hu C M,2016.Mapping macroalgal blooms in the Yellow Sea and East China Sea using HJ-1 and landsat data:application of a virtual baseline reflectance height technique.Remote Sensing of Environment,178:113-126
衣立,张苏平,殷玉齐,2010.2009年黄海绿潮浒苔暴发与漂移的水文气象环境.中国海洋大学学报,40(10):15-23
孙松,于志刚,李超伦等,2012.黄、东海水母暴发机理及其生态环境效应研究进展.海洋与湖沼,43(3):401-405
孙慧,谢小平,2016.基于MODIS数据的日照市近海浒苔监测及影响因子分析.国土资源遥感,28(1):144-151
李曰嵩,潘灵芝,肖文军等,2014.风对黄海绿潮藻漂移的影响.海洋环境科学,33(5):772-776
李德萍,杨育强,董海鹰等,2009.2008年青岛海域浒苔大爆发天气特征及成因分析.中国海洋大学学报,39(6):1165-1170
杨静,张思,刘桂梅,2017.基于卫星遥感监测的2011-2016年黄海绿潮变化特征分析.海洋预报,34(3):56-61
杨佰娟,郑立,陈军辉等,2009.黄、渤海漂移浒苔(Enteromorpha prolifera)脂肪酸组成及聚类分析的研究.海洋与湖沼,40(5):627-632
吴传庆,马万栋,王雪蕾等,2015.基于环境卫星CCD数据的黄海浒苔遥感监测.中国环境科学,31(3):161-165
吴孟泉,郭浩,张安定等,2014.2008年-2012年山东半岛海域浒苔时空分布特征研究.光谱学与光谱分析,34(5):1312-1318
吴玲娟,曹丛华,高松等,2013.我国绿潮发生发展机理研究进展.海洋科学,37(12):118-121
邱亚会,卢剑波,2015.浒苔遥感监测研究进展.生态学报,35(15):4977-4985
范士亮,傅明珠,李艳等,2012.2009-2010年黄海绿潮起源与发生过程调查研究.海洋学报,34(6):187-194
郑向阳,邢前国,李丽等,2011.2008年黄海绿潮路径的数值模拟.海洋科学,35(7):82-87
赵文静,张杰,崔廷伟等,2009.水下悬浮浒苔海面光谱响应的辐射传输模拟.光谱学与光谱分析,29(6):1656-1660
赵英时,2013.遥感数据源.见:赵英时.遥感应用分析原理与方法.2版.北京:科学出版社,34-35
夏深圳,2016.基于遥感的黄海浒苔漂移速度与驱动机制研究.南京:南京大学硕士学位论文,62-63
梁宗英,林祥志,马牧等,2008.浒苔漂流聚集绿潮现象的初步分析.中国海洋大学学报,38(4):601-604
Hu C M,2009.A novel ocean color index to detect floating algae in the global oceans.Remote Sensing of Environment,113(10):2118-2129
Hu C M,Li D Q,Chen C S et al,2010.On the recurrent Ulva prolifera blooms in the Yellow Sea and East China Sea.Journal of Geophysical Research:Oceans,115(C5):C05017
Liu D Y,Keesing J K,Xing Q G et al,2009.World’s largest macroalgal bloom caused by expansion of seaweed aquaculture in China.Marine Pollution Bulletin,58(6):888-895
Lou X L,Hu C M,2014.Diurnal changes of a harmful algal bloom in the East China Sea:observations from GOCI.Remote Sensing of Environment,140:562-572
Shi W,Wang M H,2009.Green macroalgae blooms in the Yellow Sea during the spring and summer of 2008.Journal of Geophysical Research:Oceans,114(C12):C12010
Son Y B,Min J E,Ryu J H,2012.Detecting massive green algae(Ulva prolifera)blooms in the Yellow Sea and East China Sea using Geostationary Ocean Color Imager(GOCI)data.Ocean Science Journal,47(3):359-375
Xing Q G,Hu C M,2016.Mapping macroalgal blooms in the Yellow Sea and East China Sea using HJ-1 and landsat data:application of a virtual baseline reflectance height technique.Remote Sensing of Environment,178:113-126