其他题名SPATIAL AND TEMPORAL VARIABILITY OF THE GREEN TIDE IN THE SOUTH YELLOW SEA IN 0 DECIPHERED FROM THE GOCI IMAGE
宋德彬; 高志强
; 徐福祥; 艾金泉; 宁吉才; 尚伟涛; 姜晓鹏发表期刊海洋与湖沼
ISSN0029-814X
2018-09-15
卷号49期号:05页码:1068-1074
关键词GOCI浒苔南黄海遥感GOCIulva proliferathe south Yellow Searemote sensing
研究领域海洋学
DOI10.11693/hyhz20171200330
产权排序(1)中国科学院烟台海岸带研究所; (2)中国科学院大学; (3)华东师范大学地理信息科学教育部重点实验室
作者部门海岸带信息集成与综合管理实验室
英文摘要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 2363.12km~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.
中文摘要本文应用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。
资助机构青岛海洋科学与技术国家实验室鳌山科技创新计划项目#2016ASKJ02; 国家自然科学基金项目#41876107山东省联合基金项目#U1706219; 科技部基础支撑项目#2014FY210600
收录类别CSCD
语种中文
CSCD记录号CSCD:6343545
引用统计
文献类型期刊论文
条目标识符http://ir.yic.ac.cnhttp://ir.yic.ac.cn/handle/133337/24678
专题中科院海岸带环境过程与生态修复重点实验室_海岸带信息集成与战略规划研究中心
中科院海岸带环境过程与生态修复重点实验室
作者单位1.中国科学院烟台海岸带研究所;
2.中国科学院大学;
3.华东师范大学地理信息科学教育部重点实验室
推荐引用方式
GB/T 7714宋德彬,高志强,徐福祥,等. 基于GOCI的2017年南黄海浒苔演变遥感分析[J]. 海洋与湖沼,2018,49(05):1068-1074.
APA宋德彬.,高志强.,徐福祥.,艾金泉.,宁吉才.,...&姜晓鹏.(2018).基于GOCI的2017年南黄海浒苔演变遥感分析.海洋与湖沼,49(05),1068-1074.
MLA宋德彬,et al."基于GOCI的2017年南黄海浒苔演变遥感分析".海洋与湖沼 49.05(2018):1068-1074.
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