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基于GOCI的2017年南黄海浒苔演变遥感分析

文献类型：期刊论文

作者宋德彬; 高志强; 徐福祥; 艾金泉; 宁吉才; 尚伟涛; 姜晓鹏
刊名海洋与湖沼
出版日期2018-09-15
卷号49期号:05页码:1068-1074
关键词GOCI 浒苔 南黄海 遥感 GOCI ulva prolifera the south Yellow Sea remote sensing
ISSN号0029-814X
DOI10.11693/hyhz20171200330
其他题名SPATIAL AND TEMPORAL VARIABILITY OF THE GREEN TIDE IN THE SOUTH YELLOW SEA IN 0 DECIPHERED FROM THE GOCI IMAGE
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
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.
语种中文
CSCD记录号CSCD:6343545
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
源URL[http://ir.yic.ac.cn/handle/133337/24678]  
专题烟台海岸带研究所_海岸带信息集成与综合管理实验室
烟台海岸带研究所_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.中国科学院大学;
2.中国科学院烟台海岸带研究所;
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.

入库方式： OAI收割

来源：烟台海岸带研究所

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