| 摘要: |
| 本研究利用高分辨率的GF-1卫星影像对MODIS数据绿潮监测的精度进行验证, 并在此基础上利用MODIS数据对2016年黄海绿潮过程进行连续动态监测, 结果表明: 相较于GF-1卫星影像,MODIS数据对绿潮的监测误差高于50%; 2016年黄海绿潮移动路径总体呈先向北, 然后沿山东半岛海岸线向东北方向移动, 并最终停滞于青岛、威海附近海域; 此次绿潮持续时间为80天左右, 并呈现出与往年类似的“出现→发展→暴发→治理→消亡”的规律; 其中“出现”的时间为5月12日, “发展”阶段时间为5月中下旬, 此时绿潮主体分布于苏北浑水区, 适宜前置打捞治理, 当5月底6月初绿潮进入清水区之后才开始进入“暴发”阶段, 本年度绿潮灾害“暴发”规模较大, 对山东沿海水产养殖业及旅游业影响严重。本研究成果对于绿潮预警和防控具有科学和实际意义。 |
| 关键词: MODIS 绿潮 GF-1 验证 动态监测 |
| DOI：10.11759/hykx20160922003 |
| 分类号: |
| 基金项目: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); 中国科学院重点部署项目(KZZD-EW-14); 中国科学院战略性先导科技专项(A 类)(XDA11020000); 科技部基础支撑项目(2014FY210600); 中国科学院烟台海岸带所人才引进项目 |
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| Spatial and temporal distribution characteristic of green tides in the Yellow Sea in 2016 based on MODIS data |
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XU Fu-xiang,GAO Zhi-qiang,ZHENG Xiang-yu,NING Ji-cai,SONG De-bin
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| Abstract: |
| This paper analyses the errors of the Green Tides monitoring results from MODIS data with high resolution GF-1 WFV satellite images based on the assumption that pixels of GF-1 WFV data are pure. On this basis, continuous and dynamic monitoring of the Green Tides of the Yellow Sea in 2016 were performed. The results show that the total error of the monitoring results using MODIS data is higher than 50%; the Green Tide moved northwards first, then moved in the northeast direction along the coastline of Shandong Peninsula, and finally was stranded in the sea areas near Qingdao and Weihai in 2016; Green Tides lasted around 80 days at this time, and showed a regularity similar to that of previous years, that is, it first appeared, developed and exploded, then was disposed, and finally disappeared. In detail, it appeared on May 12, it developed in mid-to late-May, at which period the main body of the Green Tide was distributed in muddy water in Subei Shoal, and began to explode in late May and early June after entering clear water. Based on these aspects, the macroalgal blooms caused by Ulva prolifera in 2016 were very serious and had huge impacts on the coastal aquaculture and tourism industry of Shandong Province. |
| Key words: MODIS Green Tides GF-1 error analysis dynamic monitoring |
