Dynamic Diurnal Changes in Green Algae Biomass in the Southern Yellow Sea Based on GOCI Images
Dynamic Diurnal Changes in Green Algae Biomass in the Southern Yellow Sea Based on GOCI Images
复制标题
基于GOCI图像的南黄海绿藻生物量动态日变化
DOI：
10.1007/s11802-020-4183-0
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发表时间：
2020-07
影响因子：
1.6
通讯作者：
Obodoefuna Doris Chigozie
中科院分区：
文献类型：
--
作者：
Jiang Binbin;Fan Daidu;Ji Qingyuan;Obodoefuna Doris Chigozie
自2007年以来，南黄海每年夏季都会发生石莼水华，造成严重的生态问题和巨大的经济损失。绿色藻华的发生和长期运动已被很好地利用遥感和其他方法监测。利用静止海洋水色成像仪（GOCI）对绿色藻类进行了探测和跟踪，并根据生物量测量值与卫星生物量指数之间的关系建立了一种新的生物量估算模型。结果表明，利用ENVI/QUAC方法对Rsurf数据进行大气校正后，计算得到的GOCI绿色藻类生物量指数（BIGAG）能够最准确地确定绿色生物量。首次研究了绿色藻类生物量在小时尺度上的动态变化。短期生物量变化的光合有效辐射（PAR）和潮汐阶段的影响很大，但较小的海表温度变化的日常时间尺度。生物量增长率与运动速度之比计算的生物量变化参数（PBC）可为南黄海及类似海域的绿色潮评估和预报提供一种有效的方法。
Macroalgae blooms ofUlva proliferahave occurred every summer in the southern Yellow Sea since 2007, inducing severe ecological problems and huge economic losses. Genesis and secular movement of green algae blooms have been well monitored by using remote sensing and other methods. In this study, green algae were detected and traced by using Geostationary Ocean Color Imager (GOCI), and a novel biomass estimation model was developed from the relationship between biomass measurements and previously published satellite-derived biomass indexes. The results show that the green algae biomass can be determined most accurately with the biomass index of green algae for GOCI (BIGAG), which is calculated from the Rsurf data that had been atmospherically corrected by ENVI/QUAC method. For the first time, dynamic changes in green algae biomass were studied over an hourly scale. Short-term biomass changes were highly influenced by Photosynthetically Available Radiation (PAR) and tidal phases, but less by sea surface temperature variations on a daily timescale. A new parameter of biomass changes (PBC), calculated by the ratio of the biomass growth rate to movement velocity, could provide an effective way to assess and forecast green tide in the southern Yellow Sea and similar areas.
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影响因子：
3.3
作者：
Hugo Pliego-Cortés;E. Caamal-Fuentes;J. Montero-Muñoz;Y. Freile-Pelegrín;D. Robledo
通讯作者：
Hugo Pliego-Cortés;E. Caamal-Fuentes;J. Montero-Muñoz;Y. Freile-Pelegrín;D. Robledo
DOI：
10.1117/12.2073158
发表时间：
2014-11
期刊：
--
影响因子：
--
作者：
Binbin Jiang;Xiaoyu Zhang;Yong Du;D. Huang
通讯作者：
Binbin Jiang;Xiaoyu Zhang;Yong Du;D. Huang
影响因子：
4.6
作者：
Li H;Zhang Y;Han X;Shi X;Rivkin RB;Legendre L
通讯作者：
Legendre L
影响因子：
13.5
作者：
Y. Son;Byoung-Ju Choi;Y. H. Kim;Young‐Gyu Park
通讯作者：
Y. Son;Byoung-Ju Choi;Y. H. Kim;Young‐Gyu Park
影响因子：
4.6
作者：
Delgado-Bonal A
通讯作者：
Delgado-Bonal A