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The effects of cyanobacterial blooms on MODIS-L2 data products in the southern Caspian Sea

机译:蓝藻绽放对南部海洋MODIS-L2数据产品的影响

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摘要

MODIS satellite imageries with minimal cloud cover (25%) were used to extract cyanobacteria index, floating algea index, fluorescence line height, chlorophyll-a and sea surface temperature products, for seven days concurrent with blooms. The results showed a positive correlation between cyanobacteria index and chlorophyll-a (R = 0.74, p = 0.05 and R= 0.75, p = 0.05 for 2005 and 2010 respectively), and a negative correlation between the cyanobacteria index and fluorescence line height (R = -0.74, p = 0.05 and R = -0.93, p = 0.005 for 2005 and 2010 respectively). Further analysis showed that considering Fluorescence Line Height is not sufficient to detect the cyanobacterial blooms in the offshore area. However, the results indicated a weak correlation between cyanobacteria index and floating algae index (R = -0.42, p = 0.34 and R= -0.47, p = 0.29 for 2005 and 2010 respectively). The results also indicated that the irregular increases in the cyanobacteria index and chlorophyll-a in the study region was an operational index for the incidence of cyanobacterial bloom, where the surface wind speed and temperature conditions were 4 m s(-1) and = 30 degrees C, respectively. Finally, a linear model was defined for monitoring, which determines occurrence or non-occurrence of cyanobacteria bloom based on daily monitoring of the changes of products. In order to evaluate the proposed model, its efficiency was tested on datasets at different times and locations, and the results were consistent with field reports, as expected. (C) 2018 Institute of Oceanology of the Polish Academy of Sciences. Production and hosting by Elsevier Sp. z o.o.
机译:MODIS卫星成像具有最小云盖(& 25%),用于提取蓝藻指数,浮动藻类指数,荧光线高度,叶绿素-A和海表面温度产品,七天并发绽放。结果表明,蓝藻指数和叶绿素-α(r = 0.74,p = 0.05和r = 0.75,p& = 0.05分别为2005和2010)之间的正相关性,以及蓝细菌指数和荧光之间的负相关性线高度(r = -0.74,p& = 0.05和r = -0.93,p& 2005和2010分别为0.005)。进一步的分析表明,考虑荧光线高度不足以检测近海地区中的蓝藻绽放。然而,结果表明,蓝细菌指数和浮藻指数(r = -0.42,p = 0.34和r = -0.47,P = 0.29分别为2005和2010)。结果还表明,研究区中的蓝细菌指数和叶绿素-A的不规则增加是蓝藻绽放的发病率的操作指标,其中表面风速和温度条件是<4 ms(-1)和&gt ; = 30摄氏度。最后,为监测定义了线性模型,该模型基于日常监测产品变化的日常监测来确定蓝藻盛开的发生或非发生。为了评估所提出的模型,其效率在不同时间和位置的数据集上进行了测试,结果与预期的现场报告一致。 (c)2018波兰科氏院海洋学院。由elsevier sp生产和托管。动物园。

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