Quantitative detection of chlorophyll in cyanobacterial blooms by satellite remote sensing
Quantitative detection of chlorophyll in cyanobacterial blooms by satellite remote sensing
复制标题
DOI：
10.4319/lo.2004.49.6.2179
复制
发表时间：
2004-11-01
影响因子：
4.5
通讯作者：
Kutser, T
中科院分区：
文献类型：
--
作者：
Kutser, T
蓝藻水华的范围已经使用从气象卫星到合成孔径雷达的不同卫星传感器绘制了地图。然而，通过遥感对蓝藻水华中的叶绿素进行定量检测却不太成功。太空中的第一个民用高光谱传感器Hyperion于2002年7月14日在芬兰湾西部获得了蓝藻水华的图像。通过运行具有不同浓度的叶绿素的生物光学模型创建的光谱库，从这张图像生成了一张叶绿素浓度图。结果表明，水华地区的叶绿素浓度远远高于传统的水监测项目、机遇号和卫星测量报告。在蓝藻水华期间，原位和卫星方法都低估了浮游植物的数量，原因是蓝藻在垂直和水平方向上的分布，因为蓝藻可以调节它们的浮力，在平静的天气条件下，蓝藻在水柱的顶部混合层中分布不均匀。在大规模水华期间，蓝藻聚集形成密集的地下水华和表面浮渣。这项研究表明，使用标准方法很难从研究船只上采集有代表性的水样，因为船只和水样采样器在采样过程中破坏了蓝藻的自然分布。流通式系统从蓝藻浓度与遥感仪器检测到的浮游植物数量没有相关性的深处采集水样。由于空间分辨率的限制，许多卫星对蓝藻水华的叶绿素估计精度受到限制，因为即使在小于30m的空间尺度上，叶绿素浓度也会发生显著变化。
The extent of cyanobacterial blooms has been mapped using different satellite sensors from weather satellites to synthetic aperture radars. Quantitative detection of chlorophyll in cyanobacterial blooms by remote sensing, however, has been less successful. The first civilian hyperspectral sensor in space, Hyperion, acquired an image of cyanobacterial bloom in the western part of the Gulf of Finland on 14 July 2002. A chlorophyll concentration map was produced from this image using a spectral library that was created by running a bio-optical model with variable concentrations of chlorophyll. The results show that chlorophyll concentrations in the bloom area were much higher than reported by conventional water-monitoring programs, ships-of-opportunity, and satellite measurements. The reason why both in situ and satellite methods underestimate the amount of phytoplankton during cyanobacterial blooms is vertical and horizontal distribution of cyanobacteria, because cyanobacteria can regulate their buoyancy and are not uniformly distributed within the top mixed layer of water column in calm weather conditions. Aggregations of cyanobacteria form dense subsurface blooms and surface scums during extensive blooms. This study demonstrates that it is difficult to collect representative water samples from research vessels using standard methods because ships and water samplers destroy the natural distribution of cyanobacteria in the sampling process. Flow-through systems take water samples from the depths at which the concentration of cyanobacteria is not correlated with the amount of phytoplankton that remote sensing instruments detect. The chlorophyll estimation accuracy in cyanobacterial blooms by many satellites is limited because of spatial resolution, as significant changes in chlorophyll concentration occur even at a smaller spatial scale than 30 m.