Influence of phytoplankton pigment composition on remote sensing of cyanobacterial biomass
Influence of phytoplankton pigment composition on remote sensing of cyanobacterial biomass
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DOI：
10.1016/j.rse.2006.09.008
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发表时间：
2007-02
影响因子：
13.5
通讯作者：
S. Simis;A. Ruiz-Verdú;J. Domínguez-Gómez;Ramón Peña-Martínez;S. Peters;H. Gons
中科院分区：
文献类型：
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作者：
S. Simis;A. Ruiz-Verdú;J. Domínguez-Gómez;Ramón Peña-Martínez;S. Peters;H. Gons
一个广泛的实地活动进行了验证先前发表的基于反射率的算法定量的蓝藻色素藻蓝蛋白（PC）。该算法使用波段设置的中分辨率成像光谱仪（MERIS）机载ENVISAT，并应准确地检索PC浓度混浊，蓝藻为主的沃茨。由于藻类和蓝细菌经常共存，因此探索了算法对不同浮游植物组成的响应。2001-2005年期间，在西班牙和荷兰使用实地分光辐射测量法和各种色素提取方法获得了遥感反射率和参考色素测量值。2005年5月在西班牙收集了更多的实地数据，以便对分光辐射度和色素评估方法进行相互校准。两种方法从浓缩水样中提取PC，并在现场测量PC荧光，比较好。在西班牙和荷兰使用的不同的现场分光辐射计的反射率测量也给出了类似的结果。残差分析结果表明，在叶绿素B、叶绿素c和脱镁叶绿素存在的情况下，PC值被高估。在低PC相对于叶绿素a浓度的错误是最强的。对叶绿素B的吸收进行校正后，预测值明显提高。如果没有这样的校正，PC预测的质量仍然显著提高，估计值>50 mg PC m−3，允许监测富营养化沃茨的蓝藻状态。当预期细胞内PC：Chl a比率较高或蓝藻占优势时，阈值浓度可能会降低。低于限值时，应将预测PC浓度视为最高估计值。我们评估，遥感PC和叶绿素a将允许评估蓝藻对水质和公众健康的风险超过70%的情况下。
An extensive field campaign was carried out for the validation of a previously published reflectance ratio-based algorithm for quantification of the cyanobacterial pigment phycocyanin (PC). The algorithm uses band settings of the Medium Resolution Imaging Spectrometer (MERIS) onboard ENVISAT, and should accurately retrieve the PC concentration in turbid, cyanobacteria-dominated waters. As algae and cyanobacteria often co-occur, the algorithm response to varying phytoplankton composition was explored. Remote sensing reflectance and reference pigment measurements were obtained in the period 2001–2005 in Spain and the Netherlands using field spectroradiometry and various pigment extraction methods. Additional field data was collected in Spain in May 2005 to allow intercalibration of spectroradiometry and pigment assessment methods. Two methods for extraction of PC from concentrated water samples, and in situ measured PC fluorescence, compared well. Reflectance measurements with different field spectroradiometers used in Spain and the Netherlands also gave similar results. Residual analysis of PC predicted by the algorithm showed that overestimation of PC mainly occurred in the presence of chlorophylls b and c, and phaeophytin. The errors were strongest at low PC relative to Chl a concentrations. A correction applied for absorption by Chl b markedly improved the prediction. Without such a correction, the quality of the PC prediction still increased markedly with estimates >50 mg PC m−3, allowing monitoring of the cyanobacterial status of eutrophic waters. The threshold concentration may be lowered when a high intracellular PC:Chl a ratio or cyanobacterial dominance is expected. Below the limit, predicted PC concentrations should be considered as the highest estimate. We evaluated that remote sensing of both PC and Chl a would allow assessment of cyanobacterial risk to water quality and public health in over 70% of our cases.