Estimation of cyanobacteria biovolume in water reservoirs by MERIS sensor

• Cyanobacterial biovolume was measured from 23 water reservoirs.
• Phycocyanin concentration was estimated from MERIS sensor images.
• Linear regression between these two parameters showed a correlation of R2 = 0.62.
• Chlorophyll-a concentration measured from the same samples showed a correlation of R2 = 0.94.
• Measured and estimated biovolume on the same day showed a high correlation (R2 = 0.72).

Planktonic cyanobacteria primarily develop in lentic water bodies, such as lakes and water reservoirs. In certain instances, toxin-producing cyanobacterial populations might dominate the phytoplankton community. Satellite remote sensing is a useful tool for large spatial scale monitoring of cyanobacteria, and the MERIS sensor from the Envisat satellite has taken worldwide images at a high frequency for over 10 years. This short time lapse image collection has provided an extensive record of images for the analysis of variation in the cyanobacterial communities in water reservoirs for management and scientific purposes. The objective of this work is to determine the relationship between measured cyanobacterial biomass as biovolume and the estimations derived from MERIS imagery. This study encompasses two independent studies relying on data from 23 water reservoirs. First, a long-term global limnological research study was conducted that provided a field data collection that included cyanobacterial biovolume, among other variables. Second, a survey was conducted that applied the processed images derived from the Envisat MERIS sensor. The chlorophyll-a (Chl a) content and phycocyanin concentration (PC) were estimated from the MERIS images. The PC estimated by remote sensing and total cyanobacterial biovolume measured from the field samples were found to be significantly correlated (R2 = 0.6219; p < 0.001). No relevant differences were found among the taxonomical groups, which indicated that this tool provides accurate estimations irrespective of the cyanobacterial group. For validation, the algorithm derived from the entire dataset was applied to the MERIS image dataset of the Rosarito reservoir. An estimated cyanobacterial biovolume time series was performed and compared to the biovolume data collected in an extensive sampling schedule spanning 4 years. The results indicated a strong correlation (R2 = 0.72; p < 0.001) between the measured and estimated data acquired on the same day.

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