Original ArticlesDeveloping a two-step method for retrieving cyanobacteria abundance from inland eutrophic lakes using MERIS data

- A two-step method was developed to estimate cyanobacteria abundance.
- MERIS bands of 5, 6 and 7 play the most important roles in estimating cyanobacteria abundance.
- [aph(624)−aph(550)]/[aph(624)+aph(550)] can be used to indicate cyanobacteria abundance.
- PC:Chl-a cannot be used as index of cyanobacteria abundance.

Cyanobacteria are the main dominant species in inland eutrophic lakes during algae blooms, and measures of cyanobacteria abundance can be used for monitoring and early detection of algal blooms by remote sensing. During May 2013 and August 2016, a total 137 water samples were collected from Lake Taihu and Lake Chaohu. Remote-sensing reflectance was measured, surface water was collected in the field, and chlorophyll-a concentration, phycocyanin concentration, suspended-matter concentration and phytoplankton pigment absorption parameters were measured in the laboratory. The composition and density of planktonic algae were also detected by microscope examination. The remote-sensing reflectance at 15 MERIS bands was simulated based on our measured spectral data, and a two-step method for detecting cyanobacteria abundance using the partial least squares model based on 5 MERIS bands was developed. The results showed that the estimation algorithm can predict cyanobacteria abundance in inland eutrophic lakes with satisfactory accuracy, with RMSE of 7.56 and MAPE of 13.44 %. This algorithm was successfully applied to the MERIS image acquired on August 12, 2010, and showed a reasonable spatial distribution of cyanobacteria abundance in Lake Taihu. It demonstrated that the developed estimation method was an effective way to monitor cyanobacteria abundance in water with a potential to be successfully applied to Sentinel-3 images.