Monitoring cyanobacteria occurrence in freshwater reservoirs using semi-analytical algorithms and orbital remote sensing
Henrique Dantas Borges
A B , Rejane Ennes Cicerelli A , Tati de Almeida A , Henrique L. Roig A and Diogo Olivetti A
+ Author Affiliations
- Author Affiliations
A Geociences Institute, University of Brasília, Campus Universitário Darcy Ribeiro ICC-Ala Central, 71910-900 Brasília, Brazil.
B Corresponding author. Email: henriquedantasborges@gmail.com
Marine and Freshwater Research 71(5) 569-578 https://doi.org/10.1071/MF18377
Submitted: 2 October 2018 Accepted: 10 February 2019 Published: 7 May 2019
Abstract
Cyanobacterial blooms pose a serious threat to the multiple uses of inland waters because of their adverse effects on the environment and human health. Monitoring cyanobacteria concentrations using traditional methods can be expensive and impractical. Recently, alternative efforts using remote sensing techniques have been successful. In particular, semi-analytical modelling approaches have been used to successfully predict chlorophyll (Chl)-a concentrations from remote sensing reflectance. The aims of this study were to test the performance of different semi-analytical algorithms in the estimation of Chl-a concentrations and the applicability of Sentinel-2 multispectral instrument (MSI) imagery, and its atmospheric correction algorithms, in the estimation of Chl-a concentrations. For our dataset, phycocyanin concentration was strongly correlated with Chl-a concentration and the inversion model of inland waters (IIMIW) semi-analytical algorithm was the best performing model, achieving a root mean square error of 4.6 mg m–3 in the prediction of Chl-a. When applying the IIMIW model to MSI data, the use of top-of-atmosphere reflectance performed better than the atmospheric correction algorithm tested. Overall, the results were satisfactory, demonstrating that even without an adequate atmospheric correction pipeline, the monitoring of cyanobacteria can be successfully achieved by applying a semi-analytical bio-optical model to MSI data.
Additional keywords: eutrophication, quasi-analytical algorithm, tropical freshwater, water quality monitoring.
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