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Unmanned aerial vehicles and low-cost sensor as tools for monitoring freshwater chlorophyll-a in mesocosms with different trophic state

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Abstract

Eutrophication is one of the leading causes of compromising the quality of freshwater and marine ecosystems, where the concentration of chlorophyll-a is an essential variable to monitoring the water quality. Moreover, monitoring in situ chlorophyll-a require constants samplings, high laboratory, and logistics costs, and sometimes in regions not accessible. Therefore, new technology can be important to increase the monitoring the water quality. In this sense, this work aimed to evaluate remote sensing techniques, from unmanned aerial vehicles (UAV), onboard low-cost sensors (RGB), to determine chlorophyll-a in aquatic environments. The experiment consisted of 26 mesocosms, where phytoplankton samples were inserted, simulating small shallow lakes, with gradual additions of nitrogen and phosphorus, until a trophic gradient was obtained. Subsequently, in situ concentrations of chlorophyll-a and aerial images with the UAV were obtained. The images were processed to generate orthorectified mosaics and calculate eight vegetation indices (NGBDI, SI, NGRDI, SCI, VWRI, GLI, EXG, and VARI) by which simple linear regressions were adjusted as a function of chlorophyll-a concentrations. All indexes were able to detect the gradient of chlorophyll-a, and the best index was NGBDI (R2 = 0.88). The vegetation indices already used in aquatic environments showed greater efficiency in detecting chlorophyll-a in situ. Therefore, our results indicated that monitoring water quality for the evaluated parameters could be carried out by remotely piloted aircraft, onboard with standard RGB cameras, with faster, simpler, and lower cost protocols.

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Data availability

The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.

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Acknowledgements

This study was developed in the context of National Institute for Science and Technology (INCT) in Ecology, Evolution and Biodiversity Conservation, supported by MCTIC/CNPq (proc. 465610/2014-5), Brazilian Network on Global Climate Change Research (Rede Clima), and Fundação de Amparo à Pesquisa do Estado de Goiás (FAPEG). M.E.F. (grant #315699/2020-5) and J.C.N. (grant #305798/2019-7) are CNPq Research Fellows.

Funding

This study was funded by FAPEG (Fundação de Amparo à Pesquisa do Estado de Goiás) and CNPq (Conselho Nacional de Desenvolvimento Científico e Tecnológico) for scholarships and productivity grants. This study was financed in part by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior—Brazil (CAPES)—Finance Code 001. National Institutes for Science and Technology (INCT) in Ecology, Evolution and Biodiversity Conservation (MCTI/CNPq/FAPEG/465610/2014–5), and Brazilian Network on Global Climate Change Research (Rede CLIMA).

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Contributions

IC was involved in the conception and design, analysis and interpretation of data, acquisition of data, and drafting of the article. KBM helped in the conception and design, analysis and interpretation of data, acquisition of data, and drafting of the article. ACMD contributed to the conception and design, analysis and interpretation of data, acquisition of data, and drafting of the article. MEF was involved in the conception and design, analysis and interpretation of data, acquisition of data, and drafting of the article. PC contributed to the analysis and interpretation of data, acquisition of data, and drafting of the article. JCN contributed to the conception and design, analysis and interpretation of data, drafting of the article, and revising critically for important intellectual content.

Corresponding author

Correspondence to J. C. Nabout.

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All authors certify that they have no affiliations with or involvement in any organization or entity with any financial interest or non-financial interest in the subject matter or materials discussed in this manuscript.

Ethics approval

Not applicable. The present study did not involve research with humans or animals.

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Editorial responsibility: Jing Chen.

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Cobelo, I., Machado, K.B., David, A.C.M. et al. Unmanned aerial vehicles and low-cost sensor as tools for monitoring freshwater chlorophyll-a in mesocosms with different trophic state. Int. J. Environ. Sci. Technol. 20, 5925–5936 (2023). https://doi.org/10.1007/s13762-022-04386-3

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  • DOI: https://doi.org/10.1007/s13762-022-04386-3

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