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Remote Detection of Cyanobacterial Blooms and Chlorophyll-a Analysis in a Eutrophic Reservoir Using Sentinel-2

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  • Manuel Viso-Vázquez

    (School of Forestry Engineering, University of Vigo, Campus A Xunqueira s/n., 36005 Pontevedra, Spain)

  • Carolina Acuña-Alonso

    (School of Forestry Engineering, University of Vigo, Campus A Xunqueira s/n., 36005 Pontevedra, Spain)

  • Juan Luis Rodríguez

    (CINTECX, GeoTECH Research Group, Universidade de Vigo, 36310 Vigo, Spain)

  • Xana Álvarez

    (School of Forestry Engineering, University of Vigo, Campus A Xunqueira s/n., 36005 Pontevedra, Spain)

Abstract

Harmful cyanobacterial blooms have been one of the most challenging ecological problems faced by freshwater bodies for more than a century. The use of satellite images as a tool to analyze these blooms is an innovative technology that will facilitate water governance and help develop measures to guarantee water security. To assess the viability of Sentinel-2 for identifying cyanobacterial blooms and chlorophyl-a, different bands of the Sentinel-2 satellite were considered, and those most consistent with cyanobacteria analysis were analyzed. This analysis was supplemented by an assessment of different indices and their respective correlations with the field data. The indices assessed were the following: Normalized Difference Water Index (NDWI), Normalized Differences Vegetation Index (NDVI), green Normalized Difference Vegetation Index (gNDVI), Normalized Soil Moisture Index (NSMI), and Toming’s Index. The green band (B3) obtained the best correlating results for both chlorophyll (R 2 = 0.678) and cyanobacteria (R 2 = 0.931). The study by bands of cyanobacteria composition can be a powerful tool for assessing the physiology of strains. NDWI gave an R 2 value of 0.849 for the downstream point with the concentration of cyanobacteria. Toming’s Index obtained a high R 2 of 0.859 with chlorophyll-a and 0.721 for the concentration of cyanobacteria. Notable differences in correlation for the upstream and downstream points were obtained with the indices. These results show that Sentinel-2 will be a valuable tool for lake monitoring and research, especially considering that the data will be routinely available for many years and the images will be frequent and free.

Suggested Citation

  • Manuel Viso-Vázquez & Carolina Acuña-Alonso & Juan Luis Rodríguez & Xana Álvarez, 2021. "Remote Detection of Cyanobacterial Blooms and Chlorophyll-a Analysis in a Eutrophic Reservoir Using Sentinel-2," Sustainability, MDPI, vol. 13(15), pages 1-17, July.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:15:p:8570-:d:606172
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    References listed on IDEAS

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    1. Álvarez, X. & Valero, E. & Santos, R.M.B. & Varandas, S.G.P. & Sanches Fernandes, L.F. & Pacheco, F.A.L., 2017. "Anthropogenic nutrients and eutrophication in multiple land use watersheds: Best management practices and policies for the protection of water resources," Land Use Policy, Elsevier, vol. 69(C), pages 1-11.
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    Cited by:

    1. Xiyong Zhao & Yanzhou Li & Yongli Chen & Xi Qiao, 2022. "A Method of Cyanobacterial Concentrations Prediction Using Multispectral Images," Sustainability, MDPI, vol. 14(19), pages 1-15, October.

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