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

Manuel Viso-Vázquez, Carolina Acuña-Alonso, Juan Luis Rodríguez and Xana Álvarez
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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

Sustainability, 2021, vol. 13, issue 15, 1-17

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.

Keywords: Sentinel-2; remote sensing; cyanobacteria; water quality; water security (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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