Phycocyanin Monitoring in Some Spanish Water Bodies with Sentinel-2 Imagery
Remote sensing is an appropriate tool for water management. It allows the study of some of the main sources of pollution, such as cyanobacterial harmful algal blooms. These species are increasing due to eutrophication and the adverse effects of climate change. This leads to water quality loss, which...
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-10-01
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| Series: | Water |
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| Online Access: | https://www.mdpi.com/2073-4441/13/20/2866 |
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| author | Rebeca Pérez-González Xavier Sòria-Perpinyà Juan Miguel Soria Jesús Delegido Patricia Urrego María D. Sendra Antonio Ruíz-Verdú Eduardo Vicente José Moreno |
| author_facet | Rebeca Pérez-González Xavier Sòria-Perpinyà Juan Miguel Soria Jesús Delegido Patricia Urrego María D. Sendra Antonio Ruíz-Verdú Eduardo Vicente José Moreno |
| author_sort | Rebeca Pérez-González |
| collection | DOAJ |
| description | Remote sensing is an appropriate tool for water management. It allows the study of some of the main sources of pollution, such as cyanobacterial harmful algal blooms. These species are increasing due to eutrophication and the adverse effects of climate change. This leads to water quality loss, which has a major impact on the environment, including human water supplies, which consequently require more expensive purification processes. The application of satellite remote sensing images as bio-optical tools is an effective way to monitor and control phycocyanin concentrations, which indicate the presence of cyanobacteria. For this study, 90 geo-referenced phycocyanin measurements were performed in situ, using a Turner C3 Submersible Fluorometer and a laboratory spectrofluorometer, both calibrated with phycocyanin standard, in water bodies of the Iberian Peninsula. These samples were synchronized with Sentinel-2 satellite orbit. The images were processed using Sentinel Application Program software and corrected with the Case 2 Regional Coast color-extended atmospheric correction tool. To produce algorithms that would help to obtain the phycocyanin concentration from the reflectance measured by the multispectral instrument sensor of the satellite, the following band combinations were tested, among others: band 665 nm, band 705 nm, and band 740 nm. The samples were equally divided: half were used for the algorithm’s calibration, and the other half for its validation. With the best adjustment, the algorithm was made more robust and accurate through a recalculation, obtaining a determination coefficient of 0.7, a Root Mean Square Error of 8.1 µg L<sup>−1</sup>, and a Relative Root Mean Square Error of 19%. In several reservoirs, we observed alarming phycocyanin concentrations that may trigger many environmental health problems, as established by the World Health Organization. Remote sensing provides a rapid monitoring method for the temporal and spatial distribution of these cyanobacteria blooms to ensure good preventive management and control, in order to improve the environmental quality of inland waters. |
| first_indexed | 2024-03-10T06:08:59Z |
| format | Article |
| id | doaj.art-efffd3cfd7344e9d97f47e44c5ee0da0 |
| institution | Directory Open Access Journal |
| issn | 2073-4441 |
| language | English |
| last_indexed | 2024-03-10T06:08:59Z |
| publishDate | 2021-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Water |
| spelling | doaj.art-efffd3cfd7344e9d97f47e44c5ee0da02023-11-22T20:21:54ZengMDPI AGWater2073-44412021-10-011320286610.3390/w13202866Phycocyanin Monitoring in Some Spanish Water Bodies with Sentinel-2 ImageryRebeca Pérez-González0Xavier Sòria-Perpinyà1Juan Miguel Soria2Jesús Delegido3Patricia Urrego4María D. Sendra5Antonio Ruíz-Verdú6Eduardo Vicente7José Moreno8Cavanilles Institute of Biodiversity and Evolutionary Biology (ICBiBE), Universitat de València, 46980 Valencia, SpainImage Processing Laboratory (IPL), Universitat de València, 46980 Valencia, SpainCavanilles Institute of Biodiversity and Evolutionary Biology (ICBiBE), Universitat de València, 46980 Valencia, SpainImage Processing Laboratory (IPL), Universitat de València, 46980 Valencia, SpainImage Processing Laboratory (IPL), Universitat de València, 46980 Valencia, SpainCavanilles Institute of Biodiversity and Evolutionary Biology (ICBiBE), Universitat de València, 46980 Valencia, SpainImage Processing Laboratory (IPL), Universitat de València, 46980 Valencia, SpainCavanilles Institute of Biodiversity and Evolutionary Biology (ICBiBE), Universitat de València, 46980 Valencia, SpainImage Processing Laboratory (IPL), Universitat de València, 46980 Valencia, SpainRemote sensing is an appropriate tool for water management. It allows the study of some of the main sources of pollution, such as cyanobacterial harmful algal blooms. These species are increasing due to eutrophication and the adverse effects of climate change. This leads to water quality loss, which has a major impact on the environment, including human water supplies, which consequently require more expensive purification processes. The application of satellite remote sensing images as bio-optical tools is an effective way to monitor and control phycocyanin concentrations, which indicate the presence of cyanobacteria. For this study, 90 geo-referenced phycocyanin measurements were performed in situ, using a Turner C3 Submersible Fluorometer and a laboratory spectrofluorometer, both calibrated with phycocyanin standard, in water bodies of the Iberian Peninsula. These samples were synchronized with Sentinel-2 satellite orbit. The images were processed using Sentinel Application Program software and corrected with the Case 2 Regional Coast color-extended atmospheric correction tool. To produce algorithms that would help to obtain the phycocyanin concentration from the reflectance measured by the multispectral instrument sensor of the satellite, the following band combinations were tested, among others: band 665 nm, band 705 nm, and band 740 nm. The samples were equally divided: half were used for the algorithm’s calibration, and the other half for its validation. With the best adjustment, the algorithm was made more robust and accurate through a recalculation, obtaining a determination coefficient of 0.7, a Root Mean Square Error of 8.1 µg L<sup>−1</sup>, and a Relative Root Mean Square Error of 19%. In several reservoirs, we observed alarming phycocyanin concentrations that may trigger many environmental health problems, as established by the World Health Organization. Remote sensing provides a rapid monitoring method for the temporal and spatial distribution of these cyanobacteria blooms to ensure good preventive management and control, in order to improve the environmental quality of inland waters.https://www.mdpi.com/2073-4441/13/20/2866remote sensingSentinel-2phycocyanincyanobacterial harmful bloomscyanotoxins |
| spellingShingle | Rebeca Pérez-González Xavier Sòria-Perpinyà Juan Miguel Soria Jesús Delegido Patricia Urrego María D. Sendra Antonio Ruíz-Verdú Eduardo Vicente José Moreno Phycocyanin Monitoring in Some Spanish Water Bodies with Sentinel-2 Imagery Water remote sensing Sentinel-2 phycocyanin cyanobacterial harmful blooms cyanotoxins |
| title | Phycocyanin Monitoring in Some Spanish Water Bodies with Sentinel-2 Imagery |
| title_full | Phycocyanin Monitoring in Some Spanish Water Bodies with Sentinel-2 Imagery |
| title_fullStr | Phycocyanin Monitoring in Some Spanish Water Bodies with Sentinel-2 Imagery |
| title_full_unstemmed | Phycocyanin Monitoring in Some Spanish Water Bodies with Sentinel-2 Imagery |
| title_short | Phycocyanin Monitoring in Some Spanish Water Bodies with Sentinel-2 Imagery |
| title_sort | phycocyanin monitoring in some spanish water bodies with sentinel 2 imagery |
| topic | remote sensing Sentinel-2 phycocyanin cyanobacterial harmful blooms cyanotoxins |
| url | https://www.mdpi.com/2073-4441/13/20/2866 |
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