A Novel Methodology to Correct Chlorophyll-a Concentrations from Satellite Data and Assess Credible Phenological Patterns
Remote sensing data play a crucial role in capturing and evaluating eutrophication, providing a comprehensive view of spatial and temporal variations in water quality parameters. Chlorophyll-a concentration time series analysis aids in understanding the current trophic state of coastal waters and tr...
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| Language: | English |
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MDPI AG
2025-03-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/17/7/1156 |
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| author | Irene Biliani Ekaterini Skamnia Polychronis Economou Ierotheos Zacharias |
| author_facet | Irene Biliani Ekaterini Skamnia Polychronis Economou Ierotheos Zacharias |
| author_sort | Irene Biliani |
| collection | DOAJ |
| description | Remote sensing data play a crucial role in capturing and evaluating eutrophication, providing a comprehensive view of spatial and temporal variations in water quality parameters. Chlorophyll-a concentration time series analysis aids in understanding the current trophic state of coastal waters and tracking changes over time, enabling the evaluation of water bodies’ trophic status. This research presents a novel and replicable methodology able to derive accurate phenological patterns using remote sensing data. The methodology proposed uses the two-decade MODIS-Aqua surface reflectance dataset, analyzing data from 30-point stations and calculating chlorophyll-a concentrations from NASA’s Ocean Color algorithm. Then, a correction process is implemented through a robust, simple statistical analysis by applying LOESS smoothing to detect and remove outliers from the extensive dataset. Different scenarios are reviewed and compared with field data to calibrate the proposed methodology accurately. The results demonstrate the methodology’s capacity to produce consistent chlorophyll-a time series and to present phenological patterns that can effectively identify key indicators and trends, resulting in valuable insights into the coastal body’s trophic state. The case study of the Ambracian Gulf is characterized as hypertrophic since algal bloom during August reaches up to 5 mg/m<sup>3</sup>, while the replicate case study of Aitoliko shows algal bloom reaching up to 2.5 mg/m<sup>3</sup>. Finally, the proposed methodology successfully identifies the positive chlorophyll-a climate tendencies of the two selected Greek water bodies. This study highlights the value of integrating statistical methods with remote sensing data for accurate, long-term monitoring of water quality in aquatic ecosystems. |
| format | Article |
| id | doaj-art-ffc1ce54193641c68c9b1b2ef0da9299 |
| institution | DOAJ |
| issn | 2072-4292 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj-art-ffc1ce54193641c68c9b1b2ef0da92992025-08-20T03:08:56ZengMDPI AGRemote Sensing2072-42922025-03-01177115610.3390/rs17071156A Novel Methodology to Correct Chlorophyll-a Concentrations from Satellite Data and Assess Credible Phenological PatternsIrene Biliani0Ekaterini Skamnia1Polychronis Economou2Ierotheos Zacharias3Laboratory of Environmental Engineering, Department of Civil Engineering, University of Patras, 26504 Patras, GreeceLaboratory of Environmental Engineering, Department of Civil Engineering, University of Patras, 26504 Patras, GreeceLaboratory of Environmental Engineering, Department of Civil Engineering, University of Patras, 26504 Patras, GreeceLaboratory of Environmental Engineering, Department of Civil Engineering, University of Patras, 26504 Patras, GreeceRemote sensing data play a crucial role in capturing and evaluating eutrophication, providing a comprehensive view of spatial and temporal variations in water quality parameters. Chlorophyll-a concentration time series analysis aids in understanding the current trophic state of coastal waters and tracking changes over time, enabling the evaluation of water bodies’ trophic status. This research presents a novel and replicable methodology able to derive accurate phenological patterns using remote sensing data. The methodology proposed uses the two-decade MODIS-Aqua surface reflectance dataset, analyzing data from 30-point stations and calculating chlorophyll-a concentrations from NASA’s Ocean Color algorithm. Then, a correction process is implemented through a robust, simple statistical analysis by applying LOESS smoothing to detect and remove outliers from the extensive dataset. Different scenarios are reviewed and compared with field data to calibrate the proposed methodology accurately. The results demonstrate the methodology’s capacity to produce consistent chlorophyll-a time series and to present phenological patterns that can effectively identify key indicators and trends, resulting in valuable insights into the coastal body’s trophic state. The case study of the Ambracian Gulf is characterized as hypertrophic since algal bloom during August reaches up to 5 mg/m<sup>3</sup>, while the replicate case study of Aitoliko shows algal bloom reaching up to 2.5 mg/m<sup>3</sup>. Finally, the proposed methodology successfully identifies the positive chlorophyll-a climate tendencies of the two selected Greek water bodies. This study highlights the value of integrating statistical methods with remote sensing data for accurate, long-term monitoring of water quality in aquatic ecosystems.https://www.mdpi.com/2072-4292/17/7/1156chlorophyll-aremote sensing NASA Ocean Color algorithmcorrectionLOESS |
| spellingShingle | Irene Biliani Ekaterini Skamnia Polychronis Economou Ierotheos Zacharias A Novel Methodology to Correct Chlorophyll-a Concentrations from Satellite Data and Assess Credible Phenological Patterns Remote Sensing chlorophyll-a remote sensing NASA Ocean Color algorithm correction LOESS |
| title | A Novel Methodology to Correct Chlorophyll-a Concentrations from Satellite Data and Assess Credible Phenological Patterns |
| title_full | A Novel Methodology to Correct Chlorophyll-a Concentrations from Satellite Data and Assess Credible Phenological Patterns |
| title_fullStr | A Novel Methodology to Correct Chlorophyll-a Concentrations from Satellite Data and Assess Credible Phenological Patterns |
| title_full_unstemmed | A Novel Methodology to Correct Chlorophyll-a Concentrations from Satellite Data and Assess Credible Phenological Patterns |
| title_short | A Novel Methodology to Correct Chlorophyll-a Concentrations from Satellite Data and Assess Credible Phenological Patterns |
| title_sort | novel methodology to correct chlorophyll a concentrations from satellite data and assess credible phenological patterns |
| topic | chlorophyll-a remote sensing NASA Ocean Color algorithm correction LOESS |
| url | https://www.mdpi.com/2072-4292/17/7/1156 |
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