Improving Colored Dissolved Organic Matter (CDOM) Retrievals by Sentinel2-MSI Data through a Total Suspended Matter (TSM)-Driven Classification: The Case of Pertusillo Lake (Southern Italy)
Colored dissolved organic matter (CDOM) is a significant constituent of aquatic systems and biogeochemical cycles. Satellite CDOM retrievals are challenging in inland waters, due to overlapped absorption properties of bio-optical parameters, like Total Suspended Matter (TSM). In this framework, we d...
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MDPI AG
2023-12-01
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| Loạt: | Remote Sensing |
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| Truy cập trực tuyến: | https://www.mdpi.com/2072-4292/15/24/5718 |
| _version_ | 1827573628681584640 |
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| author | Emanuele Ciancia Alessandra Campanelli Roberto Colonna Angelo Palombo Simone Pascucci Stefano Pignatti Nicola Pergola |
| author_facet | Emanuele Ciancia Alessandra Campanelli Roberto Colonna Angelo Palombo Simone Pascucci Stefano Pignatti Nicola Pergola |
| author_sort | Emanuele Ciancia |
| collection | DOAJ |
| description | Colored dissolved organic matter (CDOM) is a significant constituent of aquatic systems and biogeochemical cycles. Satellite CDOM retrievals are challenging in inland waters, due to overlapped absorption properties of bio-optical parameters, like Total Suspended Matter (TSM). In this framework, we defined an accurate CDOM model using Sentinel2-MSI (S2-MSI) data in Pertusillo Lake (Southern Italy) adopting a classification scheme based on satellite TSM data. Empirical relationships were established between the CDOM absorption coefficient, a<sub>CDOM</sub> (440), and reflectance band ratios using ground-based measurements. The Green-to-Red (B3/B4 and B3/B5) and Red-to-Blue (B4/B2 and B5/B2) band ratios showed good relationships (R<sup>2</sup> ≥ 0.75), which were further improved according to sub-region division (R<sup>2</sup> up to 0.93). The best accuracy of B3/B4 in the match-ups between S2-MSI-derived and in situ band ratios proved the exportability on S2-MSI data of two B3/B4-based a<sub>CDOM</sub> (440) models, namely the fixed (for the whole PL) and the switching one (according to sub-region division). Although they both exhibited good agreements in a<sub>CDOM</sub> (440) retrievals (R<sup>2</sup> ≥ 0.69), the switching model showed the highest accuracy (RMSE of 0.0155 m<sup>−1</sup>). Finally, the identification of areas exposed to different TSM patterns can assist with refining the calibration/validation procedures to achieve more accurate a<sub>CDOM</sub> (440) retrievals. |
| first_indexed | 2024-03-08T20:24:00Z |
| format | Article |
| id | doaj.art-55b3645c62f04cfaac16715df40f5276 |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-08T20:24:00Z |
| publishDate | 2023-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-55b3645c62f04cfaac16715df40f52762023-12-22T14:39:08ZengMDPI AGRemote Sensing2072-42922023-12-011524571810.3390/rs15245718Improving Colored Dissolved Organic Matter (CDOM) Retrievals by Sentinel2-MSI Data through a Total Suspended Matter (TSM)-Driven Classification: The Case of Pertusillo Lake (Southern Italy)Emanuele Ciancia0Alessandra Campanelli1Roberto Colonna2Angelo Palombo3Simone Pascucci4Stefano Pignatti5Nicola Pergola6Institute of Methodologies for Environmental Analysis-National Research Council (CNR-IMAA), C.da Santa Loja, Tito Scalo, 85050 Potenza, ItalyInstitute for Biological Resources and Marine Biotechnologies-National Research Council (CNR-IRBIM), L.go Fiera della Pesca, 2, 60125 Ancona, ItalySpace Technologies and Applications Centre (STAC), 85100 Potenza, ItalyInstitute of Methodologies for Environmental Analysis-National Research Council (CNR-IMAA), C.da Santa Loja, Tito Scalo, 85050 Potenza, ItalyInstitute of Methodologies for Environmental Analysis-National Research Council (CNR-IMAA), C.da Santa Loja, Tito Scalo, 85050 Potenza, ItalyInstitute of Methodologies for Environmental Analysis-National Research Council (CNR-IMAA), C.da Santa Loja, Tito Scalo, 85050 Potenza, ItalyInstitute of Methodologies for Environmental Analysis-National Research Council (CNR-IMAA), C.da Santa Loja, Tito Scalo, 85050 Potenza, ItalyColored dissolved organic matter (CDOM) is a significant constituent of aquatic systems and biogeochemical cycles. Satellite CDOM retrievals are challenging in inland waters, due to overlapped absorption properties of bio-optical parameters, like Total Suspended Matter (TSM). In this framework, we defined an accurate CDOM model using Sentinel2-MSI (S2-MSI) data in Pertusillo Lake (Southern Italy) adopting a classification scheme based on satellite TSM data. Empirical relationships were established between the CDOM absorption coefficient, a<sub>CDOM</sub> (440), and reflectance band ratios using ground-based measurements. The Green-to-Red (B3/B4 and B3/B5) and Red-to-Blue (B4/B2 and B5/B2) band ratios showed good relationships (R<sup>2</sup> ≥ 0.75), which were further improved according to sub-region division (R<sup>2</sup> up to 0.93). The best accuracy of B3/B4 in the match-ups between S2-MSI-derived and in situ band ratios proved the exportability on S2-MSI data of two B3/B4-based a<sub>CDOM</sub> (440) models, namely the fixed (for the whole PL) and the switching one (according to sub-region division). Although they both exhibited good agreements in a<sub>CDOM</sub> (440) retrievals (R<sup>2</sup> ≥ 0.69), the switching model showed the highest accuracy (RMSE of 0.0155 m<sup>−1</sup>). Finally, the identification of areas exposed to different TSM patterns can assist with refining the calibration/validation procedures to achieve more accurate a<sub>CDOM</sub> (440) retrievals.https://www.mdpi.com/2072-4292/15/24/5718retrieval modelsS2-MSI datainland water reflectanceCDOMunsupervised classification |
| spellingShingle | Emanuele Ciancia Alessandra Campanelli Roberto Colonna Angelo Palombo Simone Pascucci Stefano Pignatti Nicola Pergola Improving Colored Dissolved Organic Matter (CDOM) Retrievals by Sentinel2-MSI Data through a Total Suspended Matter (TSM)-Driven Classification: The Case of Pertusillo Lake (Southern Italy) Remote Sensing retrieval models S2-MSI data inland water reflectance CDOM unsupervised classification |
| title | Improving Colored Dissolved Organic Matter (CDOM) Retrievals by Sentinel2-MSI Data through a Total Suspended Matter (TSM)-Driven Classification: The Case of Pertusillo Lake (Southern Italy) |
| title_full | Improving Colored Dissolved Organic Matter (CDOM) Retrievals by Sentinel2-MSI Data through a Total Suspended Matter (TSM)-Driven Classification: The Case of Pertusillo Lake (Southern Italy) |
| title_fullStr | Improving Colored Dissolved Organic Matter (CDOM) Retrievals by Sentinel2-MSI Data through a Total Suspended Matter (TSM)-Driven Classification: The Case of Pertusillo Lake (Southern Italy) |
| title_full_unstemmed | Improving Colored Dissolved Organic Matter (CDOM) Retrievals by Sentinel2-MSI Data through a Total Suspended Matter (TSM)-Driven Classification: The Case of Pertusillo Lake (Southern Italy) |
| title_short | Improving Colored Dissolved Organic Matter (CDOM) Retrievals by Sentinel2-MSI Data through a Total Suspended Matter (TSM)-Driven Classification: The Case of Pertusillo Lake (Southern Italy) |
| title_sort | improving colored dissolved organic matter cdom retrievals by sentinel2 msi data through a total suspended matter tsm driven classification the case of pertusillo lake southern italy |
| topic | retrieval models S2-MSI data inland water reflectance CDOM unsupervised classification |
| url | https://www.mdpi.com/2072-4292/15/24/5718 |
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