Water quality and remote sensing reflectance data for global inland, coastal and ocean waters
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| Main Authors: | , , |
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| Format: | Dataset Open Access |
| Language: | en |
| Published: |
PANGAEA
2023
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| _version_ | 1867171886229618688 |
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| author | Maciel, Daniel A Pahlevan, Nima Barbosa, Cláudio C F |
| author_facet | Maciel, Daniel A Pahlevan, Nima Barbosa, Cláudio C F |
| collection | Datos científicos de ciencias marinas y ambientales |
| contents | This dataset represents the remote sensing and Secchi Disk depth data that were used to calibrate and validate a global Mixture Density Network algorithm. Remote sensing reflectance, water quality, and satellite data associated with this dataset were compiled from several providers and institutions in global waters between 1990 and 2022. Data were compiled to support water quality remote sensing applications and the development of a Secchi Disk Depth algorithm. Information about the methods used in each dataset and how they were collected is available in the referred publications. |
| format | Dataset Open Access |
| id | pangaea_https___doi_org_10_1594_PANGAEA_961720 |
| institution | PANGAEA |
| language | en |
| publishDate | 2023 |
| publisher | PANGAEA |
| record_format | pangaea |
| spellingShingle | Water quality and remote sensing reflectance data for global inland, coastal and ocean waters Maciel, Daniel A Pahlevan, Nima Barbosa, Cláudio C F Binary Object; Binary Object (File Size); Binary Object (Media Type); CDOM; Chlorophyll a; File content; GLORIA; reflectance; remote sensing reflectance; Secchi; Secchi disk depth; suspended sediments; water quality This dataset represents the remote sensing and Secchi Disk depth data that were used to calibrate and validate a global Mixture Density Network algorithm. Remote sensing reflectance, water quality, and satellite data associated with this dataset were compiled from several providers and institutions in global waters between 1990 and 2022. Data were compiled to support water quality remote sensing applications and the development of a Secchi Disk Depth algorithm. Information about the methods used in each dataset and how they were collected is available in the referred publications. |
| title | Water quality and remote sensing reflectance data for global inland, coastal and ocean waters |
| topic | Binary Object; Binary Object (File Size); Binary Object (Media Type); CDOM; Chlorophyll a; File content; GLORIA; reflectance; remote sensing reflectance; Secchi; Secchi disk depth; suspended sediments; water quality |
| url | https://doi.org/10.1594/PANGAEA.961720 |