Water quality and remote sensing reflectance data for global inland, coastal and ocean waters

doi:doi:10.1594/PANGAEA.961720

Water quality and remote sensing reflectance data for global inland, coastal and ocean waters

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.

BibTex:

@dataset{Maciel_Daniel_A_and_Pahlevan_Nima_and_Barbosa_Cláudio_C_F_2023,
    abstract = {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.},
    author = {Maciel, Daniel A and Pahlevan, Nima and Barbosa, Cláudio C F},
    doi = {10.1594/PANGAEA.961720},
    institution = {PANGAEA (Human Dimensions)},
    keyword = {'CDOM', 'Chlorophyll a', 'GLORIA', 'Secchi', 'Secchi disk depth', 'reflectance', 'remote sensing reflectance', 'suspended sediments', 'water quality'},
    title = {Water quality and remote sensing reflectance data for global inland, coastal and ocean waters},
    url = {https://service.tib.eu/ldmservice/vdataset/png-doi-10-1594-pangaea-961720},
    year = {2023}
}