@article{fdi:010087539,
  title = {{GLORIA}-{A} globally representative hyperspectral in situ dataset for optical sensing of water quality [{D}ata paper]},
  author = {{L}ehmann, {M}. {K}. and {G}urlin, {D}. and {P}ahlevan, {N}. and {A}likas, {K}. and {A}nstee, {J}. and {B}alasubramanian, {S}. {V}. and {B}arbosa, {C}. {C}. {F}. and {B}inding, {C}. and {B}racher, {A}. and {B}resciani, {M}. and {B}urtner, {A}. and {C}ao, {Z}. {G}. and {D}ekker, {A}. {G}. and {D}i {V}ittorio, {C}. and {D}rayson, {N}. and {E}rrera, {R}. {M}. and {F}ernandez, {V}. and {F}icek, {D}. and {F}ichot, {C}. {G}. and {G}ege, {P}. and {G}iardino, {C}. and {G}itelson, {A}. {A}. and {G}reb, {S}. {R}. and {H}enderson, {H}. and {H}iga, {H}. and {R}ahaghi, {A}. {I}. and {J}amet, {C}. and {J}iang, {D}. {L}. and {J}ordan, {T}. and {K}angro, {K}. and {K}ravitz, {J}. {A}. and {K}ristoffersen, {A}. {S}. and {K}udela, {R}. and {L}i, {L}. and {L}igi, {M}. and {L}oisel, {H}. and {L}ohrenz, {S}. and {M}a, {R}. {H}. and {M}aciel, {D}. {A}. and {M}althus, {T}. {J}. and {M}atsushita, {B}. and {M}atthews, {M}. and {M}inaudo, {C}. and {M}ishra, {D}. {R}. and {M}ishra, {S}. and {M}oore, {T}. and {M}oses, {W}. {J}. and {N}guyen, {H}. and {N}ovo, {E}mlm and {N}ovoa, {S}. and {O}dermatt, {D}. and {O}'{D}onnell, {D}. {M}. and {O}lmanson, {L}. {G}. and {O}ndrusek, {M}. and {O}ppelt, {N}. and {O}uillon, {S}ylvain and {P}ereira, {W}. and {P}lattner, {S}. and {V}erdu, {A}. {R}. and {S}alem, {S}. {I}. and {S}challes, {J}. {F}. and {S}imis, {S}. {G}. {H}. and {S}iswanto, {E}. and {S}mith, {B}. and {S}omlai-{S}chweiger, {I}. and {S}oppa, {M}. {A}. and {S}pyrakos, {E}. and {T}essin, {E}. and van der {W}oerd, {H}. {J}. and {V}ander {W}oude, {A}. and {V}andermeulen, {R}. {A}. and {V}antrepotte, {V}. and {W}ernand, {M}. {R}. and {W}erther, {M}. and {Y}oung, {K}. and {Y}ue, {L}. {W}.},
  editor = {},
  language = {{ENG}},
  abstract = {{T}he development of algorithms for remote sensing of water quality ({RSWQ}) requires a large amount of in situ data to account for the bio-geo-optical diversity of inland and coastal waters. {T}he {GLO}bal {R}eflectance community dataset for {I}maging and optical sensing of {A}quatic environments ({GLORIA}) includes 7,572 curated hyperspectral remote sensing reflectance measurements at 1 nm intervals within the 350 to 900 nm wavelength range. {I}n addition, at least one co-located water quality measurement of chlorophyll a, total suspended solids, absorption by dissolved substances, and {S}ecchi depth, is provided. {T}he data were contributed by researchers affiliated with 59 institutions worldwide and come from 450 different water bodies, making {GLORIA} the de-facto state of knowledge of in situ coastal and inland aquatic optical diversity. {E}ach measurement is documented with comprehensive methodological details, allowing users to evaluate fitness-for-purpose, and providing a reference for practitioners planning similar measurements. {W}e provide open and free access to this dataset with the goal of enabling scientific and technological advancement towards operational regional and global {RSWQ} monitoring.},
  keywords = {{MONDE}},
  booktitle = {},
  journal = {{S}cientific {D}ata - {N}ature},
  volume = {10},
  numero = {1},
  pages = {100 [14 p.]},
  year = {2023},
  DOI = {10.1038/s41597-023-01973-y},
  URL = {https://www.documentation.ird.fr/hor/fdi:010087539},
}