@incollection{fdi:010063838,
  title = {{A} statistical algorithm for estimating chlorophyll concentration from {MODIS} data},
  author = {{W}attelez, {G}. and {D}upouy, {C}{\'e}cile and {M}angeas, {M}organ and {L}ef{\`e}vre, {J}{\'e}r{\^o}me and {T}ouraivane, {T}. and {F}rouin, {R}.},
  editor = {},
  language = {{ENG}},
  abstract = {{W}e propose a statistical algorithm to assess chlorophyll-a concentration ([chl-a]) using remote sensing reflectance ({R}rs) derived from {MOD}erate {R}esolution {I}maging {S}pectroradiometer ({MODIS}) data. {T}his algorithm is a combination of two models: one for low [chl-a] (oligotrophic waters) and one for high [chl-a]. {A} satellite pixel is classified as low or high [chla] according to the {R}rs ratio (488 and 555 nm channels). {I}f a pixel is considered as a low [chl-a] pixel, a log-linear model is applied; otherwise, a more sophisticated model ({S}upport {V}ector {M}achine) is applied. {T}he log-linear model was developed thanks to supervised learning on {R}rs and [chl-a] data from {S}ea{BASS} and more than 15 campaigns accomplished from 2002 to 2010 around {N}ew {C}aledonia. {S}everal models to assess high [chl-a] were also tested with statistical methods. {T}his novel approach outperforms the standard reflectance ratio approach. {C}ompared with algorithms such as the current {NASA} {OC}3, {R}oot {M}ean {S}quare {E}rror is 30% lower in {N}ew {C}aledonian waters.},
  keywords = {{TELEDETECTION} {SPATIALE} ; {DONNEES} {SATELLITE} ; {ALGORITHME} ; {REFLECTANCE} ; {CHLOROPHYLLE} ; {LAGON} ; {COULEUR} {DE} {L}'{OCEAN} ; {OLIGOTROPHIE} ; {MODIS} ; {NOUVELLE} {CALEDONIE} ; {ZONE} {TROPICALE}},
  booktitle = {{O}cean remote sensing and monitoring from space},
  volume = {9261},
  numero = {92611{S}},
  pages = {92611{S}/1--92611{S}/15},
  address = {{B}ellingham {WA}},
  publisher = {{SPIE}},
  series = {{P}roceedings of {SPIE}},
  year = {2014},
  DOI = {10.1117/12.2086297},
  ISSN = {0277-786{X}},
  URL = {https://www.documentation.ird.fr/hor/fdi:010063838},
}