Wattelez G. auteur aut IRD Dupouy Cécile auteur aut IRD Mangeas Morgan auteur aut IRD Lefevre Jérôme auteur aut IRD Touraivane auteur aut IRD Frouin R. auteur aut IRD text journalArticle eng text/pdf reformatted digital access Spatial and temporal dynamics of phytoplankton biomass and water turbidity can provide crucial information about the function, health and vulnerability of lagoon ecosystems (coral reefs, sea grasses, etc.). A statistical algorithm is proposed to estimate chlorophyll-a concentration ([chl-a]) in optically complex waters of the New Caledonian lagoon from MODIS-derived remote-sensing reflectance (R-rs). The algorithm is developed via supervised learning on match-ups gathered from 2002 to 2010. The best performance is obtained by combining two models, selected according to the ratio of R-rs in spectral bands centered on 488 and 555 nm: a log-linear model for low [chl-a] (AFLC) and a support vector machine (SVM) model or a classic model (OC3) for high [chl-a]. The log-linear model is developed based on SVM regression analysis. This approach outperforms the classical OC3 approach, especially in shallow waters, with a root mean squared error 30% lower. The proposed algorithm enables more accurate assessments of [chl-a] and its variability in this typical oligo- to meso-trophic tropical lagoon, from shallow coastal waters and nearby reefs to deeper waters and in the open ocean. specialized chlorophyll-a concentration MODerate resolution Imaging Spectroradiometer (MODIS) ocean color remote sensing statistical algorithm oligotrophic waters New Caledonia coral lagoon NOUVELLE CALEDONIE PACIFIQUE 126 036 020 8 1 art. 45 [23 p.] 2016 2072-4292 https://www.documentation.ird.fr/hor/fdi:010066220 10.3390/rs8010045 2072-4292 [F B010066220] https://www.documentation.ird.fr/hor/fdi:010066220 https://horizon.documentation.ird.fr/exl-doc/pleins_textes/divers16-03/010066220.pdf IRD - Base Horizon / Pleins textes 2016-04-01 2017-08-23 fdi:010066220 fre