%0 Journal Article
%T A statistical algorithm for estimating chlorophyll concentration in the New Caledonian lagoon
%+ Université de la Nouvelle-Calédonie (UNC)
%+ Institut méditerranéen d'océanologie (MIO)
%+ UMR 228 Espace-Dev, Espace pour le développement
%+ Laboratoire d'études en Géophysique et océanographie spatiales (LEGOS)
%+ University of California [San Diego] (UC San Diego)
%A Wattelez, Guillaume
%A Dupouy, Cecile
%A Mangeas, Morgan
%A Lefèvre, Jérôme
%A Touraivane, T.
%A Frouin, Robert
%Z INSU-VALHYBIO
%Z IRD-VALHYSAT
%Z INSU-ECCO/TREMOLO
%Z GOPS-DROPS
%Z CNRT Nickel et son Environnement - DYNAMINE
%< avec comité de lecture
%@ 2072-4292
%J Remote Sensing
%I MDPI
%V 8
%N 1
%P 45-68
%8 2016-01-07
%D 2016
%R 10.3390/rs8010045
%K chlorophyll-a concentration
%K MODerate resolution Imaging Spectroradiometer (MODIS)
%K ocean color
%K remote sensing
%K statistical algorithm
%K oligotrophic waters
%K New Caledonia
%K coral lagoon
%K Nouvelle-Calédonie
%K télédétection
%K chlorophylle a
%K lagon
%K oligotrophie
%K couleur de l'océan
%K algorithme statistique
%Z Sciences of the Universe [physics]/Ocean, AtmosphereJournal articles
%X 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.
%G English
%2 https://ird.hal.science/ird-01253540/document
%2 https://ird.hal.science/ird-01253540/file/remotesensing-08-00045.pdf
%L ird-01253540
%U https://ird.hal.science/ird-01253540
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