A Statistical Algorithm for Estimating Chlorophyll Concentration in the New Caledonian Lagoon
Type | Article | ||||||||
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Date | 2016-01 | ||||||||
Language | English | ||||||||
Author(s) | Wattelez Guillaume1, 2, 3, Dupouy Cecile2, 3, Mangeas Morgan3, 4, Lefevre Jerome3, 5, Touraivane 1, Frouin Robert6 | ||||||||
Affiliation(s) | 1 : Univ New Caledonia, Sci & Technol Dept, Nouville Campus BP R4, Noumea 98851, New Caledonia 2 : Univ Toulon & Var, Aix Marseille Univ, CNRS, Mediterranean Inst Oceanog,INSU,UM 110, F-13288 Marseille, France 3 : Inst Rech Dev, BP A5 98848, Noumea 98848, New Caledonia 4 : Univ French Guiana, Univ Reunion, Univ Montpellier 2, Univ French West Indies,IRD,ESPACE DEV UMR 228, F-34093 Montpellier, France 5 : Univ Toulouse CNES, CNRS, LEGOS, IRD,UPS, F-31401 Toulouse, France 6 : Univ Calif San Diego, Scripps Inst Oceanog, La Jolla, CA 92037, USA |
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Source | Remote Sensing (2072-4292) (Mdpi Ag), 2016-01 , Vol. 8 , N. 1 , P. 45 (23p.) | ||||||||
DOI | 10.3390/rs8010045 | ||||||||
WOS© Times Cited | 10 | ||||||||
Note | This article belongs to the Special Issue Remote Sensing for Coral Reef Monitoring | ||||||||
Keyword(s) | chlorophyll-a concentration, MODerate resolution Imaging Spectroradiometer (MODIS), ocean color, remote sensing, statistical algorithm, oligotrophic waters, New Caledonia, coral lagoon | ||||||||
Abstract | 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. |
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