FN Archimer Export Format
PT J
TI A Statistical Algorithm for Estimating Chlorophyll Concentration in the New Caledonian Lagoon
BT 
AF WATTELEZ, Guillaume
   DUPOUY, Cecile
   MANGEAS, Morgan
   LEFEVRE, Jerome
   FROUIN, Robert
AS 1:1,2,3;2:2,3;3:3,4;4:3,5;5:1;6:6;
FF 1:;2:;3:;4:;5:;6:;
C1 Univ New Caledonia, Sci & Technol Dept, Nouville Campus BP R4, Noumea 98851, New Caledonia
   Univ Toulon & Var, Aix Marseille Univ, CNRS, Mediterranean Inst Oceanog,INSU,UM 110, F-13288 Marseille, France
   Inst Rech Dev, BP A5 98848, Noumea 98848, New Caledonia
   Univ French Guiana, Univ Reunion, Univ Montpellier 2, Univ French West Indies,IRD,ESPACE DEV UMR 228, F-34093 Montpellier, France
   Univ Toulouse CNES, CNRS, LEGOS, IRD,UPS, F-31401 Toulouse, France
   Univ Calif San Diego, Scripps Inst Oceanog, La Jolla, CA 92037, USA
C2 UNIV NOUVELLE CALEDONIE, FRANCE
   UNIV TOULON, FRANCE
   IRD, FRANCE
   UNIV FRENCH GUIANA, FRANCE
   UNIV TOULOUSE, FRANCE
   UNIV CALIF SAN DIEGO, USA
IN DOAJ
IF 3.244
TC 10
UR https://archimer.ifremer.fr/doc/00481/59309/62060.pdf
LA English
DT Article
CR BISSECOTE
   CALIOPE 02
   CAMECAL 1
   CAMECAL 2
   CAMECAL 5
   CAMECAL 9
   DIAPALIS
   ECHOLAG
   TOPAZE
   VALHYBIO
   ZONALIS
BO Alis
   Antea
DE ;chlorophyll-a concentration;MODerate resolution Imaging Spectroradiometer (MODIS);ocean color;remote sensing;statistical algorithm;oligotrophic waters;New Caledonia;coral lagoon
AB 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. 
PY 2016
PD JAN
SO Remote Sensing
SN 2072-4292
PU Mdpi Ag
VL 8
IS 1
UT 000369494500026
DI 10.3390/rs8010045
ID 59309
ER

EF