Organelli Emanuele, Bricaud Annick, Antoine David, Uitz Julia
Laboratoire d’Océanographie de Villefranche, UMR 7093, CNRS and Université Pierre et Marie Curie, Paris 6, France.
Appl Opt. 2013 Apr 10;52(11):2257-73. doi: 10.1364/AO.52.002257.
Models based on the multivariate partial least squares (PLS) regression technique are developed for the retrieval of phytoplankton size structure from measured light absorption spectra (BOUSSOLE site, northwestern Mediterranean Sea). PLS-models trained with data from the Mediterranean Sea showed good accuracy in retrieving, over the nine-year BOUSSOLE time series, the concentrations of total chlorophyll a [Tchl a], of the sum of seven diagnostic pigments and of pigments associated with micro, nano, and picophytoplankton size classes separately. PLS-models trained using either total particle or phytoplankton absorption spectra performed similarly, and both reproduced seasonal variations of biomass and size classes derived by high performance liquid chromatography. Satisfactory retrievals were also obtained using PLS-models trained with a data set including various locations of the world's oceans, with however a lower accuracy. These results open the way to an application of this method to absorption spectra derived from hyperspectral and field satellite radiance measurements.
基于多元偏最小二乘（PLS）回归技术建立了模型，用于从实测光吸收光谱中反演浮游植物的大小结构（地中海西北部BOUSSOLE站点）。用来自地中海的数据训练的PLS模型，在九年的BOUSSOLE时间序列中，分别反演总叶绿素a [Tchl a]、七种诊断色素总和以及与微型、纳米级和微微型浮游植物大小类相关的色素浓度时，显示出良好的准确性。使用总颗粒吸收光谱或浮游植物吸收光谱训练的PLS模型表现相似，且二者都再现了通过高效液相色谱法得出的生物量和大小类别的季节变化。使用包含世界海洋不同地点数据集训练的PLS模型也获得了令人满意的反演结果，不过准确性较低。这些结果为将该方法应用于从高光谱和实地卫星辐射测量得出的吸收光谱开辟了道路。
