基于浮游植物粒径分级的海洋初级生产力遥感定量反演方法研究

海洋初级生产力的准确估算是全球气候变化及全球碳循环研究的重要基础。基于卫星遥感数据的浮游植物光吸收海洋初级生产力模型（ABPM），为全球海域初级生产力时空分布监测提供了重要手段。但浮游植物光合量子产率的不确定性和浮游植物吸收系数垂直剖面分布的不均一性影响了模型反演精度。目前尚无成熟的方法对其进行准确计算。.本项目将分析ABPM模型中存在的上述问题,进而开展相关研究工作。针对影响浮游植物光合量子产率不确定性的关键要素，提出基于浮游植物粒径分级的光合量子产率遥感定量反演模型；针对浮游植物吸收系数剖面的不均一性，提出基于特征波段的浮游植物平均光谱吸收系数垂直分布定量反演模型。进而利用两种模型改进ABPM模型。通过项目的实施，能够解决ABPM模型在部分海域误差较大的问题，为海洋生态科学遥感研究和应用提供科学方法和理论依据。

Accurate estimation of marine primary productivity is very important for the research of global climate change and global carbon cycle. Satellite remote sensing data based Phytoplankton absorption-based primary productivity model (ABPM) is an effective method to monitor spatial and temporal distribution of marine primary productivity. However, the accuracy of this model is mainly influenced by the uncertainty of phytoplankton photosynthetic quantum yield and the vertical heterogeneity of phytoplankton absorption coefficient. Still now there are not any mature approaches can calculate it precisely...This project will analyzes these issues of existing ABPM model and carry out related research. Through the summary of key factors which affect the uncertainty of photosynthetic quantum, a quantitative phytoplankton photosynthetic quantum yield estimation model based on phytoplankton size types using remote sensing data is proposed. For the vertical heterogeneity of phytoplankton absorption coefficient, the vertical distribution of average spectral phytoplankton absorption coefficient model based on characteristic bands is proposed. Both of the models are aiming at improving the accuracy of ABPM. The implementation of this project can reduce the error of ABPM model in some part of the marine, so as to provide a scientific method and theoretical foundation in the field of marine ecology research using remote sensing data.