基于水体反射光谱和组分浓度的固有光学特性反演算法

吸收系数和后向散射系数是水体的固有光学特性参数,在探测水体中各组分浓度的过程中起着至关重要的作用.但通常组分固有光学特性的测定是一个操作复杂且费时费力的过程.提出了一种利用已知组分浓度和相应的反射光谱的水体样本来推定水体中各组分的吸收和后向散射系数的算法,并利用生物光学模型产生的模拟光谱数据对算法的合理性进行了验证.结果表明,在理想的实验条件下(反射光谱满足机理模型,且选取的训练样本相互独立),可以高精度地反演出各组分的固有光学特性,从而证实了本算法在理论卜的合理性.

Deriving inherent optical properties through training samples with known concentration of water constituents and reflectance spectra

Coefficients of absorption and backscattering are inherent optical properties (IOPs) of water, which play extraordinarily important roles in the detection of water constituent concentrations. However, it is very complicate and time-consuming to measure the IOPs of waters. In this study, a novel algorithm was proposed to derive the IOPs of water constituents through training samples with measured constituents' concentrations and reflectance spectra. Simulated data based on bio-optical model was used to assess the proposed algorithm. Results demonstrated that when the spectra of samples satisfied the analytical model and the training samples were independent each other, the performance of the algorithm can be accepted, which indicates that the algorithm proposed in this paper is theoretically reasonable.