Lu Ting, Lu Yingcheng, Hu Lianbo, Jiao Junnan, Zhang Minwei, Liu Yongxue
Opt Express. 2019 Jun 24;27(13):18620-18627. doi: 10.1364/OE.27.018620.
A laboratory experiment was conducted to obtain a floating algae index (FAI) of the floating macroalgae (Ulva prolifera), corresponding to various values of biomass per unit area (BPA). A piecewise empirical model was used to fit the statistical relationships between BPA and FAI, corresponding to FAI ≤ 0.2 (BPA ≤ 1.81kg/m) and FAI ˃ 0.2 (BPA ˃ 1.81 kg/m). Spectral mixing derived results show that a linear relationship between FAI and BPA is maintained when the BPA of endmembers is less than 1.81 kg/m. However, when the BPA of the endmembers exceeds 1.81 kg/m, there is substantial uncertainty in the optical remote estimation of biomass. Although the MODIS-derived FAI of Ulva prolifera is often less than 0.2, it is very difficult to determine whether the FAI results from low BPA (≤ 1.81kg/m) of the endmembers, or from a low area ratio including high BPA (˃ 1.81 kg/m), due to pixel mixing. If it is assumed that the unit biomass distribution of pure endmembers is a standard Gaussian distribution, then the uncertainty in the biomass estimation of Ulva prolifera from MODIS data can be expressed. This results in the uncertainty of ~36% in total biomass estimation, ~43% of which was contributed by a few pixels (10% of total pixels) with high FAI (˃ 0.05). The uncertainty in BPA caused by high FAI (˃ 0.05) pixels is about 7.2 times that for low FAI (≤ 0.05) pixels. In future research, the spatial distribution characteristics of the FAI of pure endmembers need to be considered in order to improve the accuracy of optical remote estimation of floating Ulva prolifera.
进行了一项实验室实验，以获取对应于单位面积生物量（BPA）各种值的漂浮大型海藻（浒苔）的漂浮藻类指数（FAI）。采用分段经验模型来拟合BPA与FAI之间的统计关系，分别对应FAI≤0.2（BPA≤1.81kg/m）和FAI˃0.2（BPA˃1.81kg/m）的情况。光谱混合推导结果表明，当端元的BPA小于1.81kg/m时，FAI与BPA之间保持线性关系。然而，当端元的BPA超过1.81kg/m时，生物量的光学遥感估算存在很大不确定性。尽管通过MODIS得出的浒苔FAI通常小于0.2，但由于像元混合，很难确定FAI是源于端元的低BPA（≤1.81kg/m），还是源于包含高BPA（˃1.81kg/m）的低面积比例。如果假设纯端元的单位生物量分布为标准高斯分布，那么就可以表达出利用MODIS数据估算浒苔生物量的不确定性。这导致总生物量估算的不确定性约为36%，其中约43%是由少数高FAI（˃0.05）的像元（占总像元的10%）造成的。高FAI（˃0.05）像元导致的BPA不确定性约为低FAI（≤0.05）像元的7.2倍。在未来的研究中，需要考虑纯端元FAI的空间分布特征，以提高漂浮浒苔光学遥感估算的准确性。
