Discrimination of phytoplankton functional groups using an ocean reflectance inversion model.
Discrimination of phytoplankton functional groups using an ocean reflectance inversion model.
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DOI：
10.1364/ao.53.004833
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发表时间：
2014-08
期刊：
影响因子：
1.9
通讯作者：
P. J. Werdell;C. Roesler;J. Goes
中科院分区：
文献类型：
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作者：
P. J. Werdell;C. Roesler;J. Goes
海洋反射率反演模型（ORMs）提供了一种将卫星观测到的水体颜色反演为海洋固有光学特性（IOPs）的机制，该机制可用于研究浮游植物群落结构。大多数orm有效地将浮游植物群落的总信号与其他水柱成分分离开来；然而，很少有研究表明，在大范围的环境条件下，多种浮游植物群的个体贡献是有效的。我们评估了ORM在阿拉伯海北部典型条件下区分夜luca miliaris和硅藻的能力。我们：(1)合成了代表阿拉伯海生物光学条件的IOPs剖面；(2)利用Hydrolight从这些剖面生成遥感反射率；(3)将ORM应用于合成反射率，估算硅藻和褐藻的相对浓度。通过将反演模型的估计与综合垂直剖面的估计进行比较，我们确定了ORM在哪些条件下表现良好和较差。即使在完全控制的条件下，当进一步将得到的浮游植物总信号分解成子分量时，ORM检索的绝对精度也会下降。虽然绝对震级保持偏差，但ORM成功地检测到夜莺是否出现在模拟水柱中。这在定量上要求在解释检索的绝对数量时要谨慎，但在定性上表明ORM提供了一种识别物种存在或不存在的强大机制。
Ocean reflectance inversion models (ORMs) provide a mechanism for inverting the color of the water observed by a satellite into marine inherent optical properties (IOPs), which can then be used to study phytoplankton community structure. Most ORMs effectively separate the total signal of the collective phytoplankton community from other water column constituents; however, few have been shown to effectively identify individual contributions by multiple phytoplankton groups over a large range of environmental conditions. We evaluated the ability of an ORM to discriminate between Noctiluca miliaris and diatoms under conditions typical of the northern Arabian Sea. We: (1) synthesized profiles of IOPs that represent bio-optical conditions for the Arabian Sea; (2) generated remote-sensing reflectances from these profiles using Hydrolight; and (3) applied the ORM to the synthesized reflectances to estimate the relative concentrations of diatoms and N. miliaris. By comparing the estimates from the inversion model with those from synthesized vertical profiles, we identified those conditions under which the ORM performs both well and poorly. Even under perfectly controlled conditions, the absolute accuracy of ORM retrievals degraded when further deconstructing the derived total phytoplankton signal into subcomponents. Although the absolute magnitudes maintained biases, the ORM successfully detected whether or not Noctiluca miliaris appeared in the simulated water column. This quantitatively calls for caution when interpreting the absolute magnitudes of the retrievals, but qualitatively suggests that the ORM provides a robust mechanism for identifying the presence or absence of species.