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Effects of phytoplankton species composition on absorption spectra and modeled hyperspectral reflectance

机译:浮游植物种类组成对吸收光谱和模拟高光谱反射率的影响

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Understanding the spectral characteristics of remotely-sensed reflectance by different phytoplankton species can assist in the development of algorithms to identify various algal groups using satellite ocean color remote sensing. One of the main challenges is to separate the effect of species composition on the reflectance spectrum from other factors such as pigment concentration and particle size structure. Measuring the absorption spectra of nine different cultured algae, and estimating the reflectance of the different species, provides a useful approach to study the effects of species composition on the bio-optical properties. The results show that the absorption spectra of different species exhibit different spectral characteristics and that species composition can significantly change the absorption characteristics at four main peaks (438, 536, 600 and 650 nm). A 'distance angle index' was used to compare different phytoplankton species. Results indicate that this index can be used to identify species from the absorption spectra, using a database of standard absorption spectra of known species as reference. By taking into account the role of species composition in the phytoplankton absorption model, the performance of the model can be improved by up to 5%. A reflectance-species model is developed to estimate the remotely-sensed reflectance from the absorption spectra, and the reflectance of different phytoplankton species at the same chlorophyll- a concentration is compared, to understand effects of species composition on the reflectance spectra. Different phytoplankton species can cause up to 33% difference in the modeled reflectance at short wavelengths under the condition of the same chlorophyll- a concentration, and variations in the reflectance spectrum correspond to the colors of the algae. The standard deviation of the reflectance among different species shows that the variations from 400 to 450. nm are sensitive to species composition at low chlorophyll- a concentrations, whereas variations in the 510 to 550. nm range are more sensitive under high chlorophyll- a concentrations. For this reason, the green bands may be more suitable for estimating species composition from hyperspectral satellite data during bloom conditions, whereas the blue bands may be more helpful in detection of species under low chlorophyll- a concentrations. In this theoretical approach, variations in reflectance at the same chlorophyll- a concentration can be used to identify phytoplankton species. Another approach to identify phytoplankton species from remotely-sensed hyperspectral reflectance measurements would be to derive the absorption spectra of phytoplankton from the reflectance measurements, and compare these with a standard database of absorption spectra.
机译:了解不同浮游植物物种的遥感反射光谱特性可以帮助开发使用卫星海洋颜色遥感识别各种藻类的算法。主要挑战之一是将物种组成对反射光谱的影响与其他因素(例如颜料浓度和粒度结构)分开。测量九种不同养殖藻类的吸收光谱,并估计不同物种的反射率,为研究物种组成对生物光学特性的影响提供了一种有用的方法。结果表明,不同物种的吸收光谱表现出不同的光谱特性,并且物种组成可以显着改变四个主要峰(438、536、600和650 nm)处的吸收特性。 “距离角指数”用于比较不同的浮游植物种类。结果表明,该指数可以使用已知物种的标准吸收光谱数据库作为参考,从吸收光谱中识别物种。通过考虑物种组成在浮游植物吸收模型中的作用,该模型的性能最多可提高5%。建立了一个反射物种模型以从吸收光谱中估算遥感反射率,并比较了同一叶绿素中不同浮游植物物种的反射率(浓度),以了解物种组成对反射光谱的影响。在相同叶绿素a浓度的条件下,不同的浮游植物种类可在短波长下引起模拟反射率差异高达33%,并且反射率光谱的变化对应于藻类的颜色。不同物种之间反射率的标准偏差表明,在低叶绿素a浓度下,从400到450. nm的变化对物种组成敏感,而在高叶绿素a浓度下,在510到550. nm范围内的变化更敏感。 。因此,绿色条带可能更适合在开花条件下根据高光谱卫星数据估算物种组成,而蓝色条带可能更有助于检测低叶绿素a浓度的物种。在这种理论方法中,相同叶绿素-a浓度下反射率的变化可用于识别浮游植物。从遥感高光谱反射率测量值中识别浮游植物种类的另一种方法是从反射率测量值中得出浮游植物的吸收光谱,并将其与吸收光谱的标准数据库进行比较。

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