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生物光学参数变异性和反射率测量中的不确定性对浑浊富营养水体叶绿素-a浓度遥感估算的影响:建模结果

Effect of bio-optical parameter variability and uncertainties in reflectance measurements on the remote estimation of chlorophyll-a concentration in turbid productive waters: modeling results.

作者信息

Dall'Olmo Giorgio, Gitelson Anatoly A

机构信息

Center for Advanced Land Management Information Technologies, School of Natural Resources, University of Nebraska-Lincoln 68588-0517, USA.

出版信息

Appl Opt. 2006 May 20;45(15):3577-92. doi: 10.1364/ao.45.003577.

Abstract

Most algorithms for retrieving chlorophyll-a concentration (Chla) from reflectance spectra assume that bio-optical parameters such as the phytoplankton specific absorption coefficient (aPhi*) or the chlorophyll-a fluorescence quantum yield (eta) are constant. Yet there exist experimental data showing large ranges of variability for these quantities. The main objective of this study was to analyze the sensitivity of two Chla algorithms to variations in bio-optical parameters and to uncertainties in reflectance measurements. These algorithms are specifically designed for turbid productive waters and are based on red and near-infrared reflectances. By means of simulated data, it is shown that the spectral regions where the algorithms are maximally sensitive to Chla overlap those of maximal sensitivity to variations in the above bio-optical parameters. Thus, to increase the accuracy of Chla retrieval, we suggest using spectral regions where the algorithms are less sensitive to Chla, but also less sensitive to these interferences. aPhi* appeared to be one of the most important sources of error for retrieving Chla. However, when the phytoplankton backscattering coefficient (bb,Phi) dominates the total backscattering, as is likely during algal blooms, variations in the specific bb,Phi may introduce large systematic uncertainties in Chla estimation. Also, uncertainties in reflectance measurements, which are due to incomplete atmospheric correction or reflected skylight removal, seem to affect considerably the accuracy of Chla estimation. Instead, variations in other bio-optical parameters, such as eta or the specific backscattering coefficient of total suspended particles, appear to have minor importance. Suggestions regarding the optimal band locations to be used in the above algorithms are finally provided.

摘要

大多数从反射光谱中反演叶绿素a浓度(Chla)的算法都假定生物光学参数是恒定的,比如浮游植物比吸收系数(aPhi*)或叶绿素a荧光量子产率(eta)。然而,已有实验数据表明这些量存在很大的变化范围。本研究的主要目的是分析两种Chla算法对生物光学参数变化和反射率测量不确定性的敏感性。这些算法是专门为浑浊的富产水域设计的,基于红光和近红外反射率。通过模拟数据表明,算法对Chla最敏感的光谱区域与对上述生物光学参数变化最敏感的区域重叠。因此,为了提高Chla反演的准确性,我们建议使用算法对Chla不太敏感但对这些干扰也不太敏感的光谱区域。aPhi*似乎是反演Chla最重要的误差来源之一。然而,当浮游植物后向散射系数(bb,Phi)在总后向散射中占主导时,比如在藻华期间很可能如此,特定bb,Phi的变化可能会在Chla估计中引入很大的系统不确定性。此外,由于大气校正不完全或去除反射天光导致的反射率测量不确定性,似乎会对Chla估计的准确性产生相当大的影响。相反,其他生物光学参数的变化,如eta或总悬浮颗粒的比后向散射系数,似乎不太重要。最后给出了关于上述算法中最佳波段位置的建议。

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