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Sensitivity analysis of the row model#039;s input parameters

机译:行模型输入参数的灵敏度分析

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In this study, we use the variance based sensitivity method to analyze the sensitivities of the row crop model's input parameters. This method consists of three steps: sample generation, model execution and the calculation of sensitivity indices. The results of sensitivity analysis of row crop model's input parameters indicate that the sensitivities of the row model's parameters are different under different viewing angles. We also find that the row structure of canopy can affect the sensitivities of model's inputs parameters. LAI is found to be generally the most sensitive parameter in three typical spectral bands. a and h are also identified as sensitive parameters in the along-row or near-along row directions in the VNIR bands. LIDF.a is relatively sensitive at some viewing angles and LIDF.b is insensitive in three typical spectral bands. k has marginal influence on the model outputs in all of the viewing angles and spectral bands, except around hotspot directions in the red band. The main contribution of this work is that the technique of global sensitivity analysis is applied to the row model and the results are informative for the retrieval of the parameters during the inversion.
机译:在这项研究中,我们使用基于方差的敏感性方法来分析行作物模型的输入参数的敏感性。该方法包括三个步骤:样品生成,模型执行和灵敏度指标的计算。行作物模型输入参数的敏感性分析结果表明,在不同视角下行模型参数的敏感性不同。我们还发现,树冠的行结构会影响模型输入参数的敏感性。发现LAI通常是三个典型光谱带中最敏感的参数。 a和h还被识别为VNIR频带中沿行或近行方向的敏感参数。 LIDF.a在某些视角相对敏感,而LIDF.b在三个典型光谱带中不敏感。 k在所有视角和光谱带中对模型输出具有边际影响,红色带中的热点方向周围除外。这项工作的主要贡献是将全局灵敏度分析技术应用于行模型,其结果对于反演期间的参数检索具有参考价值。

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