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Mapping forest canopy nitrogen content by inversion of coupled leaf-canopy radiative transfer models from airborne hyperspectral imagery

机译:通过耦合叶冠层辐射转移模型从机载高光谱图像中映射森林冠层氮含量

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Foliar nitrogen is a critical factor in leaf physiological processes, plant growth, and ecosystem functioning, which has been proposed as one of the essential biodiversity variables. Nitrogen has been quantified by a number of empirical approaches using hyperspectral data, but the retrieval of nitrogen through a physically based approach remains a challenge. A recent study by Wang et al. (2015a) has revealed that leaf protein can be successfully estimated from fresh leaf spectra using a revised leaf radiative transfer model PROPECT-5 which incorporated the effects of leaf protein and cellulose?+?lignin on leaf reflectance and transmittance. This provides a potential approach of estimating nitrogen using radiative transfer models given the correlation between protein and nitrogen. However, such a revised leaf model has not been tested for the estimation of leaf nitrogen at the canopy level. In this study, a canopy reflectance model INFORM, coupled with the revised PROSPECT-5 model, was used to retrieve leaf and canopy nitrogen content in a mixed temperate forest using the wavelengths of 800–2500?nm from airborne hyperspectral imagery. Ecological criteria were applied to the parameterization of the model to reduce unrealistic combinations of input parameters. Global sensitivity analysis showed that leaf protein played a small but distinct role in driving the variation of canopy reflectance in the INFORM model. More accurate estimation was obtained for canopy nitrogen content (R2?=?0.64, RMSE?=?1.90, NRMSE?=?0.18) than leaf nitrogen content (R2?=?0.46, RMSE?=?3.79e-05, NRMSE?=?0.19). Moreover, inversion techniques, particularly regularized look-up tables, further improved the estimation accuracies compared to the original tables. Our results indicate that leaf and canopy nitrogen content can be retrieved successfully at the canopy level by inversion of INFORM. Both the direct and indirect effects of nitrogen on canopy reflectance are important for nitrogen estimation. The maps of leaf and canopy nitrogen content are the first to be generated using inversion of coupled leaf-canopy models, and the spatial variation of foliar nitrogen appears to be reasonable and consistent with ecological knowledge.
机译:叶状氮是叶生理过程,植物生长和生态系统功能的关键因素,其被提出为必不可少的生物多样性变量之一。通过使用高光谱数据的许多经验方法量化氮气,但通过物理上的方法检索氮仍然是挑战。王等人最近的研究。 (2015A)已经揭示了使用修正的叶片辐射转移模型的新鲜叶谱估计叶片蛋白,其掺入叶片蛋白和纤维素的效果α+?木质素对叶反射率和透射率。这提供了使用辐射转移模型估算氮的潜在方法,鉴于蛋白质和氮气之间的相关性。然而,这种修订的叶片模型尚未测试在冠层水平下的叶片氮气估计。在本研究中,通过从空气传播的高光谱图像中使用800-2500Ω·NM的波长来检测混合温带林中的叶片和冠层氮含量的冠层反射率模型通知。将生态标准应用于模型的参数化以降低输入参数的不现实组合。全局敏感性分析表明,叶片蛋白在推送Inform模型中驱动顶篷反射的变化方面发挥了很小但不同的作用。对于冠层氮含量(R2?= 0.64,RMSE?=Δ= 0.10,nrmse?= 0.18)比叶氮含量(R2?= 0.46,Rmse?=?3.79e-05,Nrmse? =?0.19)。此外,与原始表格相比,反转技术,特别是正则查询表,进一步提高了估计精度。我们的结果表明,通过通知的反转,可以在冠层水平上成功检索叶片和冠层氮含量。氮的直接和间接效应在树冠反射率上对氮估计很重要。叶片和冠层氮含量的地图是第一个使用偶联的叶片冠层模型的转化产生的待生物,并且叶状氮的空间变化似乎是合理的,并且与生态知识一致。

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