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.
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