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

Wang, Z, Skidmore, A, Darvishzadeh, R and Wang, T 2018, 'Mapping forest canopy nitrogen content by inversion of coupled leaf-canopy radiative transfer models from airborne hyperspectral imagery', Agricultural and Forest Meteorology, vol. 253254, pp. 247-260.


Document type: Journal Article
Collection: Journal Articles

Title Mapping forest canopy nitrogen content by inversion of coupled leaf-canopy radiative transfer models from airborne hyperspectral imagery
Author(s) Wang, Z
Skidmore, A
Darvishzadeh, R
Wang, T
Year 2018
Journal name Agricultural and Forest Meteorology
Volume number 253254
Start page 247
End page 260
Total pages 14
Publisher Elsevier
Abstract 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 8002500 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.
Subject Earth Sciences not elsewhere classified
Keyword(s) Forest
Hyperspectral remote sensing
INFORM
Leaf and canopy nitrogen
Model inversion
PROSPECT
Radiative transfer model
DOI - identifier 10.1016/j.agrformet.2018.02.010
Copyright notice © 2018 Elsevier B.V. All rights reserved.
ISSN 0168-1923
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