Canopy foliar nitrogen retrieved from airborne hyperspectral imagery by correcting for canopy structure effects

Abstract

A statistical relationship between canopy mass-based foliar nitrogen concentration (%N) and canopy bidi-rectional reflectance factor (BRF) has been repeatedly demonstrated. However, the interaction betweenleaf properties and canopy structure confounds the estimation of foliar nitrogen. The canopy scatteringcoefficient (the ratio of BRF and the directional area scattering factor, DASF) has recently been suggestedfor estimating %N as it suppresses the canopy structural effects on BRF. However, estimation of %N usingthe scattering coefficient has not yet been investigated for longer spectral wavelengths (>855 nm). Weretrieved the canopy scattering coefficient for wavelengths between 400 and 2500 nm from airbornehyperspectral imagery, and then applied a continuous wavelet analysis (CWA) to the scattering coefficientin order to estimate %N. Predictions of %N were also made using partial least squares regression (PLSR).We found that %N can be accurately retrieved using CWA (R2= 0.65, RMSE = 0.33) when four waveletfeatures are combined, with CWA yielding a more accurate estimation than PLSR (R2= 0.47, RMSE = 0.41).We also found that the wavelet features most sensitive to %N variation in the visible region relate tochlorophyll absorption, while wavelet features in the shortwave infrared regions relate to protein anddry matter absorption. Our results confirm that %N can be retrieved using the scattering coefficient aftercorrecting for canopy structural effect. With the aid of high-fidelity airborne or upcoming space-bornehyperspectral imagery, large-scale foliar nitrogen maps can be generated to improve the modeling ofecosystem processes as well as ecosystem-climate feedbacks.