Scaling-up and model inversion methods with narrowband optical indices for chlorophyll content estimation in closed forest canopies with hyperspectral data

TLDR

Radiative transfer theory was applied at laboratory and field scales to link leaf reflectance and transmittance with canopy hyperspectral data for estimating chlorophyll content. The study used 12 Acer saccharum sites in Algoma, Canada, collecting field measurements, laboratory simulations, and 72‑channel CASI airborne imagery (1997–1999) and validated on 14 additional sites in 2000; infinite‑reflectance and canopy models (SAILH, MCRM) coupled with the PROSPECT leaf model were employed to simulate canopy reflectance and perform numerical inversion for chlorophyll estimation. Numerical inversion demonstrated that red‑edge indices such as R750/R710 outperform full‑spectrum CASI data, reducing the influence of shadows and LAI variation.

Abstract

Radiative transfer theory and modeling assumptions were applied at laboratory and field scales in order to study the link between leaf reflectance and transmittance and canopy hyper-spectral data for chlorophyll content estimation. This study was focused on 12 sites of Acer saccharum M. (sugar maple) in the Algoma Region, Canada, where field measurements, laboratory-simulation experiments, and hyper-spectral compact airborne spectrographic imager (CASI) imagery of 72 channels in the visible and near-infrared region and up to 1-m spatial resolution data were acquired in the 1997, 1998, and 1999 campaigns. A different set of 14 sites of the same species were used in 2000 for validation of methodologies. Infinite reflectance and canopy reflectance models were used to link leaf to canopy levels through radiative transfer simulation. The closed and dense (LAI>4) forest canopies of Acer saccharum M. used for this study, and the high spatial resolution reflectance data targeting crowns, allowed the use of optically thick simulation formulae and turbid-medium SAILH and MCRM canopy reflectance models for chlorophyll content estimation by scaling-up and by numerical model inversion approaches through coupling to the PROSPECT leaf radiative transfer model. Study of the merit function in the numerical inversion showed that red edge optical indices used in the minimizing function such as R/sub 750//R/sub 710/ perform better than when all single spectral reflectance channels from hyper-spectral airborne CASI data are used, and in addition, the effect of shadows and LAI variation are minimized.