2.3.3. Leaf, needle, and bark spectra

The leaf and needle spectral DHRF and DHTF, hereafter called simply as reflectance (R_leaf) and transmittance (T_leaf), were computed from the measurements made in an integrating sphere (Section 2.2.3) as

and

where DN_leaf,# and DN_{WR_leaf,#} are the readings taken from the sample and white reference, respectively, R_{WR_leaf} is the reflectance of the white reference, and G_R and G_T are the gap fractions in the sample. Stray light was subtracted from DN_leaf,R before DN_leaf,R was applied in calculation of R_leaf. For oak leaves, gap fractions were zero since the leaf always filled the sample port. Gap fraction in a needle sample was obtained by applying a threshold to the scanned image of the carrier with needles in it, and weighting the obtained black-and-white image with a ‘light mask’ that models the spatial distribution of the irradiance of the light beam on the sample. The procedure has been described in detail in [5]. The optimal threshold value (202 for pine, 187 for spruce) was selected so that, when the resulting gap fraction was applied in Eq. (6), the mean transmittance (T_leaf) at 410–420 nm matched a ‘target value’. The 410–420 nm region was used since in that region needle transmittance is close to zero with small residual variation depending on the sample, and thus the errors of the estimated gap fraction due to assuming constant transmittance are minimized. The target T_leaf values (0.021 for pine, 0.039 for spruce) were obtained in a separate measurement campaign in 2019, for the same species but grown in Finland. In that campaign, the gap fractions of the needle samples were obtained directly through measurements in the integrating sphere, by painting the illuminated side of the needles black, thus ensuring that the measured transmittance signal was only due to the transmission through the gaps between needles [9]. An accurate estimate of needle transmittance could then be derived from measurements made before painting, because the gap fraction was known. Finally, we applied an empirical bias correction to all processed transmittance spectra (i.e., for both leaves and needles) by adjusting T_leaf downwards by 5.5% (in relative terms). The bias correction was taken from the measurements made against a trusted reference method in [5], and it ensured that leaf and needle albedo (R_leaf + T_leaf) did not exceed unity in any of the measurements. Finally, bark reflectance spectra were also processed using Eq. (5).