Characterizing the three-dimensional spatiotemporal variation of forest photosynthetically active radiation using terrestrial laser scanning data

The three-dimensional (3-D) spatiotemporal distribution of forest canopy photosynthetically active radiation (PAR) is a major determinant of within-crown variations of leaf photosynthesis and transpiration. However, it remains challenging to map the 3-D spatiotemporal distribution of PAR within and under the forest canopy due to the limited ability to capture the detailed 3-D structures of forest canopies.This study proposes a simple approach to estimate the 3-D spatiotemporal distribution of forest canopy PAR at a fine spatial resolution based on terrestrial laser scanner (TLS) data by characterizing difference in transfer of incident solar direct PAR and diffuse PAR and by considering the effect of the orientation angles of foliage elements on the 3-D distribution of direct PAR. Estimated PAR was validated using 10-minute PAR measurements from pyranometers at different locations within four forest plots, at which effective leaf area index (LAIe) ranged from 0.83–4.25. It showed that the proposed method captured 85% (N=2831, p<0.001) of the variations in the field pyranometer measurements. Furthermore, the proposed method was also applicable for estimating the vertical distribution of PAR (R²=0.95, N=15, p<0.001). Direct, diffuse, and total PAR exhibited similar vertical distributions changing with LAIe. It was shown that without differentiation of direct and diffuse PAR or ignoring effects of orientation angles of foliage elements may cause errors of about 20% in the estimated 3-D PAR distribution. Furthermore, the results indicated that the proposed method can be used to estimate the vertical distribution of PAR when the average neighbor point distance (NPD) is ≤20 cm. This proposed method will be usable for accurate separation of sunlit and shaded leaves and estimation of vertical distribution of PAR, which will benefit to reduce uncertainties in the estimation of terrestrial carbon fluxes and retrieval of vegetation structural and biochemical parameters.