Modelling Three-Dimensional Spatiotemporal Distributions of Forest Photosynthetically Active Radiation Using UAV-Based Lidar Data

The three dimensional (3-D) spatiotemporal variations of forest photosynthetically active radiation (PAR) dictate the exchange rates of matter and energy in the carbon and water cycle processes between the plant-soil system and the atmosphere. It is still challenging to explicitly simulate spatial PAR values at any specific position within or under a discontinuous forest canopy. In this study, we propose a novel lidar-based approach to estimate both direct and diffuse forest PAR components from a 3-D perspective. An improved path length-based direct PAR estimation method was developed by incorporating the point density along a light transmission path, and we also obtained the diffuse PAR components using a point-based sky view analysis by assuming the anisotropic sky diffuse distribution. We compared the total PAR modelled using three light path length-based parameters with reference data measured by radiometers on a five-minute time scale during a daily solar course. Our results show that, in a discontinuous forest canopy, the effective path length is a feasible and powerful (R2 = 0.92, p < 0.01) parameter to capture the spatiotemporal variations of total PAR along a light transmission path with a mean bias of −53.04 μmol·m−2·s−1(−6.8%). Furthermore, incorporating point density and spatial distribution factors will further improve the final estimation accuracy (R2 = 0.97, p < 0.01). In the meantime, diffuse PAR tends to be overestimated by 17% at noon and underestimated by about 10% at sunrise and sunset periods by assuming the isotropic sky diffuse distribution. The proposed lidar-based 3-D PAR model will provide a solid foundation to various process-based eco-hydrological models for simulating plant physiological processes such as photosynthesis and evapotranspiration, intra-species competition and succession, and snowmelt dynamics purposes.