Estimation of radiation transfer and rainfall interception from drone LiDAR data by modeling 3D canopy structure and ray tracing in plantation forest

The multidimensional arrangement of upper canopy features is a physical driver of energy and water balance under various canopies, and standard modeling approaches integrate leaf area index (LAI) and canopy closure (CC) to describe canopies. Similar to physical canopy structure measurements, field measurements of throughfall and stemflow are also important for understanding canopy interception component of evapotranspiration in forest systems. However, the effects on canopy interception and understory radiation transfer due to temporal and spatial changes in stand characteristics caused by forest management are not well understood. The experiments were conducted in two plantation forests located in Tochigi and Fukushima prefecture, Japan. Throughfall was computed from 20 rain gauges distributed on a grid under the forest canopy, 3 stemflow collectors was set up around the tree trunks connected to a bucket with water level sensor. Three-dimensional point clouds from the forest canopy and understory vegetation were collected using drone LiDAR. For canopy modeling, a voxel-based method was used to create 3D representations of forest canopies, and an analysis of these point-derived canopy structures was performed disregarding optical properties of canopy elements. For light modeling, the optical properties of the different objects were created to calculate and simulate light that passes through the canopy using the ray tracer. This physics-based model was used to generate hemispherical photographs to further calculate LAI and canopy openness. Destructive sampling methods was used to accurately measured leaf area index to verify the accuracy of simulated hemispherical photographs for LAI calculation. In addition, by further analyzing the multiple return data (three-echo) included in the small footprint drone LiDAR, this study calculated the laser penetration index (LPI) and developed an empirical model of the LAI and LiDAR data for the watershed scale. Measured throughfall and stemflow results were related to the estimated LAI for further projection of canopy interception data. After thinning one year, it needs less water to saturate the canopy (2.1mm) compared to before thinning (2.7mm) and 9 years after thinning (2.5mm) due to the reduction and recovering in canopy openness (97%->44%->90%). Throughfall increase was slowed down with the increase of thinning pass time. These results indicate that LAI can be accurately estimated for plantation forests conditions using LiDAR data and further estimate the canopy interception.