Prediction of forest canopy light interception using three‐dimensional airborne LiDAR data

Abstract

The amount of light intercepted by forest canopies plays a crucial role in forest primary production. However, the photosynthetically active part of this intercepted solar radiation (IPAR) is difficult to measure using traditional ground‐based techniques. In situ measurement of IPAR requires labour‐intensive field work, often resulting in limited datasets, especially when collected over extensive areas. Remote sensing methods have been applied to the estimation of light interception in forests, but until recently have been restricted to two‐dimensional image data. These approaches do not directly account for the three‐dimensional structure of forested canopies, and therefore predicting IPAR for arbitrary sun positions is problematic. We utilized a 3D point cloud dataset acquired via an airborne laser ranging (LiDAR) system to predict in situ measured IPAR. This was achieved by defining a field‐of‐view (scope) function between observer points just above the forest floor and the sun, which relate IPAR to the LiDAR data over southern pine experimental plots containing a wide range of standing biomass. A conical scope function with an angular divergence from the centreline of ±7° provided the best agreement with the in situ measurements. This scope function yielded remarkably consistent IPAR estimates for different pine species and growing conditions. IPAR for loblolly stands, which have diffuse canopy architecture, was slightly underestimated.