VALUING FOREST STAND AT A GLANCE WITH UAV BASED LIDAR

Abstract. Comprehensive knowledge of characteristics and variability of any material is essential for its best utilization; hence forest managers are increasingly recognising the importance of resource quality characterisation earlier along the value-chain. Current methods for cruising timber at the stump lack information on branch characteristics and detailed assessment based on terrestrial lidar systems are restricted to sampled trees for assessment at the block level. Rich and dense information on vertical structure of the canopies captured using lidar system from a closer range like on a UAV platform provides a flexible, quick and a cost-effective alternative for assessing forest stands. In this study, along with detailed tree characterisation and variability, we explore the potential of ultrahigh density lidar data acquired from a UAV platform (ULS) to develop a non-destructive estimation of a suite of timber quality determinants like branchiness, clear stem and stem straightness for standing trees, and further determine possible amount of bucking segments (logs) and their expected quality. Validation of the algorithm is tested on white pine stand in Petawawa Research Forest, Ontario, Canada, holds promise in determining spatially-explicit tree level and hence stand quality.