Estimating Stand Variables in Forest Inventories

Terrestrial Laser Scanning (TLS) enables rapid, automatic and detailed 3D representation 23 of surfaces with an easily handled scanner device. TLS therefore shows great potential for use in 24 Forest Inventories (FIs). However, the lack of well established algorithms for TLS data processing 25 hampers operational use of the scanner for FI purposes. Here we present FORTLS, an R package 26 specifically developed to automate TLS point cloud data processing for forestry purposes. The 27 FORTLS package enables (i) detection of trees and estimation of their diameter at breast height (dbh), 28 (ii) estimation of some stand variables (e.g. density, basal area, mean and dominant height), (iii) 29 computation of metrics related to important tree attributes estimated in FIs at stand level and (iv) 30 optimization of plot design for combining TLS data and field measured data. FORTLS can be used 31 with single-scan TLS data, thus improving data acquisition and shortening the processing time, as 32 well as increasing sample size in a cost-efficient manner. The package also includes several features 33 for correcting occlusion problems in order to produce improved estimates of stand variables. These 34 features of the FORTLS package will enable the operational use of TLS in FIs, in combination with 35 inference techniques derived from model-based and model-assisted approaches. 36