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FORTLS: an R package for processing TLS data and estimating stand variables in forest inventories
* 1 , 2 , 3 , 1 , 4 , 1
1  Unit for Sustainable Environmental and Forest Management (UXAFORES), Department of Agricultural and Forestry Engineering, Higher Polytechnic School, University of Santiago de Compostela, Lugo, Spain
2  Department of Statistics, Mathematical Analysis and Optimization, Faculty of Mathematics, University of Santiago de Compostela, Santiago de compostela, Spain
3  Technological Institute for Industrial Mathematics (ITMATI), Santiago de Compostela, Spain
4  INIA-CIFOR, Madrid, Spain


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

Keywords: Forest inventory; LiDAR; stand-level; remote sensing; software; R-package; TLS