Operationalizing the use of TLS in forest inventories: The R package FORTLS. (April 2022)

• Record Type: Journal Article
• Authors: Molina-Valero, Juan Alberto; Martínez-Calvo, Adela; Ginzo Villamayor, María José; Novo Pérez, Manuel Antonio; Álvarez-González, Juan Gabriel; Montes, Fernando; Pérez-Cruzado, César
• Is Part Of: Environmental modelling & software. Volume 150(2022)
• Publication Date: 2022-04
• Subjects: Forest monitoring -- Forest stands parameters -- LiDAR -- Precision forestry -- Remote sensing -- Terrestrial-based-technologies; Environmental monitoring -- Computer programs -- Periodicals; Ecology -- Computer simulation -- Periodicals; Digital computer simulation -- Periodicals; Computer software -- Periodicals; Environmental Monitoring -- Periodicals; Computer Simulation -- Periodicals; Environnement -- Surveillance -- Logiciels -- Périodiques; Écologie -- Simulation, Méthodes de -- Périodiques; Simulation par ordinateur -- Périodiques; Logiciels -- Périodiques; Computer software; Digital computer simulation; Ecology -- Computer simulation; Environmental monitoring -- Computer programs; Periodicals; Electronic journals; 363.70015118
• DOI: 10.1016/j.envsoft.2022.105337
• Languages: English
• ISSNs: 1364-8152

Abstract

Abstract: Terrestrial Laser Scanning (TLS) devices show great potential for application in Forest Inventories (FIs) as they are capable of registering high resolution point clouds rapidly and automatically. Nevertheless, operational use of TLS for FI purposes has been hampered by the absence of algorithms for processing the acquired data, particularly in the single-scan mode, as occlusions result in loss of information. The R package FORTLS has been developed to overcome this obstacle, as it automates the processing of single-scan TLS point cloud data for forestry purposes and includes several features that deal with occlusions. FORTLS makes use of the main advantage of the single-scan scenario in FI, thus improving the efficiency of data acquisition and post-processing. All of these features of the FORTLS package are potentially valuable for the operational use of TLS in FIs, in combination with inference techniques derived from model-based and model-assisted approaches. Highlights: The new R package FORTLS automates TLS point cloud processing for forestry use Variables and metrics related to forest attributes are generated at stand-level FORTLS works with single scans, facilitating data acquisition and processing FORTLS will enable the operational use of TLS in forest inventories