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Operationalizing the use of TLS in forest inventories: the R package FORTLS

Authors :
Universidade de Santiago de Compostela. Departamento de Estatística, Análise Matemática e Optimización
Universidade de Santiago de Compostela. Departamento de Matemáticas
Universidade de Santiago de Compostela. Departamento de Produción Vexetal e Proxectos de Enxeñaría
Molina Valero, Juan Alberto
Martínez Calvo, Adela
Ginzo Villamayor, María José
Novo Pérez, Manuel Antonio
Álvarez González, Juan Gabriel
Montes, Fernando
Pérez Cruzado, César
Universidade de Santiago de Compostela. Departamento de Estatística, Análise Matemática e Optimización
Universidade de Santiago de Compostela. Departamento de Matemáticas
Universidade de Santiago de Compostela. Departamento de Produción Vexetal e Proxectos de Enxeñaría
Molina Valero, Juan Alberto
Martínez Calvo, Adela
Ginzo Villamayor, María José
Novo Pérez, Manuel Antonio
Álvarez González, Juan Gabriel
Montes, Fernando
Pérez Cruzado, César
Publication Year :
2022

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

Details

Database :
OAIster
Notes :
English
Publication Type :
Electronic Resource
Accession number :
edsoai.on1400979591
Document Type :
Electronic Resource