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dc.contributor.authorMolina-Valero, Juan Alberto
dc.contributor.authorMartínez Calvo, Adela
dc.contributor.authorGinzo Villamayor, María José
dc.contributor.authorNovo Pérez, Manuel Antonio
dc.contributor.authorÁlvarez-González, J.G.
dc.contributor.authorMontes, Fernando
dc.contributor.authorPérez-Cruzado, César
dc.date.accessioned2022-05-30T18:01:09Z
dc.date.available2022-05-30T18:01:09Z
dc.date.issued2022
dc.identifier.citationJuan Alberto Molina-Valero, Adela Martínez-Calvo, María José Ginzo Villamayor, Manuel Antonio Novo Pérez, Juan Gabriel Álvarez-González, Fernando Montes, César Pérez-Cruzado, Operationalizing the use of TLS in forest inventories: The R package FORTLS, Environmental Modelling & Software, Volume 150, 2022, 105337, ISSN 1364-8152, https://doi.org/10.1016/j.envsoft.2022.105337. (https://www.sciencedirect.com/science/article/pii/S1364815222000433)es_ES
dc.identifier.urihttp://hdl.handle.net/2183/30821
dc.description.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.es_ES
dc.description.sponsorshipThis work was supported by the Spanish Ministry of Science and Innovation [AGL2016-76769-C2-2-R; PID2020-119204RB-C22] and Galician Regional Government [2020-CP031; ED431F 2020/02]; JAMV was supported by the Spanish Ministry of Science, Innovation and Universities through the FPU program [FPU16/03057]; AMC was supported by Galician Regional Government within the framework of the agreement “Development of the Galician continuous forest inventory” [2020-CP031]; CPC was supported by the Spanish Ministry of Science and Innovation [RYC2018-024939-I]es_ES
dc.description.sponsorshipXunta de Galicia; ED431F 2020/02es_ES
dc.description.sponsorshipXunta de Galicia; 2020-CP031es_ES
dc.language.isoenges_ES
dc.publisherElsevieres_ES
dc.relationinfo:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/AGL2016-76769-C2-2-R/ES/MODELIZACION DEL EFECTO DE LA INTENSIDAD DE PERTURBACION SOBRE LA ESTRUCTURA Y EL STOCK DE CARBONO EN MASAS NATURALES A PARTIR DEL INVENTARIO FORESTAL NACIONAL/
dc.relationinfo:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2020-119204RB-C22/ES/CONSERVACION VS GESTION. DEFINICION DE INDICES PARA LA CARACTARIZACION DE LA INTENSIDAD DE GESTION Y PROVISION DE SERVICIOS ECOSITEMICOS: SEGUIMIENTO Y OPTIMIZACION/
dc.relationinfo:eu-repo/grantAgreement/MECD/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/FPU16%2F03057/ES/
dc.relationinfo:eu-repo/grantAgreement/MECD/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/FPU16%2F03057/ES/
dc.relation.urihttps://doi.org/10.1016/j.envsoft.2022.105337es_ES
dc.rightsAtribución 4.0 Internacionales_ES
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.subjectForest monitoringes_ES
dc.subjectForest stands parameterses_ES
dc.subjectLiDARes_ES
dc.subjectPrecision forestryes_ES
dc.subjectRemote sensinges_ES
dc.subjectTerrestrial-based-technologieses_ES
dc.titleOperationalizing the Use of TLS in Forest Inventories: The R Package FORTLSes_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.rights.accessinfo:eu-repo/semantics/openAccesses_ES
UDC.journalTitleEnvironmental Modelling & Softwarees_ES
UDC.volume150es_ES
UDC.startPage105337es_ES
dc.identifier.doi10.1016/j.envsoft.2022.105337


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