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Analyzing TLS Scan Distribution and Point Density for the Estimation of Forest Stand Structural Parameters

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Analyzing TLS Scan Distribution and Point Density for the Estimation of Forest Stand Structural Parameters

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dc.contributor.author Torralba, Jesús es_ES
dc.contributor.author Carbonell-Rivera, Juan Pedro es_ES
dc.contributor.author Ruiz Fernández, Luis Ángel es_ES
dc.contributor.author Crespo-Peremarch, Pablo es_ES
dc.date.accessioned 2023-05-24T18:02:03Z
dc.date.available 2023-05-24T18:02:03Z
dc.date.issued 2022-12 es_ES
dc.identifier.uri http://hdl.handle.net/10251/193573
dc.description.abstract [EN] In recent decades, the feasibility of using terrestrial laser scanning (TLS) in forest inventories was investigated as a replacement for time-consuming traditional field measurements. However, the optimal acquisition of point clouds requires the definition of the minimum point density, as well as the sensor positions within the plot. This paper analyzes the effect of (i) the number and distribution of scans, and (ii) the point density on the estimation of seven forest parameters: above-ground biomass, basal area, canopy base height, dominant height, stocking density, quadratic mean diameter, and stand density index. For this purpose, 31 combinations of TLS scan positions, from a single scan in the center of the plot to nine scans, were analyzed in 28 circular plots in a Mediterranean forest. Afterwards, multiple linear regression models using height metrics extracted from the TLS point clouds were generated for each combination. In order to study the influence of terrain slope on the estimation of forest parameters, the analysis was performed by using all the plots and by creating two categories of plots according to their terrain slope (slight or steep). Results indicate that the use of multiple scans improves the estimation of forest parameters compared to using a single one, although using more than three to five scans does not necessarily improves the accuracy. Moreover, it is also shown that lower accuracies are obtained in plots with steep slope. In addition, it was observed that each forest parameter has a strategic distribution depending on the field of view of the TLS. Regarding the point density analysis, the use of 1% to 0.1% (¿136 points·m¿2) of the initial point cloud density (¿37,240.86 points·m¿2) generates an R2adj difference of less than 0.01. These findings are useful for planning more efficient forest inventories, reducing acquisition and processing time as well as costs. es_ES
dc.description.sponsorship This research has been funded by the project PID2020-117808RB-C21 MCIN/AEI/10.13039/501100011033 and by the grant PEJ2018-002924-A Fondo de Garantia Juvenil en I+D+i ESF Investing in your future. es_ES
dc.language Inglés es_ES
dc.publisher MDPI AG es_ES
dc.relation.ispartof Forests es_ES
dc.rights Reconocimiento (by) es_ES
dc.subject Terrestrial laser scanning es_ES
dc.subject Point-cloud density es_ES
dc.subject Multi-scan es_ES
dc.subject Random sample es_ES
dc.subject LiDAR height metrics es_ES
dc.subject Scanner positions es_ES
dc.subject Terrain slope es_ES
dc.subject.classification INGENIERIA CARTOGRAFICA, GEODESIA Y FOTOGRAMETRIA es_ES
dc.title Analyzing TLS Scan Distribution and Point Density for the Estimation of Forest Stand Structural Parameters es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.3390/f13122115 es_ES
dc.relation.projectID info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2020-117808RB-C21/ES/CARTOGRAFIADO ESPECTRAL Y ESTRUCTURAL 3D DE COMBUSTIBLE MEDITERRANEO PARA LA MODELIZACION DEL COMPORTAMIENTO DEL FUEGO/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/AEI//PEJ2018-002924-A-AR//AYUDA GARANTIA JUVENIL AEI. ACTUACION: FORMACION EN PROCESADO DE DATOS CARTOGRAFICOS PARA LA PREVENCION Y RESPUESTA A INCENDIOS FORESTALES/ es_ES
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Escuela Técnica Superior de Ingeniería Geodésica, Cartográfica y Topográfica - Escola Tècnica Superior d'Enginyeria Geodèsica, Cartogràfica i Topogràfica es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Ingeniería Cartográfica Geodesia y Fotogrametría - Departament d'Enginyeria Cartogràfica, Geodèsia i Fotogrametria es_ES
dc.description.bibliographicCitation Torralba, J.; Carbonell-Rivera, JP.; Ruiz Fernández, LÁ.; Crespo-Peremarch, P. (2022). Analyzing TLS Scan Distribution and Point Density for the Estimation of Forest Stand Structural Parameters. Forests. 13(12):1-22. https://doi.org/10.3390/f13122115 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion https://doi.org/10.3390/f13122115 es_ES
dc.description.upvformatpinicio 1 es_ES
dc.description.upvformatpfin 22 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 13 es_ES
dc.description.issue 12 es_ES
dc.identifier.eissn 1999-4907 es_ES
dc.relation.pasarela S\479506 es_ES
dc.contributor.funder European Social Fund es_ES
dc.contributor.funder AGENCIA ESTATAL DE INVESTIGACION es_ES
dc.subject.ods 15.- Proteger, restaurar y promover la utilización sostenible de los ecosistemas terrestres, gestionar de manera sostenible los bosques, combatir la desertificación y detener y revertir la degradación de la tierra, y frenar la pérdida de diversidad biológica es_ES
upv.costeAPC 2200 es_ES


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