Fecha/hora: 16/06/2024 00:53:01

Biblioteca(s): | INIA Las Brujas.
Fecha corriente: | 09/06/2023
Fecha de la última actualización: | 09/06/2023
Autoria: | RIZZO-MARTÍN, I.; HIRIGOYEN, A.; ARTHUS-BACOVICH, R.; VARO-MARTÍNEZ, M.A.; NAVARRO-CERRILLO, R.
Afiliación: | IVÁN RIZZO-MARTÍN, Department of Forest Production and Wood Technology, Faculty of Agronomy, University of the Republic, Montevideo 12900, Uruguay; ANDRES EDUARDO HIRIGOYEN DOMINGUEZ, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; RODRIGO ARTHUS-BACOVICH, Observatory of Global Change of the Mediterranean Forest, Department of Forest Engineering, University of Córdoba, E-14071 Córdoba, Spain; MARÍA ÁNGELES VARO-MARTÍNEZ, Department of Forestry Engineering, Laboratory of Silviculture, Dendrochronology and Climate Change, DendrodatLab-ERSAF, University of Cordoba, Campus de Rabanales, Crta. IV, km. 396, E-14071 Córdoba, Spain; RAFAEL NAVARRO-CERRILLO, Department of Forestry Engineering, Laboratory of Silviculture, Dendrochronology and Climate Change, DendrodatLab-ERSAF, University of Cordoba, Campus de Rabanales, Crta. IV, km. 396, E-14071 Córdoba, Spain.
Título: | Site index estimation using airborne laser scanner data in Eucalyptus dunnii Maide stands in Uruguay.
Año de publicación: | 2023
Fuente/Imprenta: | Forests, 2023, Volume 14, Issue 5, article 933. https://doi.org/10.3390/f14050933 -- OPEN ACCESS.
ISSN: | 1999-4907 (electronic).
DOI: | 10.3390/f14050933
Idioma: | Inglés
Notas: | Article history: Received 16 March 2023; Revised 23 April 2023; Accepted 27 April 2023; Published 1 May 2023. -- Correspondence: Rizzo-Martín, I.; Department of Forest Production and Wood Technology, Faculty of Agronomy, University of the Republic, Montevideo, Uruguay; email:ivan-rizzo@hotmail.com -- Funding: This research was funded by SILVADAPT.NET (RED2018-102719-T), EVIDENCE (Ref: 2822/2021) and REMEDIO (PID2021-128463OB-I00). -- This article belongs to the Special Issue Application of Laser Scanning and Satellite Image in Forest Mensuration (https://www.mdpi.com/journal/forests/special_issues/Application_Mensuration ). -- License: This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Contenido: | Intensive silviculture demands new inventory tools for better forest management and planning. Airborne laser scanning (ALS) was shown to be one of the best alternatives for high-precision inventories applied to productive plantations. The aim of this study was to generate multiple stand-scale maps of the site index (SI) using ALS data in the intensive silviculture of Eucalyptus dunnii Maide plantations in Uruguay. Forty-three plots (314.16 m3) were established in intensive E. dunnii plantations in the departments of Río Negro and Paysandú (Uruguay). ALS data were obtained for an area of 1995 ha. Linear and Random Forest models were fitted to estimate the height and site index, and OrpheoToolBox (OTB) software was used for stand segmentation. Linear models for dominant height (DH) estimation had a better fit (R2 = 0.84, RMSE = 0.94 m, MAPE = 0.04, Bias = 0.002) than the Random Forest (R2 = 0.85, RMSE = 1.27 m, MAPE = 7.20, Bias=-0.173) model when including only the 99th percentile metric. The coefficient between RMSE values of the cross-validation and RMSE of the model had a higher value for the linear model (0.93) than the Random Forest (0.75). The SI was estimated by applying the RF model, which included the ALS metrics corresponding to the 99th height percentile and the 80th height bicentile (R2 = 0.65; RMSE = 1.62 m). OTB segmentation made it possible to define a minimum segment size of 2.03 ha (spatial radius = 30, range radius = 1 and minimum region size = 64). This study provides a new tool for better forest management and promotes the need for further progress in the application of ALS data in the intensive silviculture of Eucalyptus spp. plantations in Uruguay. © 2023 by the authors. Licensee MDPI, Basel, Switzerland.
Palabras-Clave: | Eucaliptus spp; LiDAR; Orpheo ToolBox (OTB); Precision silvicultural; Random forest; Site Index; Stand segmentation.
Categoría del tema: | K01 Ciencias forestales - Aspectos generales
URL: | https://www.mdpi.com/1999-4907/14/5/933/pdf
Registro original: | INIA Las Brujas (LB)
Ejemplares: | LB - (103532-1) - PXI - AP - DD - Forests/2023 -  -  - DIS