|
|
Registros recuperados : 14 | |
6. | | HIRIGOYEN, A.; NAVARRO-CERRILLO, R.; BAGNARA, M.; FRANCO, J.; RESQUÍN, F.; RACHID, C. Modelling taper and stem volume considering stand density in Eucalyptus grandis and Eucalyptus dunnii. i Forest - Biogeosciences and Forestry, 2021, Volume 14, Issue 2, Pages 127-136.OPEN ACCESS. DOI: https://doi.org/10.3832/ifor3604-014 Article history: Received: Jul 31, 2020 - Accepted: Jan 15, 2021. Acknowledgments: The authors thank the Instituto Nacional de Investigaciones Agropecuarias (INIAUruguay) for supporting fieldwork and the INIA Scholarship for PhD studies....Biblioteca(s): INIA Tacuarembó. |
| |
9. | | RIZZO-MARTÍN, I.; HIRIGOYEN, A.; ARTHUS-BACOVICH, R.; VARO-MARTÍNEZ, M.A.; NAVARRO-CERRILLO, R. Site index estimation using airborne laser scanner data in Eucalyptus dunnii Maide stands in Uruguay. Forests, 2023, Volume 14, Issue 5, article 933. https://doi.org/10.3390/f14050933 -- OPEN ACCESS. 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...Biblioteca(s): INIA Las Brujas. |
| |
10. | | HIRIGOYEN, A.; VARO-MARTINEZ, M.A.; RACHID, C.; FRANCO, J.; NAVARRO-CERRILLO, R.M. Stand characterization of eucalyptus spp. Plantations in uruguay using airborne lidar scanner technology. Remote Sensing, 1 December 2020, Volume 12, Issue 23, Article number 3947, Pages 1-19. Open Access. Doi: https://doi.org/10.3390/rs12233947 Article history: Received: 16 October 2020 / Revised: 5 November 2020 / Accepted: 21 November 2020 / Published: 2 December 2020. Acknowledgments: The authors thank the Instituto Nacional de Investigaciones Agropecuarias (INIA-Uruguay) for...Biblioteca(s): INIA Tacuarembó. |
| |
11. | | RESQUÍN, F.; BENTANCOR, L.; CARRASCO-LETELIER, L.; RACHID, C.; NAVARRO-CERRILLO, R.M. Rotation length of intensive Eucalyptus plantations: how it impacts on productive and energy sustainability. Biomass and Bioenergy, 2022, Volume 166, article 106607. doi: https://doi.org/10.1016/j.biombioe.2022.106607 Article history: Received 11 April 2022; Received in revised form 31 August 2022; Accepted 18 September 2022; To be published November 2022.
Corresponding author: Fernando Resquin, Route 5 km 368, CP45000, INIA Tacuarembó, Uruguay. E-mail...Biblioteca(s): INIA Las Brujas. |
| |
12. | | HIRIGOYEN, A.; ACUNA. M.; RACHID, C.; FRANCO, J.; NAVARRO-CERRILLO, R. Use of optimization modeling to assess the effect of timber and carbon pricing on harvest scheduling, carbon sequestration, and net present value of eucalyptus plantations. Forests, 2021, Volume 12, Issue 6, Article number 651. OPEN ACCESS. Doi: https://doi.org/10.3390/f12060651 Article history: Received 21 March 2021; Revised 10 May 2021; Accepted 12 May 2021; Published: 21 May 2021.
Academic Editor: Luis Diaz-Balteiro.
The authors thank the Instituto Nacional de Investigaciones Agropecuarias (INIA-Uruguay) for...Biblioteca(s): INIA Las Brujas. |
| |
13. | | HIRIGOYEN, A.; ACOSTA-MUÑOZ, C.; SALAMANCA, A.J.A.; VARO-MARTINEZ, M.Á.; RACHID, C.; FRANCO, J.; NAVARRO-CERRILLO, R. A machine learning approach to model leaf area index in Eucalyptus plantations using high-resolution satellite imagery and airborne laser scanner data. Annals of Forest Research, 2021, Volume 64, Issue 2, Pages 165-183. OPEN ACCESS. doi: https://doi.org/10.15287/afr.2021.2073 Article history: Received October 27, 2020; Revised December 14, 2021; Accepted December 21, 2021.
Corresponding author: Hirigoyen, A.; National Institute of Agricultural Research (INIA), Tacuarembó, Uruguay; email:ahirigoyen@inia.org.uy...Biblioteca(s): INIA Las Brujas. |
| |
14. | | RESQUÍN, F.; DUQUE-LAZO, J.; ACOSTA-MUÑÓZ, C.; RACHID, C.; CARRASCO-LETELIER, L.; NAVARRO-CERRILLO, R.M. Modelling Current and Future Potential Habitats for Plantations of Eucalyptus grandis Hill ex Maiden and E. dunnii Maiden in Uruguay. Forests, 2020, vol. 11, Issue 9, Article 948. OPEN ACCESS. Doi: https://doi.org/10.3390/f11090948 Article history: Received: 6 July 2020; Accepted: 24 August 2020; Published: 29 August 2020.
Supplementary material.
This article belongs to the Special Issue Modeling of Species Distribution and Biodiversity in Forests -...Biblioteca(s): INIA Las Brujas; INIA Tacuarembó. |
| |
Registros recuperados : 14 | |
|
|
| Acceso al texto completo restringido a Biblioteca INIA Tacuarembó. Por información adicional contacte bibliotb@tb.inia.org.uy. |
Registro completo
|
Biblioteca (s) : |
INIA Tacuarembó. |
Fecha actual : |
10/12/2020 |
Actualizado : |
10/12/2020 |
Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
Circulación / Nivel : |
Internacional - -- |
Autor : |
HIRIGOYEN, A.; VARO-MARTINEZ, M.A.; RACHID, C.; FRANCO, J.; NAVARRO-CERRILLO, R.M. |
Afiliación : |
ANDRES EDUARDO HIRIGOYEN DOMINGUEZ, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; MARÍA ANGELES VARO-MARTINEZ, Department of Forestry Engineering, Laboratory of Silviculture, Dendrochronology and Climate Change, DendrodatLab-ERSAF, University of Cordoba, Campus de Rabanales, Córdoba, Spain; ANA CECILIA RACHID CASNATI, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; JORGE FRANCO, Faculty of Agronomy, University of the Republic, Paysandú, Uruguay; RAFAEL MARÍA NAVARRO-CERRILLO, Department of Forestry Engineering, Laboratory of Silviculture, Dendrochronology and Climate Change, DendrodatLab-ERSAF, University of Cordoba, Campus de Rabanales, Córdoba, Spain. |
Título : |
Stand characterization of eucalyptus spp. Plantations in uruguay using airborne lidar scanner technology. |
Fecha de publicación : |
2020 |
Fuente / Imprenta : |
Remote Sensing, 1 December 2020, Volume 12, Issue 23, Article number 3947, Pages 1-19. Open Access. Doi: https://doi.org/10.3390/rs12233947 |
DOI : |
10.3390/rs12233947 |
Idioma : |
Inglés |
Notas : |
Article history: Received: 16 October 2020 / Revised: 5 November 2020 / Accepted: 21 November 2020 / Published: 2 December 2020. Acknowledgments: The authors thank the Instituto Nacional de Investigaciones Agropecuarias (INIA-Uruguay) for supporting our research work and for help during the fieldwork. We are particularly grateful for the support of Roberto Scoz, Demian Gomez, Zenia Barrios and Gustavo Balmelli (INIA), Mariano Blanco, Santiago Heguaburu, Carola Odone and José Carlos de Mello (FOSA). R.M.N.-C. acknowledges the ISOPINE (UCO-1265298) and ESPECTRAMED (CGL2017-86161-R) projects for methodological support. We acknowledge the institutional support of the University of Cordoba-Campus de Excelencia CEIA3. We also thank the ERSAF group and, particularly. Cristina Acosta and Antonio Ariza. for their assistance during this research. We thank David Walker for his revisions of the different versions of this manuscript, and the anonymous referees for their comments and corrections. |
Contenido : |
Abstract: Airborne lidar scanner (ALS) technology is used in a variety of applications, including forestry. ALS has enormous potential for the estimation of relevant biometric parameters in forest plantations. This study investigates the use of an object-oriented semi-automated segmentation algorithm for stands delineation, based on modeling ALS data, in plantations of Eucalyptus grandis and E. dunnii in Uruguay. The results show that non-parametric methods delivered more accurate and less biased results for total volume (TV) with R2 0.93, RMSE 20.04 m3 h ?1 for E. grandis and R2 0.93, RMSE 18.43 m3 h ?1 for E. dunnii; and above ground biomass (AGB) with R2 0.95, RMSE 70.2 kg h?1 for E. grandis and R2 0.96, RMSE: 71.2 Kg h?1 for E. dunnii. Parametric methods performed better for dominant height (Ho) with R2 0.98, RMSE 0.67 m and R2 : 0.96, RMSE: 0.8 m for E. grandis and E. dunnii, respectively. The most informative ALS metrics for the estimation of AGB and TV were metrics related to the elevation in parametric models (Elev.70 and Elev.75), while for the non-parametric models (k-NN) they were Elev.75 and canopy density. For Ho, the ALS metrics selected were also related to elevation both in the parametric (Elev.90 and Elev.99) and random forest models (Elev.max and Elev.75). The segmentation methodology proposed here matched closely the segments delineated by human operators, and provides a low-cost, cost-effective, easy to apply and update model aimed at generating AGB or TV maps for harvest tasks, based on rasters derived from ALS metrics. The present research shows the capacity of ALS metrics to improve extensive strategic inventories; validating and promoting the adoption of ALS technology for inventory forest stands of Eucalyptus spp. in Uruguay. MenosAbstract: Airborne lidar scanner (ALS) technology is used in a variety of applications, including forestry. ALS has enormous potential for the estimation of relevant biometric parameters in forest plantations. This study investigates the use of an object-oriented semi-automated segmentation algorithm for stands delineation, based on modeling ALS data, in plantations of Eucalyptus grandis and E. dunnii in Uruguay. The results show that non-parametric methods delivered more accurate and less biased results for total volume (TV) with R2 0.93, RMSE 20.04 m3 h ?1 for E. grandis and R2 0.93, RMSE 18.43 m3 h ?1 for E. dunnii; and above ground biomass (AGB) with R2 0.95, RMSE 70.2 kg h?1 for E. grandis and R2 0.96, RMSE: 71.2 Kg h?1 for E. dunnii. Parametric methods performed better for dominant height (Ho) with R2 0.98, RMSE 0.67 m and R2 : 0.96, RMSE: 0.8 m for E. grandis and E. dunnii, respectively. The most informative ALS metrics for the estimation of AGB and TV were metrics related to the elevation in parametric models (Elev.70 and Elev.75), while for the non-parametric models (k-NN) they were Elev.75 and canopy density. For Ho, the ALS metrics selected were also related to elevation both in the parametric (Elev.90 and Elev.99) and random forest models (Elev.max and Elev.75). The segmentation methodology proposed here matched closely the segments delineated by human operators, and provides a low-cost, cost-effective, easy to apply and update model aimed at generating AGB or TV... Presentar Todo |
Palabras claves : |
ABOVE GROUND BIOMASS; DOMINANT HEIGHT; INTENSIVE SILVICULTURE; PARAMETRIC AND NON-PARAMETRIC METHODS; STAND SEGMENTATION; VOLUME. |
Asunto categoría : |
K10 Producción forestal |
Marc : |
LEADER 03675naa a2200265 a 4500 001 1061559 005 2020-12-10 008 2020 bl uuuu u00u1 u #d 024 7 $a10.3390/rs12233947$2DOI 100 1 $aHIRIGOYEN, A. 245 $aStand characterization of eucalyptus spp. Plantations in uruguay using airborne lidar scanner technology.$h[electronic resource] 260 $c2020 500 $aArticle history: Received: 16 October 2020 / Revised: 5 November 2020 / Accepted: 21 November 2020 / Published: 2 December 2020. Acknowledgments: The authors thank the Instituto Nacional de Investigaciones Agropecuarias (INIA-Uruguay) for supporting our research work and for help during the fieldwork. We are particularly grateful for the support of Roberto Scoz, Demian Gomez, Zenia Barrios and Gustavo Balmelli (INIA), Mariano Blanco, Santiago Heguaburu, Carola Odone and José Carlos de Mello (FOSA). R.M.N.-C. acknowledges the ISOPINE (UCO-1265298) and ESPECTRAMED (CGL2017-86161-R) projects for methodological support. We acknowledge the institutional support of the University of Cordoba-Campus de Excelencia CEIA3. We also thank the ERSAF group and, particularly. Cristina Acosta and Antonio Ariza. for their assistance during this research. We thank David Walker for his revisions of the different versions of this manuscript, and the anonymous referees for their comments and corrections. 520 $aAbstract: Airborne lidar scanner (ALS) technology is used in a variety of applications, including forestry. ALS has enormous potential for the estimation of relevant biometric parameters in forest plantations. This study investigates the use of an object-oriented semi-automated segmentation algorithm for stands delineation, based on modeling ALS data, in plantations of Eucalyptus grandis and E. dunnii in Uruguay. The results show that non-parametric methods delivered more accurate and less biased results for total volume (TV) with R2 0.93, RMSE 20.04 m3 h ?1 for E. grandis and R2 0.93, RMSE 18.43 m3 h ?1 for E. dunnii; and above ground biomass (AGB) with R2 0.95, RMSE 70.2 kg h?1 for E. grandis and R2 0.96, RMSE: 71.2 Kg h?1 for E. dunnii. Parametric methods performed better for dominant height (Ho) with R2 0.98, RMSE 0.67 m and R2 : 0.96, RMSE: 0.8 m for E. grandis and E. dunnii, respectively. The most informative ALS metrics for the estimation of AGB and TV were metrics related to the elevation in parametric models (Elev.70 and Elev.75), while for the non-parametric models (k-NN) they were Elev.75 and canopy density. For Ho, the ALS metrics selected were also related to elevation both in the parametric (Elev.90 and Elev.99) and random forest models (Elev.max and Elev.75). The segmentation methodology proposed here matched closely the segments delineated by human operators, and provides a low-cost, cost-effective, easy to apply and update model aimed at generating AGB or TV maps for harvest tasks, based on rasters derived from ALS metrics. The present research shows the capacity of ALS metrics to improve extensive strategic inventories; validating and promoting the adoption of ALS technology for inventory forest stands of Eucalyptus spp. in Uruguay. 653 $aABOVE GROUND BIOMASS 653 $aDOMINANT HEIGHT 653 $aINTENSIVE SILVICULTURE 653 $aPARAMETRIC AND NON-PARAMETRIC METHODS 653 $aSTAND SEGMENTATION 653 $aVOLUME 700 1 $aVARO-MARTINEZ, M.A. 700 1 $aRACHID, C. 700 1 $aFRANCO, J. 700 1 $aNAVARRO-CERRILLO, R.M. 773 $tRemote Sensing, 1 December 2020, Volume 12, Issue 23, Article number 3947, Pages 1-19. Open Access. Doi: https://doi.org/10.3390/rs12233947
Descargar
Esconder MarcPresentar Marc Completo |
Registro original : |
INIA Tacuarembó (TBO) |
|
Biblioteca
|
Identificación
|
Origen
|
Tipo / Formato
|
Clasificación
|
Cutter
|
Registro
|
Volumen
|
Estado
|
Volver
|
Expresión de búsqueda válido. Check! |
|
|