A LiDAR-Based System to Assess Poplar Biomass

dc.contributor.author
Andújar, Dionisio
dc.contributor.author
Escolà i Agustí, Alexandre
dc.contributor.author
Rosell Polo, Joan Ramon
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Sanz Cortiella, Ricardo
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Rueda-Ayala, Victor
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Fernandez Quintanilla, C.
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Ribeiro, Angela
dc.contributor.author
Dorado, José
dc.date.accessioned
2024-12-05T22:30:24Z
dc.date.available
2024-12-05T22:30:24Z
dc.date.issued
2018-11-14T09:50:58Z
dc.date.issued
2018-11-14T09:50:58Z
dc.date.issued
2016-06-21
dc.date.issued
2018-11-14T09:50:58Z
dc.identifier
https://doi.org/10.1007/s10343-016-0369-1
dc.identifier
0367-4223
dc.identifier
http://hdl.handle.net/10459.1/65098
dc.identifier.uri
http://hdl.handle.net/10459.1/65098
dc.description.abstract
This study evaluated the capabilities of a LiDAR-based system to characterize poplar trees for biomass production. The precision of the system was assessed by analyzing the relationship between the distance records and biophysical parameters. The terrestrial laser scanner (TLS) system consisted of a 2D time-of-flight LiDAR sensor, a gimbal to dynamically stabilize the sensor and a RTK-GPS to georeference its location and, subsequently, the sensor data. The sensor and its stabilizer were fixed facing downwards, on a metal frame designed for this purpose. Then, it was mounted on an all-terrain vehicle to perform 2D scans in planes perpendicular to the travel direction. Distances between the sensor and the surrounding objects had a high spatial resolution, providing high density 3D point clouds. Results on the reliability of the LiDAR system to estimate plant height showed a significant relationship between the sensor readings and actual poplar height and biomass data. In addition, tree biomass and tree volume were properly estimated in the point cloud. Regression analysis showed significant estimates of 0.79 and 0.89 for biomass and volume, respectively. These results reveal the potential of the LiDAR sensor to estimate both, plant height and plant biomass. This sensor's capability, added to its relative low cost, fast reaction, and the high number of readings per second consolidate the ideal system for estimating the productivity of biomass in energy crops. http://link.springer.com/article/10.1007%2Fs10343-016-0369-1
dc.description.abstract
This research was funded by the CICyT (Commision Interministerial de Ciencia y Tecnología, Spain), under Agreement No. AGL2011-25243 and AGL2014-52465-C4.
dc.format
application/pdf
dc.language
eng
dc.publisher
Springer-Verlag
dc.relation
info:eu-repo/grantAgreement/MICINN//AGL2011-25243/ES/SISTEMAS DE BAJOS INSUMOS PARA CULTIVOS LEÑOSOS PARA BIOMASA: DESARROLLO Y EVALUACION DE TACTICAS Y ESTRATEGIAS DE GESTION DE MALAS HIERBAS/
dc.relation
info:eu-repo/grantAgreement/MINECO//AGL2014-52465-C4-1-R/ES/DESARROLLO DE NUEVAS HERRAMIENTAS TECNOLOGICAS Y CONCEPTUALES PARA LA IMPLANTACION DE SISTEMAS DE GESTION INTEGRADA DE MALAS HIERBAS EN CULTIVOS DE CEREALES Y VIÑA/
dc.relation
info:eu-repo/grantAgreement/MINECO//AGL2014-52465-C4-2-R/ES/BALANCE ENTRE EFICACIA Y SOSTENIBILIDAD EN LA GESTION INTEGRADA DE MALAS HIERBAS EN SISTEMAS DE PRODUCCION EN ZONAS SEMIARIDAS DE CATALUÑA/
dc.relation
info:eu-repo/grantAgreement/MINECO//AGL2014-52465-C4-3-R/ES/INTEGRACION DE INFORMACION MULTISENSORIAL Y APRENDIZAJE AUTOMATICO PARA LA DETECCION, CARACTERIZACION Y RECONOCIMIENTO PRECISO DE ESTRUCTURAS NATURALES EN CAMPOS DE CULTIVO/
dc.relation
Versió preprint del document publicat a: https://doi.org/10.1007/s10343-016-0369-1
dc.relation
Gesunde Pflanzen, 2016, vol. 68, p. 155-162
dc.rights
(c) Springer-Verlag, 2016
dc.rights
info:eu-repo/semantics/openAccess
dc.subject
3D Plant structure
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Energy crops
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Productivity assessment
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Terrestrial LIDAR
dc.title
A LiDAR-Based System to Assess Poplar Biomass
dc.type
info:eu-repo/semantics/article
dc.type
submittedVersion


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