Mostrar o rexistro simple do ítem
dc.contributor.author | Díaz Varela, Ramón Alberto |
dc.contributor.author | Rosa, Raúl de la |
dc.contributor.author | León, Lorenzo |
dc.contributor.author | Zarco Tejada, Pablo J. |
dc.date.accessioned | 2020-06-23T10:28:31Z |
dc.date.available | 2020-06-23T10:28:31Z |
dc.date.issued | 2015 |
dc.identifier.citation | Díaz-Varela, R.A.; De la Rosa, R.; León, L.; Zarco-Tejada, P.J. High-Resolution Airborne UAV Imagery to Assess Olive Tree Crown Parameters Using 3D Photo Reconstruction: Application in Breeding Trials. Remote Sens. 2015, 7, 4213-4232 |
dc.identifier.uri | http://hdl.handle.net/10347/23050 |
dc.description.abstract | The development of reliable methods for the estimation of crown architecture parameters is a key issue for the quantitative evaluation of tree crop adaptation to environment conditions and/or growing system. In the present work, we developed and tested the performance of a method based on low-cost unmanned aerial vehicle (UAV) imagery for the estimation of olive crown parameters (tree height and crown diameter) in the framework of olive tree breeding programs, both on discontinuous and continuous canopy cropping systems. The workflow involved the image acquisition with consumer-grade cameras on board a UAV and orthomosaic and digital surface model generation using structure-from-motion image reconstruction (without ground point information). Finally, geographical information system analyses and object-based classification were used for the calculation of tree parameters. Results showed a high agreement between remote sensing estimation and field measurements of crown parameters. This was observed both at the individual tree/hedgerow level (relative RMSE from 6% to 20%, depending on the particular case) and also when average values for different genotypes were considered for phenotyping purposes (relative RMSE from 3% to 16%), pointing out the interest and applicability of these data and techniques in the selection scheme of breeding programs. |
dc.description.sponsorship | The authors would like to thank Todolivo S.L. for hosting the hedgerow trial. This work has been partly supported by research projects EM2014-003 funded by “Proxectos Plan Galego de Investigación, Innovación e Crecemento 2011-2015 (Plan I2C)”, from the “Consellería de Cultura, Educación e Ordenación Universitaria. Xunta de Galicia”, RTA2012-00018-C02-01 from the National Institute for Agricultural and Food Research and Technology (INIA), partially funded by the European Regional Development Fund (ERDF) and AGL2012-40053-C03-01 from the Spanish “Ministerio de Economia y Competitividad”. Plant materials evaluated in this work were obtained in the cooperative breeding program carried out by the University of Cordoba and the Institute of Agricultural and Fishery Research and Training (IFAPA). |
dc.language.iso | eng |
dc.publisher | MDPI |
dc.rights | © 2015 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/4.0/) |
dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ |
dc.subject | Unmanned aerial vehicle (UAV) |
dc.subject | Olive phenotyping |
dc.subject | Tree crown architecture |
dc.subject | 3D image modelling |
dc.subject | Consumer-grade camera |
dc.subject | Very high-resolution imagery |
dc.subject | Digital surface model |
dc.subject | Geographical object-based image analysis |
dc.title | High-Resolution Airborne UAV Imagery to Assess Olive Tree Crown Parameters Using 3D Photo Reconstruction: Application in Breeding Trials |
dc.type | journal article |
dc.identifier.doi | 10.3390/rs70404213 |
dc.relation.publisherversion | https://doi.org/10.3390/rs70404213 |
dc.type.hasVersion | VoR |
dc.identifier.essn | 2072-4292 |
dc.rights.accessRights | open access |
dc.contributor.affiliation | Universidade de Santiago de Compostela. Departamento de Botánica |
dc.description.peerreviewed | SI |
Ficheiros no ítem
Este ítem aparece na(s) seguinte(s) colección(s)
-
BOT-Artigos [137]