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High-resolution airborne UAV imagery to assess olive tree crown parameters using 3D photo reconstruction: Application in breeding trials

AuthorsDíaz-Varela, Ramón A.; Rosa, Raúl de la; León, Lorenzo; Zarco-Tejada, Pablo J.
KeywordsVery high-resolution imagery
Geographical object-based image analysis
Digital surface model
Consumer-grade camera
Unmanned aerial vehicle (UAV)
Olive phenotyping
Tree crown architecture
3D image modelling
Issue Date8-Apr-2015
PublisherMultidisciplinary Digital Publishing Institute
CitationRemote Sensing 7(4): 4213-4232 (2015)
AbstractThe 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 forphenotyping 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. © 2015 by the authors; licensee MDPI, Basel, Switzerland.
Publisher version (URL)http://dx.doi.org/10.3390/rs70404213
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