High-Resolution Airborne UAV Imagery to Assess Olive Tree Crown Parameters Using 3D Photo Reconstruction: Application in Breeding Trials

By Ramón Alberto Díaz-Varela, Raúl de la Rosa, Lorenzo León, Pablo J. Zarco-Tejada. Remote Sensing, 2015

299 citations recorded by the source corpus.

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.

Subfields: Ecology, Environmental Engineering, Plant Science

View Paper: https://www.semanticscholar.org/paper/669886f1cda6ffcf5cec723ec819d326c47ba3ea

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Ecology

In Environmental Engineering

In Plant Science

Lianjun Zhang

Citations in the corpus

Trends in Automatic Individual Tree Crown Detection and Delineation - Evolution of LiDAR Data (2016, methodology): “ITCD and related literature are summarized into four focus types: (1) research that concentrated on ITCD algorithm development [70,96]; (2) research that concentrated on applying ITCD results for forest parameter estimation or comparing different datasets using published ITCD algorithms [32,108,109]”