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High Resolution Imaging applied to high Throughput Field Apple Phenotyping (HiRI-FAP)

Improving high-resolution multispectral and thermal images acquired from unmanned aerial vehicles (UAVs) for high-throughput field phenotyping

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The HiriFAP project made it possible to develop a methodology of high-throughput phentoyping based on airborne high-resolution imagery performed by UAV flights over apple plant groves submitted to variable hydric regimes. The HiriFAP project allowed us to validate (i) a flight procedure and image harvesting, thanks to programming RGB and NIR snapshots, and thermal-IR video; (ii) extraction of fix thermal IR images from video files, geometric and radiometric corrections of images, geolocation and mosaicking; (iii) extraction of multispectral data from image files; (iv) computation of vegetation and stress indices from these data; (v) relation of indices to the phenotypic variables acquired at ground level, in planta. The potential added value of an image post-treatment, consisting in image supervised classification is currently studied. Publication of the project results has been actively undertaken in front of different scientific audiences.


Since Hiri-FAP project produced real methodological breakthrough, transfer in professional context is currently undertaken. This consists of Aliage-fruits Casdar program (2014-2017), which aims at achieving a pre- and post-treatment pipeline dedicated to images acquired and assessing feasability of imagery procedures in professional conext.

Project Number : 1202-070

Year : 2012

Type of funding : AAP OS

Project type : AAP

Research units in the network : ITAP QUALISUD

Start date :
01 Feb 2013

End date :
15 Feb 2015

Flagship project :

Project leader :
Jean-Luc Regnard

Project leader's institution :

Project leader's RU :

Budget allocated :
87932 €

Total budget allocated ( including co-financing) :
87932 €

Funding :