Back to Search Start Over

« On-the-go » multispectral imaging system to characterize the development of vineyard foliage with quantitative and qualitative vegetation indices

Authors :
Sylvain Villette
Marie-Aure Bourgeon
Sébastien Debuisson
Christelle Gée
Jean-Noël Paoli
Gawain Jones
Agroécologie [Dijon]
Institut National de la Recherche Agronomique ( INRA ) -Université de Bourgogne ( UB ) -AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement-Université Bourgogne Franche-Comté ( UBFC )
Comité Interprofessionnel du Vin de Champagne ( CIVC )
Institut National de la Recherche Agronomique (INRA)-Université de Bourgogne (UB)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement-Université Bourgogne Franche-Comté [COMUE] (UBFC)
Comité Interprofessionnel du Vin de Champagne (CIVC)
Université de Bourgogne (UB)-Institut National de la Recherche Agronomique (INRA)-Université Bourgogne Franche-Comté [COMUE] (UBFC)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement
Source :
Precision Agriculture, Precision Agriculture, Springer Verlag, 2016, 18 (3), pp.293-308. 〈10.1007/s11119-016-9489-y〉, Precision Agriculture, Springer Verlag, 2016, 18 (3), pp.293-308. ⟨10.1007/s11119-016-9489-y⟩
Publication Year :
2016
Publisher :
HAL CCSD, 2016.

Abstract

EA GESTAD Agrosup CT1; International audience; Over the last years, the literature presents new technologies to optimize vineyard management. In the proximal sensing context, optical sensors are mainly developed to characterize the vegetation and the most famous one is the Greenseeker RT-100 (Trimble, Germany), that provides NDVI. The interpretation of its measurements is complex because it overlaps quantitative and qualitative information. However, it is a robust active sensor especially dedicated to characterize vineyard at early growth stage. To overcome these limits, we developed a multispectral (RGB, NIR) imaging system. We present a first application of spectral imagery, in proximal sensing conditions, to characterize the vine foliage of three grapevine varieties (Meunier, Pinot Noir and Chardonnay) at four phenological stages. The imaging system is embedded on a ground vehicle acquiring images with natural light, and an original radiometric calibration is proposed. From images, three agronomic indices (NDVIimage, NDVIvegetation and “foliage occupation”) are defined. They are computed from entire images and from the area of the grapes. These indices are compared to Greenseeker ones at the beginning of berry formation to be assessed. Whatever the grapevine variety the NDVIimage is in agreement with the index provided by Greenseeker (NDVIGS). At the other stages, the comparison of NDVIGS to the other indices leads to a new interpretation of NDVIGS depending on the phenological stage. The new indices provide a better understanding on the part of quantitative and quantitative information in Greenseeker index and lead to a more accurate leaf quantity estimation (from entire images), or specific physiological status characterization.

Details

Language :
English
ISSN :
13852256 and 15731618
Database :
OpenAIRE
Journal :
Precision Agriculture, Precision Agriculture, Springer Verlag, 2016, 18 (3), pp.293-308. 〈10.1007/s11119-016-9489-y〉, Precision Agriculture, Springer Verlag, 2016, 18 (3), pp.293-308. ⟨10.1007/s11119-016-9489-y⟩
Accession number :
edsair.doi.dedup.....36502ce65e131b27d7d3ac140d15b5a7
Full Text :
https://doi.org/10.1007/s11119-016-9489-y〉