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Evaluation of spectral-based and canopy-based vegetation indices from UAV and Sentinel 2 images to assess spatial variability and ground vine parameters

Published online by Cambridge University Press:  01 June 2017

A. Matese ,
S. F. Di Gennaro ,
C. Miranda ,
A. Berton  and
L.G. Santesteban
A. Matese*
Affiliation:
Institute of Biometeorology, National Research Council (CNR-IBIMET), Via G. Caproni, 8, 50145 Florence, Italy
S. F. Di Gennaro
Affiliation:
Institute of Biometeorology, National Research Council (CNR-IBIMET), Via G. Caproni, 8, 50145 Florence, Italy
C. Miranda
Affiliation:
Dpto. Producción Agraria, Universidad Pública de Navarra, Campus Arrosadia, 31006 Pamplona (Navarra), Spain
A. Berton
Affiliation:
Institute of Clinical Physiology, National Research Council (CNR-IFC), Via Moruzzi 1, 56124 Pisa, Italy
L.G. Santesteban
Affiliation:
Dpto. Producción Agraria, Universidad Pública de Navarra, Campus Arrosadia, 31006 Pamplona (Navarra), Spain
*
†E-mail a.matese@ibimet.cnr.it
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Abstract

New remote sensing technologies have provided unprecedented results in vineyard monitoring. The aim of this work was to evaluate different sources of images and processing methodologies to describe spatial variability of spectral-based and canopy-based vegetation indices within a vineyard, and their relationship with productive and qualitative vine parameters. Comparison between image-derived indices from Sentinel 2 NDVI, unfiltered and filtered UAV NDVI and with agronomic features have been performed. UAV images allow calculating new non-spectral indices based on canopy architecture that provide additional and useful information to the growers with regards to within-vineyard management zone delineation.

Keywords

UAVSentinel-2NDVIspatial variabilitycanopy architecture
Type
UAV applications
Information
Advances in Animal Biosciences , Volume 8 , Special Issue 2: Papers presented at the 11th European Conference on Precision Agriculture (ECPA 2017), John McIntyre Centre, Edinburgh, UK, July 16–20 2017 , July 2017 , pp. 817 - 822
Copyright
© The Animal Consortium 2017 

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