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

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.

[1]  Xiaodong Li,et al.  Water Bodies' Mapping from Sentinel-2 Imagery with Modified Normalized Difference Water Index at 10-m Spatial Resolution Produced by Sharpening the SWIR Band , 2016, Remote. Sens..

[2]  Alfonso Fernández-Manso,et al.  SENTINEL-2A red-edge spectral indices suitability for discriminating burn severity , 2016, Int. J. Appl. Earth Obs. Geoinformation.

[3]  Arko Lucieer,et al.  Sensor Correction of a 6-Band Multispectral Imaging Sensor for UAV Remote Sensing , 2012, Remote. Sens..

[4]  L. G. Santesteban,et al.  High-resolution UAV-based thermal imaging to estimate the instantaneous and seasonal variability of plant water status within a vineyard , 2017 .

[5]  Piero Toscano,et al.  Intercomparison of UAV, Aircraft and Satellite Remote Sensing Platforms for Precision Viticulture , 2015, Remote. Sens..

[6]  L. Johnson.  Temporal stability of an NDVI-LAI relationship in a Napa Valley vineyard , 2003 .

[7]  V. Freitas,et al.  Influence of the heterogeneity of grape phenolic maturity on wine composition and quality , 2011 .

[8]  Andrea Berton,et al.  Assessment of a canopy height model (CHM) in a vineyard using UAV-based multispectral imaging , 2017 .

[9]  B. Tisseyre,et al.  Are precision agriculture tools and methods relevant at the whole-vineyard scale? , 2013, Precision Agriculture.

[10]  B. Tisseyre,et al.  Oenological significance of vineyard management zones delineated using early grape sampling , 2013, Precision Agriculture.

[11]  Clement Atzberger,et al.  First Experience with Sentinel-2 Data for Crop and Tree Species Classifications in Central Europe , 2016, Remote. Sens..

[12]  Abderrahim Nemmaoui,et al.  Performance evaluation of object based greenhouse detection from Sentinel-2 MSI and Landsat 8 OLI data: A case study from Almería (Spain) , 2016, Int. J. Appl. Earth Obs. Geoinformation.

[13]  R. G. V. Bramley,et al.  Variation in vine vigour, grape yield and vineyard soils and topography as indicators of variation in the chemical composition of grapes, wine and wine sensory attributes , 2011 .

[14]  J. Arnó,et al.  Review. Precision Viticulture. Research topics, challenges and opportunities in site-specific vineyard management , 2009 .