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IVES 9 IVES Conference Series 9 Use of hyperspectral data for assessing vineyard biophysical and quality parameters in northern Italy

Use of hyperspectral data for assessing vineyard biophysical and quality parameters in northern Italy

Abstract

A total of 39 study sites from 11 commercial vineyards located in two traditional growing areas of Northern Italy were identified for airborne hyperspectral acquisition in summer 2009 with the Aisa-EAGLE Airborne Hyperspectral Imaging Sensor. Field sampling campaigns were conducted during the airborne overflights and around harvest, collecting canopy structural parameters, leaf and canopy biophysical characteristics as well as spectral signatures and must quality traits. Several vegetation indices were calculated from each plot to relate variations in canopy structure and foliar pigment concentration to vine status and grape quality parameters. The up-scaling model through TCARI/OSAVI index allowed to yield acceptable estimates of leaf chlorophyll content. However model refinements are needed to improve its capacity to taking into account understory grass cover at the highest instrument resolution.

DOI:

Publication date: October 8, 2020

Issue: Terroir 2010

Type: Article

Authors

F. Meggio, G. Fila, A. Pitacco

University of Padova, Department of Environmental Agronomy and Crop Science I-35020Legnaro (PD), Italy

Contact the author

Keywords

hyperspectral remote sensing, physiological indices, stress detection, airborne remote sensing

Tags

IVES Conference Series | Terroir 2010

Citation

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Cohen, Y., Gogumalla, P., Bahat, I., Netzer, Y., Ben-Gal, A., Lenski, I., … Helman, D. (2019). Can time series of multispectral satellite images be used to estimate stem water potential in vineyards? In Precision agriculture ’19, The Netherlands: Wageningen Academic Publishers, pp. 445–451.
Laroche-Pinel, E., Duthoit, S., Albughdadi, M., Costard, A. D., Rousseau, J., Chéret, V., & Clenet, H. (2021). Towards vine water status monitoring on a large scale using sentinel-2 images. remote sensing, 13(9), 1837.
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