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Remote estimation of vine canopy density in vertically shoot‐positioned vineyards: determining optimal vegetation indices

Remote estimation of vine canopy density in vertically shoot‐positioned vineyards: determining... Three spectral vegetation indices were examined for their correlation with vertically shoot‐positioned canopy density (leaf area per metre of canopy) using both field spectroscopy data at the vine scale, and aerial image analysis at the vineyard scale. Vine canopy density accounted for a significant amount of the variability in all three vegetation indices (r2= 0.65 to 0.92). The perpendicular vegetation index (PVI) was found to have the greatest information cost as well as the poorest coefficient of determination value, and thus was the least desirable of the indices examined. The ratio‐based indices (RVI and NDVI) were shown to have similar information contents; however, the RVI was found to be more linearly related to canopy density over a broad range of values, and thus more desirable for vineyard remote sensing applications. Results from this analysis corroborate with findings from investigators in woodland and forest environments, and provide evidence of the complex nature of vineyard scene reflectance properties. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Australian Journal of Grape and Wine Research Wiley

Remote estimation of vine canopy density in vertically shoot‐positioned vineyards: determining optimal vegetation indices

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References (37)

Publisher
Wiley
Copyright
Copyright © 2002 Wiley Subscription Services, Inc., A Wiley Company
ISSN
1322-7130
eISSN
1755-0238
DOI
10.1111/j.1755-0238.2002.tb00220.x
Publisher site
See Article on Publisher Site

Abstract

Three spectral vegetation indices were examined for their correlation with vertically shoot‐positioned canopy density (leaf area per metre of canopy) using both field spectroscopy data at the vine scale, and aerial image analysis at the vineyard scale. Vine canopy density accounted for a significant amount of the variability in all three vegetation indices (r2= 0.65 to 0.92). The perpendicular vegetation index (PVI) was found to have the greatest information cost as well as the poorest coefficient of determination value, and thus was the least desirable of the indices examined. The ratio‐based indices (RVI and NDVI) were shown to have similar information contents; however, the RVI was found to be more linearly related to canopy density over a broad range of values, and thus more desirable for vineyard remote sensing applications. Results from this analysis corroborate with findings from investigators in woodland and forest environments, and provide evidence of the complex nature of vineyard scene reflectance properties.

Journal

Australian Journal of Grape and Wine ResearchWiley

Published: Jul 1, 2002

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