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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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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 Research – Wiley

Published: Jul 1, 2002

References

  • Biophysical and biochemical sources of variability in canopy reflectance
    Asner, Asner
  • Leaf color and vine size are related to yield in a phylloxera infested vineyard
    Baldy, Baldy; Benedicts, Benedicts; Johnson, Johnson; Weber, Weber; Baldy, Baldy; Osborn, Osborn; Burleigh, Burleigh
  • Potenials and limits of vegetation indices for LAI and APAR assessment
    Baret, Baret; Guyot, Guyot
  • Soil background effects on reflectance based crop coefficients for corn
    Bausch, Bausch
  • On the relation between NDVI, fractional vegetation cover, and leaf area index
    Carlson, Carlson; Ripley, Ripley
  • Evaluation of vegetation indices and a modified simple ratio for boreal applications
    Chen, Chen
  • Compact airborne spectro‐graphic imager (CASI) used for mapping biophysical parameters of boreal forests
    Chen, Chen; Leblanc, Leblanc
  • Vegetation canopy reflectance
    Colwell, Colwell
  • The light environment within grapevine canopies. I. Description and seasonal changes during fruit development
    Dokoozlian, Dokoozlian; Kliewer, Kliewer
  • Relationships between NDVI, canopy structure, and photosynthesis in three Californian vegetation types
    Gamon, Gamon; Field, Field
  • An empirical protocol for indirect measurements of leaf area index in grape ( Vitis vinifera L.)
    Grantz, Grantz; Williams, Williams
  • Suitability of spectral indices for evaluating vegetation characteristics on arid rangelands
    Huete, Huete; Jackson, Jackson
  • Soil and atmosphere influences on the spectra of partial canopies
    Huete, Huete; Jackson, Jackson
  • Spectral response of a plant canopy with different soil backgrounds
    Huete, Huete; Jackson, Jackson
  • Development of vegetation and soil indices for MODIS‐EOS
    Huete, Huete; Justice, Justice; Liu, Liu
  • Soil spectral effect on 4‐space vegetation discrimination
    Huete, Huete; Post, Post; Jackson, Jackson
  • Airborne imaging aids vineyard canopy evaluation
    Johnson, Johnson; Lobitz, Lobitz; Armstrong, Armstrong; Baldy, Baldy; Weber, Weber; Benedicts, Benedicts; Bosch, Bosch
  • A feedback based modification ofthe NDVI to minimize canopy background and atmospheric noise
    Liu, Liu; Huete, Huete
  • Canopy structure and radiation regime in grapevine. I. Spatial and angular distribution of leaf area in two canopy systems
    Mabrouk, Mabrouk; Carbonneau, Carbonneau; Sinoquet, Sinoquet
  • Indices of light microclimate and canopy structure of grapevines determined by 3D digitising and image analysis, and their relationship to grape quality
    Mabrouk, Mabrouk; Sinoquet, Sinoquet
  • Investigation of the utility of spectral vegetation indices for determining information on coniferous forests
    McDonald, McDonald; Gemmell, Gemmell; Lewis, Lewis
  • Evaluation of an indirect method for leaf area index determination in the vineyard: combined effects of cultivar, year and training system
    Ollat, Ollat; Fermaud, Fermaud; Tandonnet, Tandonnet; Neveux, Neveux
  • Functional equivalence of spectral vegetation indices
    Perry, Perry; Lautenschlager, Lautenschlager
  • Estimating vegetation amount from visible and near infrared reflectances
    Price, Price
  • Distinguishing vegetation from soil background information
    Richardson, Richardson; Wiegand, Wiegand
  • Estimating PAR absorbed by vegetation from bi‐directional reflectance measurements
    Roujean, Roujean; Breon, Breon
  • Grape canopy structure, light microclimate and photosynthesis. I. A two‐dimensional model of the spatial distribution of surface area densities and leaf ages in two canopy systems
    Schultz, Schultz
  • Principles of grapevine canopy management micro‐climate manipulation with implications for yield and quality. A review
    Smart, Smart
  • Comparitive analysis of two indirect methods of measuring leaf area index as applied to minimal and spur pruned grape vines
    Sommer, Sommer; Lang, Lang
  • Red and photographic infrared linear combinations for monitoring vegetation
    Tucker, Tucker
  • Relationships between leaf area index and landsat TM spectral vegeation indices across three temperate zone sites
    Turner, Turner; Cohen, Cohen
  • Effects of standing letter on the biophysical interpretation of plant canopies with spectral indices
    Leeuwen, Leeuwen; Huete, Huete
  • Photosynthesis and stomatal conductance related to reflectance on the canopy scale
    Verma, Verma; Sellers, Sellers; Walthall, Walthall; Hall, Hall; Kim, Kim; Goetz, Goetz
  • Leaf area, light interception and yield estimated from spectral components analysis
    Wiegand, Wiegand; Richardson, Richardson
  • Vegetation indices in crop assessments
    Wiegand, Wiegand; Richardson, Richardson; Escobar, Escobar; Gerbermann, Gerbermann