Mapping vineyard leaf area with multispectral satellite imagery

Mapping vineyard leaf area with multispectral satellite imagery Vineyard leaf area is a key determinant of grape characteristics and wine quality. As is frequently the case in agriculture, available ground-based leaf area measurements employed by growers are not well suited to larger area mapping. In this study, IKONOS high spatial resolution, multispectral satellite imagery was used to map leaf area throughout two commercial wine grape vineyards (approximately 800 ha) in California's North Coast growing region. The imagery was collected near harvest during the 2000 growing season, converted to at-sensor radiance, geo-referenced and transformed to normalized difference vegetation index (NDVI) on a per pixel basis. Measurements at 24 ground calibration sites were used to convert NDVI maps to leaf area index (LAI; m 2 leaf area m −2 ground area); planting density was then used to express leaf area on a per vine basis (LA v ). Image-based LA v was significantly correlated with ground-based LA v estimates developed at 23 validation sites ( r 2 =0.72; P <0.001). Despite challenges posed by the discontinuous nature of vineyard canopies and architectural differences imposed by shoot positioning trellis systems, remote sensing appears to offer a basis for mapping vineyard leaf area in low LAI vineyards. Such maps can potentially be used to parameterize plant growth models or provide decision support for irrigation and canopy management. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Computers and Electronics in Agriculture Elsevier

Mapping vineyard leaf area with multispectral satellite imagery

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Publisher
Elsevier
Copyright
Copyright © 2002 Elsevier Science B.V.
ISSN
0168-1699
eISSN
1872-7107
DOI
10.1016/S0168-1699(02)00106-0
Publisher site
See Article on Publisher Site

Abstract

Vineyard leaf area is a key determinant of grape characteristics and wine quality. As is frequently the case in agriculture, available ground-based leaf area measurements employed by growers are not well suited to larger area mapping. In this study, IKONOS high spatial resolution, multispectral satellite imagery was used to map leaf area throughout two commercial wine grape vineyards (approximately 800 ha) in California's North Coast growing region. The imagery was collected near harvest during the 2000 growing season, converted to at-sensor radiance, geo-referenced and transformed to normalized difference vegetation index (NDVI) on a per pixel basis. Measurements at 24 ground calibration sites were used to convert NDVI maps to leaf area index (LAI; m 2 leaf area m −2 ground area); planting density was then used to express leaf area on a per vine basis (LA v ). Image-based LA v was significantly correlated with ground-based LA v estimates developed at 23 validation sites ( r 2 =0.72; P <0.001). Despite challenges posed by the discontinuous nature of vineyard canopies and architectural differences imposed by shoot positioning trellis systems, remote sensing appears to offer a basis for mapping vineyard leaf area in low LAI vineyards. Such maps can potentially be used to parameterize plant growth models or provide decision support for irrigation and canopy management.

Journal

Computers and Electronics in AgricultureElsevier

Published: Jan 1, 2003

References

  • Optical remote sensing applications in viticulture: a review
    Hall, A.; Lamb, D.W.; Holzapfel, B.; Louis, J.
  • Assessment of vine development according to available water resources by using remote sensing in La Mancha, Spain
    Montero, F.J.; Melia, J.; Brasa, A.; Segarra, D.; Cuesta, A.; Lanjeri, S.
  • Precision Agriculture in the 21st Century

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