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Image-Based Decision Tools for Vineyard Management

Published by the American Society of Agricultural and Biological Engineers, St. Joseph, Michigan

Citation:  Paper number  033129,  2003 ASAE Annual Meeting . (doi: 10.13031/2013.14068) @2003
Authors:   Lee F. Johnson, Lars Pierce, Jennifer DeMartino and Shlemon Youkhana, Ramakrishna Nemani, Daniel Bosch
Keywords:   Remote sensing, multi-spectral image processing, leaf area, irrigation modeling, yield monitor, viticulture, decision making

Vineyard managers in Californias premium wine industry are concerned with canopy development, field uniformity, relative amounts of leaf and fruit production, and irrigation management strategy. The application of high-resolution satellite imagery to viticultural management in Napa Valley was examined with respect to each of these issues. Ikonos multispectral data were transformed to a spectral vegetation index and combined with ground measurements to map vineyard canopy density, expressed both as leaf area index (LAI) and leaf area per vine. Within-field variance was used to quantify field uniformity. Leaf area and yield data were combined to map end-of-season vine balance (leaf area to fruit weight ratio). A water balance model was developed to assist with irrigation planning. The model combines leaf area with weather and soils databases to predict soil moisture, vine stress, and water replacement needs. The simulation operates on a 24 hour timestep, and results can be temporally aggregated as needed. It is concluded that remote sensing can provide a basis for decision support in vineyard management.

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