Abstract
Accurate ground-based measurements of leaf area index (LAI) are needed for validation of remote sensing-based retrievals used in models estimating plant water use, stress, carbon assimilation and other land surface processes. Several methods for indirect LAI estimation with the Plant Canopy Analyzer (PCA, LAI-2200C, LI-COR, Lincoln, NE, USA) were evaluated using destructive (direct) leaf area measurements in three split-canopy vineyards and one double-vertical vineyard in California, as part of the Grape Remote sensing and Atmospheric Profile and Evapotranspiration eXperiment (GRAPEX). A method with the sensor facing the canopy, and four readings occurring evenly across the interrow space, had a coefficient of determination (R2) of 0.87 and relative root mean square error (RRMSE) of 16%, when compared to direct LAI measurements via destructive sampling. A previously used method, with the sensor facing down-row, showed lower correlation to direct LAI (R2 = 0.75, RRMSE = 33%) and underestimation which was mitigated by removing the outer sensor rings from analysis. A PCA method is recommended for rapid and accurate LAI estimation in split-canopy vineyards, though local calibration may be required. The method was tested within small units of ground surface area, which compliments high-resolution datasets such as those acquired by small unmanned aerial vehicles. The utility of ground-based LAI measurements to validate remote sensing products is discussed.
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Acknowledgements
We would like to thank the staff of Viticulture, Chemistry, and Enology Division of E. & J. Gallo Winery for the collection and processing of field data during GRAPEX IOPs. This project would not have been possible without the cooperation of vineyard staff and managers including Ernie Dosio, Joe Larranaga, Jose Botello, and Amanpreek Virk, for logistical support of GRAPEX field and research activities. USDA is an equal opportunity provider and employer.
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White, W.A., Alsina, M.M., Nieto, H. et al. Determining a robust indirect measurement of leaf area index in California vineyards for validating remote sensing-based retrievals. Irrig Sci 37, 269–280 (2019). https://doi.org/10.1007/s00271-018-0614-8
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DOI: https://doi.org/10.1007/s00271-018-0614-8