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dc.contributor.authorWhite, William A.
dc.contributor.authorAlsina, Maria Mar
dc.contributor.authorNieto, Héctor
dc.contributor.authorMcKee, Lynn G.
dc.contributor.authorGao, Feng
dc.contributor.authorKustas, William P.
dc.contributor.otherProducció Vegetalca
dc.date.accessioned2020-05-28T08:43:44Z
dc.date.available2020-05-28T08:43:44Z
dc.date.issued2018-12-05
dc.identifier.citationWhite, William A., Maria Mar Alsina, Héctor Nieto, Lynn G. McKee, Feng Gao, and William P. Kustas. 2019. "Determining A Robust Indirect Measurement Of Leaf Area Index In California Vineyards For Validating Remote Sensing-Based Retrievals". Irrigation Science 37 (3): 269-280. doi:10.1007/s00271-018-0614-8.ca
dc.identifier.issn0342-7188ca
dc.identifier.urihttp://hdl.handle.net/20.500.12327/827
dc.description.abstractAccurate 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.ca
dc.format.extent22ca
dc.language.isoengca
dc.publisherSpringer Verlagca
dc.relation.ispartofIrrigation Scienceca
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internationalca
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.titleDetermining a robust indirect measurement of leaf area index in California vineyards for validating remote sensing-based retrievalsca
dc.typeinfo:eu-repo/semantics/articleca
dc.description.versioninfo:eu-repo/semantics/acceptedVersionca
dc.rights.accessLevelinfo:eu-repo/semantics/openAccess
dc.embargo.terms12 mesosca
dc.subject.udc634ca
dc.identifier.doihttps://doi.org/10.1007/s00271-018-0614-8ca
dc.contributor.groupÚs Eficient de l'Aigua en Agriculturaca


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Except where otherwise noted, this item's license is described as http://creativecommons.org/licenses/by-nc-nd/4.0/
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