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Determining a robust indirect measurement of leaf area index in California vineyards for validating remote sensing-based retrievals
dc.contributor.author | White, William A. | |
dc.contributor.author | Alsina, Maria Mar | |
dc.contributor.author | Nieto, Héctor | |
dc.contributor.author | McKee, Lynn G. | |
dc.contributor.author | Gao, Feng | |
dc.contributor.author | Kustas, William P. | |
dc.contributor.other | Producció Vegetal | ca |
dc.date.accessioned | 2020-05-28T08:43:44Z | |
dc.date.available | 2020-05-28T08:43:44Z | |
dc.date.issued | 2018-12-05 | |
dc.identifier.citation | White, 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.issn | 0342-7188 | ca |
dc.identifier.uri | http://hdl.handle.net/20.500.12327/827 | |
dc.description.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. | ca |
dc.format.extent | 22 | ca |
dc.language.iso | eng | ca |
dc.publisher | Springer Verlag | ca |
dc.relation.ispartof | Irrigation Science | ca |
dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 International | ca |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | * |
dc.title | Determining a robust indirect measurement of leaf area index in California vineyards for validating remote sensing-based retrievals | ca |
dc.type | info:eu-repo/semantics/article | ca |
dc.description.version | info:eu-repo/semantics/acceptedVersion | ca |
dc.rights.accessLevel | info:eu-repo/semantics/openAccess | |
dc.embargo.terms | 12 mesos | ca |
dc.subject.udc | 634 | ca |
dc.identifier.doi | https://doi.org/10.1007/s00271-018-0614-8 | ca |
dc.contributor.group | Ús Eficient de l'Aigua en Agricultura | ca |
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