Determining optimum wavelengths for leaf water content estimation from re ectance: a distance correlation approach

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Determining optimum wavelengths for leaf water content estimation from re ectance: a distance correlation approach

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Title: Determining optimum wavelengths for leaf water content estimation from re ectance: a distance correlation approach
Author: Ordoñez, Celestino;Oviedo de la Fuente, Manuel;Roca-Pardiñas, Javier;Rodríguez Pérez, José Ramón, 1968-
xmlui.dri2xhtml.METS-1.0.item-contributor: Escuela Superior y Tecnica de Ingenieros de Minas
xmlui.dri2xhtml.METS-1.0.item-area: Ingeniería Cartografica, Geodesica y Fotogrametria
Abstract: This paper proposes a method to estimate leaf water content from reflectance in four commercial vineyard varieties by estimating the local maxima of a distance correlation function. First, it applies four different functional regression models to the data and compares the models to test the viability of estimating water content from reflectance. It then applies our methodology to select a small number of wavelengths (optimum wavelengths) from the continuous spectrum, which simplifies the regression problem. Finally, it compares the results to those obtained by means of two different methods: a nonparametric kernel smoothing for variable selection in functional data and a wavelet-based weighted LASSO functional linear regression. Our approach proved to have some advantages over these two testing approaches, mainly in terms of the computing time and the lack of assumption of an underlying model. Finally the paper concludes that estimating water content from a few wavelengths is almost equivalent to doing so using larger wavelength intervals
xmlui.dri2xhtml.METS-1.0.item-desfisica: P. 1-10
xmlui.dri2xhtml.METS-1.0.item-peerreviewed: SI
Publisher: Elsevier
xmlui.dri2xhtml.METS-1.0.item-citation: Chemometrics and Intelligent Laboratory Systems, 2018, n. 172
URI: http://hdl.handle.net/10612/7087
Date: 2018-01-16
xmlui.dri2xhtml.METS-1.0.item-tipo: info:eu-repo/semantics/article
Subject: Ingeniería agrícola
xmlui.dri2xhtml.METS-1.0.item-palclave: Vineyard
Water content
Distance correlation
Functional analysis
Design points
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