Evaluating hyperspectral vegetation indices for estimating nitrogen concentration of winter wheat at different growth stages

By Fei Li, Y. Miao, S. Hennig, M. Gnyp, Xin-ping Chen, L. Jia, Georg Bareth. Precision Agriculture, 2010

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Reflectance estimation of canopy nitrogen content in winter wheat using optimised hyperspectral spectral indices and partial least squares regression (2014, methodology): “Hansen and Schjoerring (2003), Li et al. (2010) and Stroppiana et al. (2009) used the algorithm of two band combinations to extract optimum NDVI-like spectral indices in winter wheat and rice, respectively, which significantly improved the predictive power compared to the selected published…”
Estimating Biomass of Barley Using Crop Surface Models (CSMs) Derived from UAV-Based RGB Imaging (2014, background): “Biomass can be estimated through spectral reflectance measurements [11] from space [12,13], from the air [14–16] or from the ground [7,17–19].”
LAI assessment of wheat and potato crops by VENμS and Sentinel-2 bands (2011, background): “Applying non-linear models for plant properties assessment and prediction can lead to uncertain predicted values (Buschmann & Nagel, 1993; Coyne et al., 2009; Ding et al., 2009; Gonzalez-Sanpedro et al., 2008; Lee et al., 2004; Li et al., 2010; Tucker, 1979; Ustin et al., 2009; Vina et al., 2004).”