Influence of landscape spatial heterogeneity on the non-linear estimation of leaf area index from moderate spatial resolution remote sensing data

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GEOV1: LAI and FAPAR essential climate variables and FCOVER global time series capitalizing over existing products. Part1: Principles of development and production (2013, unknown): “However, its effect will be significant mainly for the larger LAI values as discussed by Garrigues et al. (2006).”
Scale Issues in Remote Sensing: A Review on Analysis, Processing and Modeling (2009, methodology): “Fernandes et al. [53] simply used empirical relationships between spectral vegetation indices and surface estimations of LAI, which are in-situ measurements from the auxiliary sites, to estimate coarse-scale LAI.”
Assimilating a synthetic Kalman filter leaf area index series into the WOFOST model to improve regional winter wheat yield estimation (2016, methodology): “Details of these regression models an be found in Huang et al. (2015b). The RMSE values were also sed for these regression equations as the observational errors for M LAI in the EnKF algorithm.”