Quantifying the variability of ecosystem functional traits and plant metabolism with field and imaging spectroscopy

A primary goal of remote sensing, and imaging spectroscopy (IS) in particular, is the development of generalizable algorithms to repeatedly and accurately map key ecosystem properties related to plant chemistry and function across space and time.  We present a generalized framework for the spectroscopic estimation of foliar biochemical, structural, and metabolic traits at the leaf and canopy scales, including the quantification of uncertainties in trait estimates.  Our work shows the strong potential for IS data to provide key ecological information across broad spatial scales that are critical to understanding fundamental questions in ecology and for informing ecosystem modeling.