Remotely estimating photosynthetic capacity, and its response to temperature, in vegetation canopies using imaging spectroscopy

To date, the utility of ecosystem and Earth system models (EESMs) has been limited by poor spatial and temporal representation of critical input parameters. For example, EESMs often rely on leaf-scale or literature-derived estimates for a key determinant of canopy photosynthesis, the maximum velocity of RuBP carboxylation (V-cmax, mu mol m(-2) s(-1)). Our recent work (Ainsworth et al., 2014; Serbin et al., 2012) showed that reflectance spectroscopy could be used to estimate V-cmax at the leaf level. Here, we present evidence that imaging spectroscopy data can be used to simultaneously predict V-cmax and its sensitivity to temperature (E-V) at the canopy scale. In 2013 and 2014, high-altitude Airborne Visible/Infrared Imaging Spectroscopy (AVIRIS) imagery and contemporaneous ground-based assessments of canopy structure and leaf photosynthesis were acquired across an array of monospecific agroecosystems in central and southern California, USA. A partial least-squares regression (PLSR) modeling approach was employed to characterize the pixel-level variation in canopy V-cmax (at a standardized canopy temperature of 30 degrees C) and E-V, based on visible and shortwave infrared AVIRIS spectra (414-2447 nm). Our approach yielded parsimonious models with strong predictive capability for V-cmax (at 30 degrees C) and E-V (R-2 of withheld data = 0.94 and 0.92, respectively), both of which varied substantially in the field (>= 1.7 fold) across the sampled crop types. The models were applied to additional AVIRIS imagery to generate maps of V-cmax and E-V, as well as their uncertainties, for agricultural landscapes in California. The spatial patterns exhibited in the maps were consistent with our in-situ observations. These findings highlight the considerable promise of airborne and, by implication, space-borne imaging spectroscopy, such as the proposed HyspIRI mission, to map spatial and temporal variation in key drivers of photosynthetic metabolism in terrestrial vegetation. (C) 2015 Elsevier Inc. All rights reserved.