Assessment of Satellite Chlorophyll-Based Leaf Maximum Carboxylation Rate (Vcmax) Using Flux Observations at Crop and Grass Sites

Abstract

The leaf maximum carboxylation rate (Vcmax) is a key parameter in modeling plant photosynthesis. The rapid and accurate acquisition of Vcmax at large scales can improve understanding of global vegetation productivity and the terrestrial carbon cycle. In this article, we assessed the retrieval of Vcmax from satellite data by validating these data using flux observations made at eight crop and grass sites. Firstly, an empirical model applicable to C3 species that was based on the semimechanistic linkage between leaf chlorophyll and Vcmax was used to derive Vcmax from satellite data. Then, using vegetation, soil, and meteorological variables as inputs, the SCOPE model was used to estimate Vcmax from half-hourly or hourly flux observations at each site. The estimates of Vcmax were assessed by comparing the simulated gross primary production (GPP) against the observed GPP: that is, the Vcmax value corresponding to its simulated diurnal GPP data with minimum root-mean-square error (RMSE) was selected as the inverted Vcmax value. Finally, the Vcmax values retrieved from MERIS and Semtinel-3 OLCI satellite data were validated using the in situ flux site observations. The results showed that the estimates of Vcmax based on satellite data successfully captured the seasonal variations in Vcmax retrieved from the tower-based GPP data, giving a mean RMSE value of 15.30 μmol m-2 s-1. Our results support the retrieval of Vcmax from satellite data based on the link with leaf chlorophyll content and show that there was good agreement between Vcmax derived from remote sensing and flux data.