Evaluating the Performance of Sentinel-3A OLCI Land Products for Gross Primary Productivity Estimation Using AmeriFlux Data

Abstract

Accurate and reliable estimation of gross primary productivity (GPP) is of great significance in monitoring global carbon cycles. The fraction of absorbed photosynthetically active radiation (FAPAR) and vegetation index products of the Moderate Resolution Imaging Spectroradiometer (MODIS) are currently the most widely used data in evaluating GPP. The launch of the Ocean and Land Colour Instrument (OLCI) onboard the Sentinel-3 satellite provides the FAPAR and the OLCI Terrestrial Chlorophyll Index (OTCI) products with higher temporal resolution and smoother spatial distribution than MODIS, having the potential to monitor terrain GPP. OTCI is one of the red-edge indices and is particularly sensitive to canopy chlorophyll content related to GPP. The purpose of the study is to evaluate the performance of OLCI FAPAR and OTCI for the estimation of GPP across seven biomes in 2017–2018. To this end, OLCI FAPAR and OTCI products in combination with insitu meteorological data were first integrated into the MODIS GPP algorithm and in three OTCI-driven models to simulate GPP. The modeled GPP (GPP_OLCI-FAPAR and GPP_OTCI) were then compared with flux tower GPP (GPP_EC) for each site. Furthermore, the GPP_OLCI-FAPAR and GPP derived from the MODIS FAPAR (GPP_MODIS-FAPAR) were compared. Results showed that the performance of GPP_OLCI-FAPAR was varied in different sites, with the highest R² of 0.76 and lowest R² of 0.45. The OTCI-driven models that include APAR data exhibited a significant relationship with GPP_EC for all sites, and models using only OTCI provided the most varied performance, with the relationship between GPP_OTCI and GPP_EC from strong to nonsignificant. Moreover, GPP_OLCI-FAPAR (R² = 0.55) performed better than GPP_MODIS-FAPAR (R² = 0.44) across all biomes. These results demonstrate the potential of OLCI FAPAR and OTCI products in GPP estimation, and they also provide the basis for their combination with the soon-to-launch Fluorescence Explorer satellite and their integration with the Sentinel-3 land surface temperature product into light use models for GPP monitoring at regional and global scales.