Correcting in-situ SIF measurements from nadir view footprint to the whole flux-tower landscape

Recent advances in solar-induced chlorophyll fluorescence (SIF) provide a new opportunity for terrestrial vegetation monitoring. Ground-based SIF measurements with concurrent eddy covariance (EC) flux observations have been used to understand the relationship between SIF and gross primary production (GPP) across various ecosystems and environmental conditions. However, the footprint mismatch between SIF and GPP increases the uncertainty of the SIF-GPP relationships at the site level, especially for heterogeneous sites. EC observations at ecosystem level generally cover much larger footprint areas (e.g., ~1km) than SIF observations (a bare fiber with nadir, e.g., <10m). Correcting the nadir-view footprint-based SIF observations to the GPP footprint-based SIF is expected to decrease the variability of SIF-GPP relationships with the same plant species. Here, we intend to correct SIF observations by the automated Fluospec2 system (hemispheric-nadir system) to the GPP footprint-based SIF using NIRvP which is the product of near-infrared of vegetation (NIRv) and photosynthetic active radiation (PAR). We used a portable SIF system to collect SIF and NIRv simultaneously across different sites at two-week frequency in the 2021 growing season and built the spatial relationship between SIF and NIRvP at site-level for corn and soybean, separately. The temporal variation of the spatial SIF-NIRvP relationship was also investigated. Additionally, the spatial relationship between SIF-NIRvP as well as its temporal variation was further investigated using the TROMOPI satellite-based SIF and NIRvP data. EC flux footprint model was used to get the GPP flux footprint at daily scale. Daily NIRv at the SIF footprint and GPP footprint were calculated from our groups STAIR dataset. Nadir-view footprint SIF was corrected to GPP footprint SIF based on the relationship between SIF and NIRvP. We expect that after footprint correction, SIF-GPP relationships would be more stable with the same species in terms of both correlation and regression slope. Our study could provide a potential way to match the footprint of ground-based SIF and GPP which are important for further understanding the link between SIF and GPP.