Quantifying Seasonal and Diurnal Cycles of Solar-Induced Fluorescence With a Novel Hyperspectral Imager

Solar-induced fluorescence (SIF) is a proxy of ecosystem photosynthesis that often scales linearly with gross primary productivity (GPP) at the canopy scale. However, the mechanistic relationship between GPP and SIF is still uncertain, especially at smaller temporal and spatial scales. We deployed a ultra-hyperspectral imager over two grassland sites in California throughout a soil moisture dry down. The imager has high spatial resolution that limits mixed pixels, enabling differentiation between plants and leaves within one scene. We find that imager SIF correlates well with diurnal changes in leaf-level physiology and gross primary productivity under well-watered conditions. These relationships deteriorate throughout the dry down event. Our results demonstrate an advancement in SIF imaging with new possibilities in remotely sensing plant canopies from the leaf to the ecosystem. These data can be used to resolve outstanding questions regarding SIF's meaning and usefulness in terrestrial ecosystem monitoring. Estimating the rate of carbon uptake by vegetation across space and time remains a challenge. Solar-induced fluorescence (SIF), the emission of light by vegetation during photosynthesis, has recently emerged as a potential estimate of carbon uptake in many ecosystems and is observable from both satellites and ground-based sensors. Here we present results from a field campaign with a novel SIF instrument that creates images (akin to a photo) across a landscape, allowing for SIF measurements from individual leaves, plants, or areas of interest. We find that SIF retrievals from the imager correspond to seasonal variations in carbon dioxide fixation rates and leaf-level physiology relating to photosynthesis. We use this novel technology to improve understanding of SIF and carbon uptake across spatial and temporal scales. Novel imagery technology enables solar-induced fluorescence (SIF) acquisition across space and time SIF diurnal and seasonal variations correspond to carbon fluxes and environmental conditions Imaging capacity predicts leaf-level physiology across leaf, plant, and landscape scales