From the Ground to Space: Using Solar-Induced Chlorophyll Fluorescence to Estimate Crop Productivity

Timely and accurate monitoring of crops is essential for food security. Here, we examine how well solar-induced chlorophyll fluorescence (SIF) can inform crop productivity across the United States. Based on tower-level observations and process-based modeling, we find highly linear gross primary production (GPP):SIF relationships for C4 crops, while C3 crops show some saturation of GPP at high light when SIF continues to increase. C4 crops yield higher GPP:SIF ratios (30-50%) primarily because SIF is most sensitive to the light reactions (does not account for photorespiration). Scaling to the satellite, we compare SIF from the TROPOspheric Monitoring Instrument (TROPOMI) against tower-derived GPP and county-level crop statistics. Temporally, TROPOMI SIF strongly agrees with GPP observations upscaled across a corn and soybean dominated cropland (R-2 = 0.89). Spatially, county-level TROPOMI SIF correlates with crop productivity (R-2 = 0.72; 0.86 when accounting for planted area and C3/C4 contributions), highlighting the potential of SIF for reliable crop monitoring. Plain Language Summary Crop monitoring is essential for ensuring food security, but reliable, instantaneous production estimates at the global scale are lacking. The monitoring of crop production in a changing climate is of paramount importance to sustainable food security. Accurate estimates of crop production are dependent on adequately quantifying crop photosynthesis. Our paper demonstrates that solar-induced chlorophyll fluorescence (SIF), an emission of red to far-red light from chlorophyll is highly correlated with crop photosynthesis. We show that a new high spatial resolution satellite SIF data set is highly correlated with crop productivity in the United States, which is benchmarked by the United States Department of Agriculture county-level crop statistics. These results will improve the understanding of crop production and carbon flux over agricultural lands, as well as provide an accurate, large-scale, and timely monitoring method for global crop production estimates.