Terrestrial plant ecosystems face tremendous pressure and stress due to climate change and anthropogenic activities, which alters plant function and productivity at different spatial and temporal scales [1]. A better understanding of such dynamics is a prerequisite for accurate monitoring and prediction of the global carbon cycle and securing food production. The integration of the earth observation data and ground-based measurements are highly applicable for rapid analysis of plant productivity and health. However, traditional reflectance based remotely sensed vegetation indices such as Normalized Differential Vegetation Indices (NDVI) are not sensitive to capture the short-term or diurnal changes in plant functioning [2], [3].

Solar-induced chlorophyll fluorescence (SIF), as a promising and novel product, has become an attractive method for estimating hourly plant productivity and for detecting pre-visual plant stress [4]–[6]. The inherent linkage of vegetation photosynthesis and SIF makes it possible to monitor crop yield and detect plant stress [7]–[10]. However, interpretation of the SIF signal at the canopy scale is still challenging due to the impact of plant canopy structure, especially between diverse forest and crop types, as well as different growth stages.