Evaluation of SIF retrievals from narrow-band and sub-nanometer airborne hyperspectral imagers flown in tandem: Modelling and validation in the context of plant phenotyping

Solar-induced chlorophyll fluorescence (SIF) can be used as an indicator of crop photosynthetic activity and a proxy for vegetation stress in plant phenotyping and precision agriculture applications. SIF quantification is sensitive to the spectral resolution (SR), and its accurate retrieval requires sensors with sub-nanometer resolutions. However, for accurate SIF quantification from imaging sensors onboard airborne platforms, sub-nanometer imagers are costly and more difficult to operate than the commonly available narrow-band imagers (i.e., 4- to 6-nm bandwidths), which can also be installed on drones and lightweight aircraft. Although a few theoretical and experimental studies have evaluated narrow-band spectra for SIF quantification, there is a lack of research focused on comparing the effects of the SR on SIF from airborne hyperspectral imagers in practical applications. This study investigates the effects of SR and sensor altitude on SIF accuracy, comparing SIF quantified at the 760-nm O2-A band (SIF760) from two hyperspectral imagers with different spectral configurations (full width at half-maximum resolutions of 0.1–0.2 nm and 5.8 nm) flown in tandem on board an aircraft. SIF760 retrievals were compared from two different wheat and maize phenotyping trials grown under different nitrogen fertilizer application rates over the 2019–2021 growing seasons. SIF760 from the two sensors were correlated (R2 = 0.77–0.9, p < 0.01), with the narrow-band imager producing larger SIF760 estimates than the sub-nanometer imager (root mean square error (RMSE) 3.28–4.69 mW/m2/nm/sr). Ground-level SIF760 showed strong relationships with both sub-nanometer (R2 = 0.90, p < 0.001, RMSE = 0.07 mW/m2/nm/sr) and narrow-band (R2 = 0.88, p < 0.001, RMSE = 3.26 mW/m2/nm/sr) airborne retrievals. Simulation-based assessments of SIF760 for SRs ranging from 1 to 5.8 nm using the SCOPE model were consistent with experimental results showing significant relationships among SIF760 quantified at different SRs. Predictive algorithms of leaf nitrogen concentration using SIF760 from either the narrow-band or sub-nanometer sensor yielded similar performance, supporting the use of narrow-band resolution imagery for assessing the spatial variability of SIF in plant phenotyping, vegetation stress detection and precision agriculture contexts.