## 3 Currently Operational UAS Systems for SIF Retrieval
### \"Piccolo-Doppio\"--A Dual-Field of View (FOV) Dual Spectrometer System
Founded on the statements of the instrument's near-linear response to light intensity (when the generic non-linearity correction of the instrument is applied to the data in post processing) plus the etaloning stationarity in respect to the wavelength, [34] carried out laboratory experiments and presented two post-processing techniques for the etaloning correction for any system using QEPro spectrometers:  
1. 'By reference': employing etaloning correction factors obtained from the division between the measured spectra of a calibrated light source and the known outputs per wavelength. The factors were applied to tungsten halogen readings at 20 levels of intensity (Figure 2a). The instrument response was then convolved with the respective spectral measurements to obtain the spectrum with the etaloning effect corrected. A variance of \(\pm\)0.7% was detected (Figure 2b) and linked to the instrument non-perfect linear response. 2. 'By curve-fitting and residual interpolation': using correction coefficients obtained from the rounded residuals between actual and spline-smoothed reflectance at 17 levels of intensity of a tungsten halogen light source. A validation test performed with three additional levels of intensity demonstrated the efficiency of the method by reproducing a smooth spectrum (Figure 2c). Furthermore, the residuals of measured wavelengths were interpolated to enable the etaloning correction at unassessed ranges. The results obtained, differed by no more than 10 raw digital  
Figure 1: Piccolo-Doppio data processing workflow to obtain radiance. In step 2, an analogue data processing flow was developed in Python3. counts (DN) from the etaloning corrected spectra (Figure 2d), hence demonstrating higher performance in the correction of the effect compared with the'referencing' method. [PERSON] et al. [34] demonstrated a feasible route to solve the discrepancies in time between surface radiance and solar irradiance wavelengths collected from individual spectroradiometers. The authors clarified that the application of both methods for etaloning correction under field conditions is challenging and will necessitate to push the spectroradiometer dynamic range to the maximum. Later, the authors of [33] reported the feasibility to mount the Piccolo-Doppio onto the UAS DJI Matrice 600 with an interchangeable gimbal where the spectroradiometer could be installed together with an RGB or thermal camera (Figure 3a). The Piccolo-Doppio design was further used by [31] who recorded information at several altitudes (up to 500 m) and time points confirming the viability of the Piccolo-Doppio system to be mounted on aerial platforms. However, at the time of the present manuscript publication the authors had not completed the data processing. Additionally, a Piccolo-Doppio was also installed on a DJI Matrice 600 Pro [44] to monitor SIF in a mature oak woodland (UK) over a 30 m diameter free air CO\({}_{2}\) enrichment experiment [45]. A significant correlation of R\({}^{2}\) = 0.8821 (\(p<0.01\); Figure 3b) was found between UAS-based SIF and the incoming radiation, suggesting reliable variations of the SIF data retrieved with this system especially in a context where other approaches (e.g., eddy covariance) are not appropriate due to the scale of the treatments. Additionally, SIF information was useful to identify treatment effects and its relationship with environmental drivers. Furthermore, the spectral calibration and characterization of three spectroradiometers using a Piccolo-Doppio-like system design could be analyzed [46] by the implementation of two methodologies, using Ar and Ne lamps or a double monochromator respectively. The versatility of Piccolo-Doppio makes it practical to be used even on a ground platform mounted on a tractor, as demonstrated by [47] who estimated soy bean populations on early vegetative states under changing atmospheric conditions.