## 4 Discussion
### PlanetScope and MicaSense Intercomparability  
The discrepancies in the correlation between PlanetScope and MicaSense reflectance values, as highlighted by the low Pearson R\({}^{2}\) values across the spectrum, are largely due to the fundamental differences in their spectral responses. The two sensors are designed with different band specifications and sensitivities. The PS SSD sensor captures a wider range of wavelengths compared to the RedEdge-M sensor, which has narrower and more defined spectral bands. This mismatch in wavelength coverage and bandwidth is likely to lead to variations in the measured reflectance, particularly in regions of the spectrum where the two sensors do not fully overlap. In addition, differences in radiometric calibration procedures between the two sensors may further contribute to the observed discrepancies. These findings align with previous reports of MicaSense camera limitations, particularly, the underestimation of the reflectance values for reference panels and the challenges associated with sensor saturation [77] and band [78] mismatch. Consequently, direct comparisons between the two datasets should account for these inherent differences in spectral characteristics and calibration methods.  
When such variability cannot be resolved by addressing biases alone, incorporating ground-based surface reflectance measurements becomes critical. These measurements provide an objective reference to evaluate uncertainties and validate reflectance values from both satellite and drone data. For MicaSense, improvements in acquisition protocols, such as accounting for BRDF effects in the SfM workflow or correcting illumination-induced variability during flights, could reduce discrepancies. In contrast, PlanetScope benefits from being an Analysis Ready Data (ARD) product, with harmonized corrections for radiometry, geometry, and atmosphere. These preprocessing advantages ensure consistency, although validation using reference data remains essential.  
Furthermore, although [PERSON] et al. (2019) [79] reported radiometric uncertainties for PlanetScope arising from variations in acquisition times, additional challenges are presented by anisotropic variations related to the bidirectional reflectance distribution function (BRDF), as demonstrated by [PERSON] et al. (2021) [80]. Such directional effects are exacerbated by differences in acquisition timing between sensors, potentially further complicating the comparison between PlanetScope and MicaSense data. However, the observed consistency in PlanetScope's SuperDove data can be attributed to the atmospheric correction applied to harmonize the constellation. This harmonization process has proven reliable in comparison with other datasets, such as Sentinel-2 [81; 82], suggesting that while temporal and directional variations present challenges, the SuperDove's corrected data may mitigate some discrepancies when properly accounted for.  
Additionally, a comparative analysis of NDVI rankings between MicaSense and PlanetScope revealed consistent alignment in high-yield treatments, such as P(St) + N(i) and P(Bm) + N(om), where differences in NDVI ranks were minimal, typically within one or two ranks. However, mid-yield treatments, such as P(Bm) + N(o), exhibited larger discrepancies, with PlanetScope ranking these treatments higher by two to three ranks on average. This suggests that while PlanetScope is effective in tracking broad trends in crop development, particularly in high-yield scenarios, mid-yield treatments demonstrate greater variability. This variability in MicaSense data could be attributed to challenges in radiometric calibration, which may have affected its ability to accurately detect finer-scale variability induced by different fertilization strategies.