## 6 Discussion  
Though the preliminary evaluation results indicate that the absolute errors of FASat-C with respect to RapidEye radiances and reflectances have been reduced, if the obtained values are compared to the errors prior to the cross-calibration, a validation process that includes cross-validation and in situ measurements should be performed over heterogeneous areas. This task will allow the evaluation of the new set of calibration coefficients over low reflectance targets, which were not represented in the sample due to the characteristics of the site. According to [PERSON] (2010) and [PERSON] et al. [PERSON] et al. (2010), low reflectances present a reduced SNR due to the increasing contribution of aerosols to at-sensor radiance. In relation to that topic, when assessing the uncertainty of an in-flight calibration, [PERSON] et al. [PERSON] et al. (2010) found that for low-reflectance surfaces, uncertainties were higher than for more reflective targets, suggesting that the quality of remotely sensed data of darker areas should be carefully studied. Furthermore, considering all of the previous factors and what has been analyzed by [PERSON] et al. [PERSON] et al. (2010), it must be added that most of the samples characterized by higher errors correspond to targets that are more sensitive to misregistration. In the present work, BRDF (Bi-directional Reflectance Distribution Function) effects have not been corrected; it is therefore not unlikely that some of the high absolute errors are a consequence of the anisotropic behavior of reflectance. Moreover, according to [PERSON] et al. [PERSON] et al. (2010) and [PERSON] et al. (2010), the calibration site presents some debris from weapon tests; this can be another possible factor influencing the response of some validation samples at the sub-pixel level. As atmospheric path radiance, diffuse radiance and related adjacency effects have not been removed during the cross-calibration process, some influence on the results can also be expected. In addition, areas from which evaluation samples were collected neither exhibit the lowest CV nor the highest degree of spatial autocorrelation; therefore, as stated by [PERSON] et al. [PERSON] et al. (2010), the adjacency effects would not be narrowed. This point may explain to some extent the higher standard deviations of MBE after cross-calibration, particularly for B1 and B2. Another important issue to consider is the fact that the discrepancies of FASat-C B3 and B4, with respect to RapidEye, are larger than the ones existing for B1 and B2; this can be explained by the differences in the shape and magnitude of the SRF at the wavelengths where absorption features are located. The O\({}_{2}\) absorption feature at 630 nm is in the limit of the FWHM of RapidEye's B3, although encompassed by B3 of FASat-C. At this specific wavelength, the responses of the two sensors differ by \(\sim\)50%. The next O\({}_{2}\) feature at 690 nm is by-passed by the RapidEye SRF, but not by FASat-C B3. In the case of the NIR band, the water vapor absorption feature at 760 nm is located where the difference in the RSR of the sensors is \(\sim\)25%. Besides, a H\({}_{2}\)O feature at 820 nm is over an area of the spectrum in which the RSR of FASat-C differs by 17%, in relative terms. In Figure 2, the RSR of both sensors and a MODTRAN (MODerate resolution atmospheric TRANsmission) [PERSON] et al. (2010) simulation of the transmittance for the mid-latitude summer atmosphere model are shown. The absorption features of the different atmospheric constituents can be observed. The transmittance presents a flat behavior within B1 and B2, while absorption features are noticeable for B3 and B4; thus, an influence of the overall shape of the RSR can be expected in this case. In accordance with [PERSON] et al. [PERSON] et al. (2010), the existence of other atmospheric features, non-detectable for the Hyperion \(\sim\)10-nm spectral resolution, affects the SBAF and the degree of agreement between Rapid and FASat-C B3 and B4.