## 5 Conclusions  
In this paper, we have investigated the possibility of reconstructing one or two of the 20 m resolution bands from Sentinel-2 using the remaining bands. The goal of the study was to assess the possibility of removing some of the current Sentinel-2 spectral bands for the next generations of similar satellites. The interest of working on band reconstruction is that the approach is independent of the application. The main rationale is, if a band can be reconstructed with errors which are within the radiometric requirements of the sensor, downstream applications can use a reconstructed band instead of a real measure. The main findings of the study are that, at the least, one of the bands among B5, B6, B7 and B8A could be removed from next generation sensors, as all of them can be reconstructed with small errors when the others are available. Removing two bands could be possible at the cost of slightly higher reconstruction errors. We have also shown that the estimation of a credibility interval for the predicted reflectances is possible and can therefore be used as a quality mask. However, this study has several limitations that have been clearly identified in section 4 and that would need to be addressed in the future. If the next generation of Sentinel-2 had one or several bands removed, one could argue that the approach presented in this work could not be applied, since the regression calibration (i.e., the neural network training) needs the target band. Several responses can be given to this argument. If the bands used as predictors remain the same in the new sensor, the regressions calibrated with the current Sentinel-2 data should be applicable. If the bands used as predictors for this study were not available in the next generation of satellites, one could constitute enough training data by using acquisitions from a hyperspectral mission such as CHIME [31]. The appropriate spectral bands (predictors and targets) could be generated using the relative spectral responses of the next generation of Sentinel-2. Finally, given the temporal revisit of Sentinel-2, it would be interesting to evaluate the possibility of having different bands in different satellites of the constellation, so that the band predictions could be temporally interleaved. For instance, with two satellites, one could imagine removing B6 in the A unit and removing B7 in the B unit. In this configuration, the reconstruction of B6 at a given date could use the other bands for this acquisition, as well as the most recent acquisition of the other satellite, for which B6 would have been observed. This kind of scenario would allow for interesting configurations where one satellite of the pair could have the SWIR bands absent. Indeed, the variance observed in Figure 13 could be highly reduced if the two SWIR bands for a previous date were available. Of course, for surfaces where the SWIR signature can change quickly during cloudy periods (snow falls), the impact of this kind of setting should be studied. Fortunately, available Sentinel-2 archive data allows that. Another interesting possibility of the approaches presented in this paper is the _addition_ of new bands, but only in some satellites of the constellation. On this topic, we should stress the comments on [32], as we did in Section 1.4: the fact that a particular phenomenon has a signature in a particular band does not mean that this same phenomenon cannot be detected by using a (nonlinear) combination of other bands. The results presented in this paper indicate that the question can be reversed. The attentive reader will have understood that many options are open to reduce costs and hardware complexity for the successors of the current Sentinel-2 system by leveraging spectral, spatial and temporal correlations of the observed surfaces through ground data processing. This work is just an example of what could be done by using the richness of the Sentinel-2 archives. We think that with the help of other scientists, further studies could be defined.