## 5 Conclusions  
The results obtained from this study aim to provide a harmonization procedure that allows for expanding the availability of comparable surface reflectance data for the Mediterranean basin area. The analysis of surface reflectance products demonstrates a good level of agreement, but the conducted analyses and comparisons with existing studies in the literature have highlighted the potential of integrating the available products with site-specific transformation factors.  
Satellite data processing was conducted using open-source software GEE, a cloud-based platform that provides freely accessible surface reflectance datasets. The use of GEE made it possible to analyse and process the large geospatial datasets used in this study, which would have otherwise required significant computing and storage capacity. Working directly with the collections of the three sensors online through GEE's library eliminated the need to download satellite images separately. The ability to post-process entire image collections simultaneously, extract values, and apply harmonization coefficients using GEE's API makes the data used in this study easily analysable. Additionally, the use of atmospherically corrected products already available in GEE for all the sensors investigated facilitates the methodology's application even for users with limited experience in remote-sensing techniques. These characteristics ensure the reproducibility of the methodological approach and enable its widespread application to other studies in the Mediterranean basin area.  
The application of this experimental design encountered difficulties primarily due to the limited availability of disturbance-free images (clouds, shadows), necessitating an increase in sampling points and longer computational times, as well as a need for a reliable internet connection.  
The authors did not apply BRDF and haze corrections since the aim of the study was to develop band-wise correction factors applicable to a broad range of users. It is assumed that the application of such corrections could further enhance the results already obtained in this study. The future challenge will undoubtedly involve integrating these corrections into the proposed model and assessing their contribution.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Band** & **Mean Difference** & **RMSD** \\ \hline Blue & \(-0.0142\) * & \(0.0188\) \\ Green & \(-0.0132\) * & \(0.0197\) \\ Red & \(-0.0137\) * & \(0.0202\) \\ NIR & \(-0.0063\) * & \(0.0271\) \\ NIRa & \(-0.0162\) * & \(0.0374\) \\ SWIR1 & \(-0.0133\) * & \(0.0332\) \\ SWIR2 & \(-0.0142\) * & \(0.0188\) \\ \hline \hline \end{tabular}
\end{table}
Table 5: Statistical differences in surface reflectance between the OLI and ETM+ band values. Mean difference, and RMSD values for each pairwise band of the test set, comprising a total of 7692 data points. The asterisk (*) indicates the significance of the \(t\)-test, with a \(p\)-value < 0.05.  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Band** & **OLS** & **RMA** & **Chastain et al. Coeff.** \\ \hline Blue & \(-4.83\times 10^{-4}\) & \(-4.38\times 10^{-4}\) & \(0.0112\) * \\ Green & \(-3.51\times 10^{-4}\) & \(-3.00\times 10^{-4}\) & \(0.0022\) * \\ Red & \(-4.75\times 10^{-4}\) & \(-4.79\times 10^{-4}\) & \(0.0006\) \\ NIR & \(-2.15\times 10^{-4}\) & \(-3.24\times 10^{-4}\) & \(0.0216\) * \\ NIRa & \(-7.36\times 10^{-5}\) & \(-9.69\times 10^{-5}\) & \(-0.0061\) * \\ SWIR1 & \(-2.36\times 10^{-4}\) & \(-2.56\times 10^{-4}\) & \(0.0118\) * \\ SWIR2 & \(-2.49\times 10^{-4}\) & \(-2.94\times 10^{-4}\) & \(0.0146\) * \\ \hline \hline \end{tabular}
\end{table}
Table 4: Statistical differences in surface reflectance between the MSI and ETM+ band values after transformation functions. Mean difference (a) and RMSD values (b) for each pairwise band of the training set subjected to OLS/RMA regression model coefficients in this study and [PERSON] et al. (2019) transformation functions. The asterisk (*) indicates the significance of the \(t\)-test, with a \(p\)-value < 0.05.