## 4 Discussion
Application of the proposed coefficients significantly enhances the agreement between sensors, as demonstrated by the calculation of NDVI. The NDVI comparison obtained after the band correction proposed shows a slight improvement in mean difference value. It is important to underline that following the adjustment, the difference between the variables decreased to such an extent that it was not statistically significant. Finally, the ODR analysis shows a better agreement between the variables, although the RMSD does not significantly change its value. This observation could be attributed to the NDVI equation; it is obtained from the normalized difference between NIR and RED bands, which does not exhibit a higher degree of disagreement between sensor pairs. It is expected that more complex indices, incorporating other spectral bands, may reinforce these findings. The use of coefficients for sensor calibration is strongly recommended, not only for long-term historical analysis but also to increase data frequency, which is crucial in land cover change analyses, and to overcome issues caused by clouds and shadows [28]. Large-scale studies underline the importance and potential of site-specific harmonization models, as observed by [PERSON] et al. in Australia [25] and by [PERSON] et al. in China [26]. These studies reveal that variations between SR values due to sensor differences are significant when comparing different satellite products, and each region is characterized by distinct variations in these values. Similar findings have been confirmed in this study within the Mediterranean basin area, where discrepancies in SR values were bridged through appropriate site-specific harmonization coefficients. The validity and utility of these coefficients were confirmed through conducted statistical analyses and comparisons with coefficients already reported in the literature [39; 40]. As demonstrated in all the regional-scale studies presented in this work [25; 26; 39; 40], the integration of long-time-series reflectance values and numerous sampling points distributed throughout the area of interest enables the creation of a highly robust experimental design. This work, for the first time, integrates the SR values from the MSI, OLI, and ETM+ sensors for all overlapping years (2017-2021) using a dataset of sample points that encompasses a wide range of reflectance variability in the Mediterranean basin. This integration significantly reinforces the reliability of the harmonization method. Several studies conducted in smaller areas within the Mediterranean basin have emphasized the need to thoroughly evaluate potential integration between satellite products [63; 64]. Others, like [PERSON] et al. [38], have highlighted how differences in satellite reflectance values can adversely impact the assessment of time series for biophysical variables, often leading to an overestimation of them. However, previous workflow harmonization efforts have been limited to local scales, as seen in the work by [PERSON] et al. [65], resulting in coefficients with limited generalizability. This study addresses this literature gap by being the only work to harmonize different sensors within the Mediterranean basin and being the sole harmonization study at a regional scale in Europe. Given these insights, the process of harmonizing satellite products from the MSI, OLI, and ETM+ sensors in the Mediterranean basin, characterized by specific bioclimatic and biogeographic features, serves as an excellent test site for obtaining harmonization coefficients that encapsulate a unique variability, making it valuable for future research. In conclusion, the difference between the results obtained using the coefficients in this study and those proposed from the literature could be attributed to the sampling method. The work by [PERSON] et al. [40] on the HLS product was based on a global dataset with few sampled points in the Mediterranean Basin, while [PERSON] et al. (2019) [39] proposed a method based on points sampled in the CONUS region.