## 1 Introduction
A high frequency of data is a limitation in studies of climate change effects and land cover change, especially in particularly heterogeneous areas. The Mediterranean Basin region is a highly heterogeneous area that is very sensitive to the effects of climate change and anthropogenic activities, such as floods, wildfires, and deforestation [30; 31]. In particular, Mediterranean landscapes have some peculiar traits that make them unique compared to all other types of environmental landscapes and their geographical composition is characterized by high spatiotemporal heterogeneity of the vegetation pattern [32]. The nature and complexity of environmental ecosystems in the Mediterranean basin leads to the necessity for robust and integrated analysis to identify the changes in the landscape and apply efficient environmental monitoring. Several studies have leveraged the opportunity to harmonize satellite products from the Landsat-8 and Sentinel-2 constellations for investigations conducted in the Mediterranean basin region [33; 34; 35]. Few studies have integrated data from the Landsat-7 satellite in the Mediterranean basin area, focusing on specific areas [36; 37]. Moreover, the literature has highlighted the need to integrate these products for the estimation of biophysical variables, as calculating such variables using time-series data from non-appropriately-integrated sensors often leads to inaccurate estimations [38]. No study has been conducted on the entire Mediterranean basin area, considering the full variability of reflectance values. The purpose of this work is to address the needs identified in the literature and fill the gap regarding regional-scale studies in this specific area of the world. The aim is to propose a robust harmonization method that can be utilized for future research within this region. In this study, we sampled surface reflectance images from Landsat-7 ETM+, Landsat-8 OLI and Sentinel-2 MSI. The main objective of this study was to evaluate the differences between Sentinel-2 MSI, Landsat-8 OLI and Landsat-7 ETM+ surface reflectance data, and to propose cross-sensor transformation coefficients using different regression models (OLS and RMA) to facilitate the integration of these data sources for the entire area of the Mediterranean basin regions. This study represents an advancement compared to the existing literature as it aims to harmonize, for the first time, the surface reflectance products of ETM+, OLI, and MSI sensors specifically for the Mediterranean basin region. We compared pairs of ETM+, OLI, and MSI image observations and developed regression models to describe the differences between the surface reflectance values of the common spectral bands across these sensors. The potential of integrating reflectance values for the Mediterranean basin area was verified by applying different metrics of difference between the values of the models used in this study (OLS, RMA) compared to the coefficients reported in the literature. The comparison with harmonization coefficients proposed by [PERSON] et al. (2019) [39] and those proposed by [PERSON] et al. (2018) for the Harmonized Landsat-8 and Sentinel-2 (HLS) [40] data set was implemented to assess a site-specific approach for the harmonization procedure. This comparison will highlight the need for focused analyses that consider the unique characteristics and dynamics of the Mediterranean area. Finally, the impact of this comparison on the estimation of biophysical variables is shown by calculating the widely used vegetation index, the Normalized Difference Vegetation Index (NDVI).