Forests play a critical role in climate regulation by acting as carbon sinks, reducing atmospheric carbon dioxide and mitigating climate change. Early detection of low plant moisture levels is essential for monitoring drought conditions in forests. This study assessed whether Landsat-8 and Sentinel-2 remote sensing data could effectively detect level of water stress assessed using stem water potential (Psi s) in Aleppo pine (Pinus halepensis) and oak (Quercus coccifera) forests within the Mediterranean ecological zone. Two canopy cover densities were analyzed: pine (70-73% and 89-90%) and oak (77-80% and 94-95%). Ground measurements were conducted during the growing seasons from 2021 to 2024 and were synchronized with satellites overpasses. The long-term assessment (2021-2024) of oak and pine forests revealed Psi s values ranging from -0.2 to -3.4 MPa in oak and -0.3 to -3.0 MPa in pine, indicating sustained exposure to severe water deficit conditions and highlighting the urgent need for an effective forest health monitoring approach. Analysis of variance revealed that water stress significantly affected most spectral bands and vegetation indices, especially in the red-edge, near infrared and thermal regions, while canopy density mainly influenced shorter wavelengths. Regression analysis showed moderate correlations (R2 up to 0.67) between stem water potential and key indices (NDVI, NDWI, MI1, and LST/NDVI), with higher sensitivity under dense canopies. Stepwise and discriminant analyses confirmed that these indices effectively distinguished water stress levels (wet, moderately stressed, and severely stressed), achieving 64-71% classification accuracy, particularly in homogeneous oak and pine forests. Overall, the findings demonstrate that satellite-derived vegetation indices, particularly from Landsat-8 and Sentinel-2, provide reliable indicators of canopy water status and can effectively support monitoring of drought stress in Mediterranean forest ecosystems.