This report presents approaches developed within the FORWARDS project WP2 to bridge ground-based forest monitoring and remote sensing. Advances in proximal methods, including improved dendrometer measurements, meteorological integration, and terrestrial laser scanning, have contributed towards enhanced data quality and comparability. Physiological links between leaf-level traits and drone-based optical data demonstrate that vegetation indices (VIs) can capture drought impacts and recovery at the tree scale. Scaling analyses reveal limitations in applying optical indicators across spatial resolutions and forest types, though relationships between VIs and water availability still show promise at landscape scales. Satellite-based approaches, including temporal autocorrelation, can detect early resilience loss and flag forest areas at risk. Within such targeted risk areas, satellite-based VIs could be directly correlated with plot-scale measurements or integrated within models, for which we demonstrate examples. Machine learning models integrating data from the ground and gridded meteorological data, in future also remote sensing data, can provide complementary wall-to-wall insights, e.g. on tree water deficit. Together, these approaches support identification of forest vulnerability and prioritization of monitoring efforts across Europe