While polarimetric interferometric SAR techniques provide a strong theoretical framework for forest height retrieval, their application using C-band Sentinel-1 data is challenging due to repeat-pass acquisition geometry and strong temporal decorrelation. In this study, we assemble a globally distributed dataset combining Sentinel-1 interferometric observations with spaceborne LiDAR forest height measurements from the GEDI and ICESat-2 missions. More than 1800 Sentinel-1 interferometric image pairs were processed and spatially matched with LiDAR observations across tropical, temperate, and boreal forest regions. Sentinel-1 Single Look Complex data were used to derive interferometric coherence and polarimetric–interferometric observables, enabling statistical analysis of their relationship with forest structural properties. The results reveal physical relationships between Sentinel-1 coherence and canopy height across multiple forest biomes, indicating that Sentinel-1 interferometric measurements, under nearzero spatial baseline conditions, retain measurable sensitivity to vegetation structure despite temporal decorrelation effects. These findings provide a conceptual basis for exploiting similar repeat-pass interferometric observations from new low-frequency SAR missions such as NISAR and upcoming ROSE-L for forest height mapping. In addition, the assembled dataset provides a global benchmark for developing and evaluating data-driven approaches for forest height estimation using Sentinel-1 observations.