Mapping forest structure, critical for assessing carbon stocks and fluxes, remains challenging with remote sensing. We propose a novel framework linking an individual-based forest model (FORMIND), which generates explicit 3D forest structures and dynamics, with a radar simulator (here used for TanDEM-X). We investigate radar coherence from simulated forests to predict aboveground biomass (AGB) across varying spatial scales, measurement noise levels, and successional stages. The framework is applied to the Barro Colorado Island (BCI) tropical forest, where we evaluate simulated coherence against TanDEM-X observations and invert canopy height, comparing the results with airborne laser scanning (ALS) data.<br />Results indicate a positive link between forest structure and interferometric patterns, with AGB prediction showing a clear dependence on spatial resolution. This novel approach offers a pathway to map forest structure by combining broad radar data coverage with an ecologically explicit forest model.