Funded by CAL FIRE’s First Health Program, the CSU’s Agricultural Research Institute, and the Joint Fire Science Program, the project, 3DForests, aims to evaluate the use of remote sensing techniques to rapidly and more accurately estimate aboveground biomass (AGB) for a range of tree species and estimate crucial fuels parameters to help validate or refine fuel treatment tools and fire behavior models across diverse California forests. Specifically, we use state-of-the-art terrestrial laser scanning (TLS) and a low-cost unoccupied aerial system (UAS), combined with modern data processing techniques, to acquire detailed measurements of 3D forest structures in coastal and southern Cascade forests of northern California. We asses the trade-offs in ease-of-use, speed, accuracy, cost-effectiveness, and comprehensiveness in estimating AGB and fuels parameters with TLS and UAS when compared to traditional field-based methods across a range of forest types. We consider how different approaches may be implemented by land managers and provide data related to the economic and technical hurdles for the adoption of these techniques.