Shrub volume is used to calculate numerous, essential ecological indicators in rangeland ecosystems such as biomass, fuel loading, wildlife habitat, site productivity, and ecosystem structure. Field techniques for biomass estimation, including destructive sampling, ocular estimates, and allometric techniques use shrub height and canopy widths to estimate volume and translate it to biomass with species-specific allometric equations. These techniques are timeconsuming, and pose challenges, including removal of plant material and training of observers. In this project we sought to expand techniques and methodologies for estimating canopy volume using two main techniques: drone imagery and additional allometric equations. First, we compared canopy volume estimates from field-based measurements with drone-collected canopy volume estimates for seven dominant shrub species within mountain big sagebrush (Artemisia tridentata subsp. vaseyana) plant communities in southern ID, USA. Canopy height and two perpendicular width measurements were taken from 103 shrubs of varying sizes, and volume was estimated using a traditional allometric equation. Overlapping aerial images captured with a DJI Mavic 2 Professional drone were used to create a 3D representation of the study area using structure-from-motion photogrammetry. Each shrub was extracted from the point cloud, and volume was estimated using allometric and volumetric methods. The volumetric method, which involved converting point clouds to raster canopy height models with 2.5 and 5 cm grid cells, outperformed the allometric method (R2 > 0.7), and was more reproducible and robust to userrelated variability. Drone-estimated volume best matched field-estimated volume (R2 > 0.9) for three larger species: A. tridentata subsp. tridentata, A. tridentata subsp. vaseyana, and Purshia tridentata. The volume of smaller shrubs (canopy widths <1 m) was slightly overestimated from drone-based models. Second, we created new allometric equations for eight shrubland species and span a range of site conditions using a sample of 631 shrubs of eight species at 13 sites in the Great Basin within the Sagebrush Steppe Treatment Evaluation Project (SageSTEP) monitoring network. This effort generated both generalized species-specific and site-specific biomass equations through linear regression models. This dual modeling approach offers users the flexibility to apply general species relationships or tailor biomass estimation based on geographical location or species distribution. Additionally, we provide biomass estimates within fuel size classes, enhancing the utility of these equations for future research and management applications in the Great Basin. Our equations are shared as R code and an excel sheet, allowing users to implement these equations. Our findings from these two experiments demonstrate that drone-collected images can be used to assess shrub canopy volume for at least five upland sagebrush steppe shrub species and support the integration of drone data-collection into rangeland vegetation monitoring. Further, by advancing the availability and precision of allometric equations for upland shrub species, our study contributes valuable tools for understanding shrub biomass dynamics in sagebrush shrubland ecosystems.