Alaska’s boreal forests are vast and remote, making it challenging to accurately monitor forest structure and conditions. Globally, these northernmost forests cover about 17 percent of Earth’s terrestrial surface and changes in them influence global carbon and water cycles. Hans-Erik Andersen, a research forester with the USDA Forest Service's Pacific Northwest Research Station and partners with NASA and American University have found ways to use three-dimensional measurements obtained from drone-based imagery to supplement traditional field data collected by technicians on the ground. The scientists bridged the scale gap between intensive but sparse plot measurements and extensive remote sensing studies by collecting forest inventory variables at the plot scale via an unmanned aerial vehicle (UAVs or drones), and a structure-from-motion approach. Structure-from-motion, also called photogrammetry, is a technique for measuring three-dimensional structures, such as trees, from stereo (overlapping) two-dimensional digital images, which in this study were collected via drones. By using this approach, the scientists were able to identify the dominant tree species, and more precisely estimate forest inventory quantities than is possible using airborne Light Detection and Ranging (LiDAR), another remote sensing technique collected from a manned aircraft typically flying at higher altitudes. Their study demonstrates the potential for analysis of boreal forest conditions at the scale of individual tree crowns. Beyond highlighting the value of UAV-based structure-from-motion for plot-level studies, their results hint at the possibility of three-dimensional photo-based analysis of forest structure across larger spatial extents by manned aircraft. It offers a promising approach to augment the spatial and temporal coverage of on-the-ground forest inventory measurements in boreal forests, enabling us to track changes in forest structure and composition from climate warming, insect outbreaks, and large-scale disturbances from fire and permafrost degradation.