The shape and structure of trees are important for understanding forests. They tell us which species are present, how good the habitat is for animals, and how much carbon the forest can store. But it is hard to measure tree structure using common tools like airborne LiDAR, which only gives a rough view of the forest from above. To get better data, this project uses detailed laser scans taken from the ground in three forest areas. These scans are used to create 3D models of individual trees, showing their shape in high detail. We then use these detailed models to better understand what airborne LiDAR can and can’t show—especially when it comes to the forest understory. We found that one part of the airborne LiDAR signal, the lower quartile of the point height distribution, matches well with the complexity of the understory. This means we can use airborne LiDAR more effectively to map forest structure.