The identification of small habitat features embedded within forest ecosystems is a challenge for many wildlife inventory and monitoring programs, especially for those involving rock outcrop specialist taxa. Rock outcrops are often difficult to remotely detect in dense Appalachian hardwood forests, as most outcrops remain hidden under the forest canopy and therefore invisible when relying on aerial orthoimagery to pinpoint habitat features. We investigated the ability for light detection and ranging (LiDAR) point cloud data to identify small rock outcrops during the environmental assessment phase of a proposed management project on the Jefferson National Forest in Virginia, USA. We specifically compared this approach to the visual identification of rock outcrops across the same area using aerial orthoimagery. Our LiDAR-based approach identified three times as many rock outcrop sites as aerial orthoimagery, resulting in the field-verification of four times as many previously-unknown populations of green salamanders Aneides aeneus, a rock outcrop specialist amphibian of high conservation concern, than would have been possible if relying on aerial orthoimagery alone to guide surveys. Our results indicate that LiDAR-based methods may provide an effective, efficient, and low-error approach that can remotely identify below-canopy rock outcrops embedded within Appalachian forests, especially when researchers lack pre-existing knowledge of local terrain and the location of habitat features.