This thesis assessed the viability of using LiDAR-derived elevation data in accurately mapping and characterizing bouldery geomorphic features in a study area in the Allegheny Mountains. This study showed that the ground returns classification process conducted by the Canaan Valley Institute (CVI) for their property using the TerraScan software generally removed 5 to 10 m scale local topographic variability and bouldery landforms in creating the CVI classified ground returns data. In open areas, last returns elevation and intensity data were successfully used in this study to map bouldery landforms in the study area. Identifying and describing boulders under a tree canopy required a relatively reliable ground classification of LiDAR points. This study\u27s classifications conducted within Prologic LiDAR Explorer provided a more useful representation than the CVI classified ground data for mapping bouldery landforms and generalized rugged topography. Index overlay for likelihood of presence of bouldery landforms using supervised classified aerial imagery and LiDAR-derived parameters in a raster environment was explored as an alternative means of detecting bouldery landforms because hillshade imagery derived from CVI classified ground data were inadequate for mapping bouldery landforms