Digital　elevation　model　(DEM)　is　one　of　the　most　important　information　that　can　be　derived　from　the　airborne　LiDAR　data.　However　in　areas　covered　by　dense　vegetation,　the　chance　of　laser　passing　through　the　canopy,　hitting　the　ground　and　back　to　the　receiver　is　limited,　thus　it　is　difficult　to　achieve　accurate　DEM　in　regions　with　dense　vegetative　covers　(trees,　shrubs　and　grasses).　We　considered　the　challenges　in　deriving　accurate　terrain　elevation　information　from　LiDAR　data:　identifying　areas　covered　with　dense　vegetation,　separating　LiDAR　point　clouds　into　ground　and　non-ground　returns,　interpolating　to　create　raster　surface　models.　A　case　study　in　the　semi-arid　mountainous　area　of　the　Northwest　US　shows　that　dense　shrub　caused　about　20　cm　DEM　error　in　vertical　accuracy,　in　line　with　similar　study　results　of　LiDAR　derived　DEM　from　dense　grass　areas.　Terrain,　cover　type　and　LiDAR　acquisition　parameters　(scan　or　incidence　angle,　point　density)　can　also　affect　accuracy.　©　2011　IEEE.