Vegetation Filtering of a Steep Rugged Terrain: The Performance of Standard Algorithms and a Newly Proposed Workflow on an Example of a Railway Ledge

Point clouds derived using structure from motion (SfM) algorithms unmanned aerial vehicles (UAVs) are increasingly used in civil engineering practice. This includes areas such as (vegetated) rock outcrops or faces above linear constructions (e.g., railways) where accurate terrain identification, i.e., ground filtering, is highly difficult but, at the same time, important for safety management. In this paper, we evaluated performance of standard geometrical filtering (a progressive morphological filter (PMF), a simple (SMRF) cloth simulation (CSF)) and structural filter, CANUPO (CAractérisation de NUages POints), identification point cloud by SfM UAV imagery an area railway ledge adjacent face). The was both original position after levelling (its transformation into horizontal plane). poor results filters (total errors approximately 6–60% with PMF performing worst) mediocre result (approximately 4%) led us to combine these complementary approaches, yielding total 1.2% (CANUPO+SMRF) 0.9% (CANUPO+CSF). new technique could represent excellent solution high-density steep vegetated that can be well-used, example,