Obstruction detection comparison of small-footprint full-waveform and discrete return lidar

Abstract

Laser Radar, also referred to as lidar, has become widely available and is an established contributor to the military and intelligence community by providing precise elevation data using 3-dimensional measurements. The utilization of customized algorithms designed for lidar data exploitation provides the capability to determine corridors or gaps in areas of vegetation cover. These capabilities lend themselves as geospatial tools for mobility applications and tactical planning. This effort uses elevations derived from small-footprint (airborne) lidar surveys to create accurate surface models and corresponding canopy characterization maps. The canopy height models are based on elevation voxels above ground level and are used as input into a tree finding algorithm. Corridors under the canopy are then predicted using the obstruction identification technique and neighboring point characteristics. Path determination can also be performed using the obstruction maps and a modified A-star algorithm. A lidar survey over Camp Shelby, MS was chosen as the test case for the obstruction detection utilities as it provides fairly dense vegetation cover and interesting topographic features. The survey was completed using both a full-waveform lidar and a discrete return system which offers a coincident comparison of the obstruction methodology for differing data types. It is determined that the fullwaveform data provides a more complete and accurate assessment of the surface, the canopy and potential obstruction detection than the discrete return system.