Airborne LIDAR systems collect huge volumes of irregularly-spaced, three-dimensional point measurements of ground and non-ground objects scanned by the laser beneath the aircraft.  LIDAR measurements for terrain, vegetation, and buildings have to be separated in order to generate digital terrain models (DTM), digital canopy models (DSM), and 3-D buiding models.  We have developed a set of transparent and automatic filtering algorithms to classify ground and non-ground LIDAR measurements and a series of auxiliary tools such as thinning, tiling, and gridding the point data sets to assist the LIDAR data analysis. A graphics-based user interface has also been developed to facilitate the usage of algorithms and tools. We hope that the algorithms and software will provide researchers with the necessary tools to analyze LIDAR data and derive useful information in order to understand and model natural and human-induced earth surface processes and their changes.

Airborne LIDAR Data Processing and Analysis Tools (ALDPAT) project has been partially sponsored by National Science Foundation and National Oceanic and Atomspheric Administration. These tools are developed mainly for research purposes.