Study On Filling The Void Methods Of Airborne LiDAR Point Cloud Data

Airborne LiDAR(Light Detection and Ranging)has advantage of active remote sensing method,and a little dependence on the weather,moreover it is not easy affected by shadows and the sun angle,which can obtain a wide range of three dimensional information of terrain and features intensive sample point actively and directly.It is an important way to obtain high space-time resolution earth space information.As the demands to the Airborne LiDAR cloud point data because of the special advantages.However,inside Airborne LiDAR data often exist plenty of missing,which because of the following four aspects:the system failure、lacking of covering between stripe、it is because laser incident wave is aborted by high absorbent material that there is no exist corresponding data、the high block leads to missing data.This loss to follow-up point cloud data processing,analysis and application of the negative effect,so before we go further in the point cloud data processing,the lack of the data necessary to fill in,to ensure the integrity of the data.Thus,the rules of this article is based on grid storage discrete LiDAR data points,this paper proposes a convex hull based on data missing boundary isometric expand to determine effective influence area of the algorithm,this method can effectively draw on the data missing area is filled by the known data range.Based on different types of missing data using different interpolation methods to fill in the data of large area missing domain,the result by the method of cross check accuracy assess,identify the optimal and the appropriate filling scheme.