New optimum dataset method in LiDAR processing

Abstract

Until now, the optimization of a large dataset acquired by means of the laser scanning technology was understood as reducing the number of data and finding a satisfactory solution. Generating Digital Terrain Model on the basis of the reduced dataset does not always lead to desired results or previously planned goals. Therefore, it is important that the algorithm which reduces large dataset, could find the optimal solution for creating the model. The objective of this paper is to develop and test a new OptD method (Optimum Dataset) in the processing of Airborne Laser Scanning point cloud. The algorithm of this method can reduce the dataset in terms of number of measuring points for a given criterion, such as e.g. mean error of the Digital Terrain Model.