The OptD-multi method in LiDAR processing

Abstract

New and constantly developing technology for acquiring spatial data, such as LiDAR (light detection and ranging), is a source for large volume of data. However, such amount of data is not always needed for developing the most popular LiDAR products: digital terrain model (DTM) or digital surface model. Therefore, in many cases, the number of contained points are reduced in the pre-processing stage. The degree of reduction is determined by the algorithm used, which should enable the user to obtain a dataset appropriate and optimal for the planned purpose. The aim of this article is to propose a new Optimum Dataset method (OptD method) in the processing of LiDAR point clouds. The OptD method can reduce the number of points in a dataset for the specified optimization criteria concerning the characteristics of generated DTM. The OptD method can be used in two variants: OptD-single (one criterion for optimization) and OptD-multi (two or more optimization criteria). The OptD-single method has been thoroughly tested and presented by Błaszczak-Bąk ( Acta Geodyn. Geomater. 13/4 379–86). In this paper the authors discussed the OptD-multi method.

Reduction Method for Mobile Laser Scanning Data

“…Our previous method, which was called the Optimum Dataset method, is presented in Błaszczak-Bąk et al [17][18][19]. The OptD method removes those points which do not have relevant effect on the terrain characteristics from a practical point of view.…”

“…Obviously, it is best if the result is the optimal solution for the adopted criteria. It can be achieved by using the Optimum Dataset (OptD) method [17,18]. This paper is the continuation of our ongoing effort to develop an efficient data reduction and presents the modification of the Optimum Dataset method, with one criterion for MLS data captured by Velodyne sensors (called OptD-single-MLS).…”

The Optimum Dataset method – examples of the application

“…Only those points that are significant will remain, and the generated model will meet the predetermined parameters, for example, the accuracy of the obtained model. The method has been described in details and presented in [7,8].…”

“…Evidently, it is best if the result is the optimal solution for the adopted criteria. It can be achieved by using the Optimum Dataset (OptD) method [7,8] -the optimum method of reduction. This paper presents various variants of this method's applications.…”

Terrestial laser scaning in forest invetory based on OptD optimization method

“…The OptD is a optimization method described in [12][13][14] and used to reducing the number of points in the processing of Airborne Laser Scanning point cloud. Of course there is a lot of algorithms described in the literature [15][16] that allows to filter and reduce the point clouds obtained from laser scanning, but the proposed algorithm, in comparison to other methods, allows to obtain the optimal solution.…”