CSF (Cloth simulation filtering) Algoritmasının Zemin Noktalarını Filtrelemedeki Performans Analizi

Abstract

In the production of digital models belonging to the earth, LiDAR technology stands out with its great advantages in terms of labor, time and accuracy compared to traditional methods. Processing LiDAR data consisting of an irregular point cloud is an important process for the numerical models we will create. In this process, filtering of raw LiDAR data is an important step. In open source and commercial softwares, there are many different filtering algorithms that determine ground points by filtering LiDAR data. When the studies are examined, the strengths and weaknesses of each algorithm stand out for different land surfaces. Each algorithm has different parameters in its content. In this study, the performance of the CSF (Cloth simulation filter) algorithm, which is available in an open source software that can be easily downloaded by the users for a challenging terrain surface consisting of dense forests and steep slopes, was tested. As a result of filtering with different parameter values, it has been revealed that the grid resolution parameter in the CSF algorithm is important in determining the ground point and determines more ground points with low values for a steep and inclined working area. In addition, when the field models produced as a result of filtering are examined, it is concluded that manual filtering is required for the objects that cannot be removed.