Creating 3D Models Using Segmented Point Clouds

In the modern era, the protection and sustainable management of forest resources have become crucial. This study is aimed at improving three-dimensional modeling, which will help in simulating forest development and better management of forest resources. The main idea of the study is that segmented trees turn out to be of higher quality than modeling an entire forest area at once. To do this, the DBSCAN method was used during segmentation, and the Ball-Pivoting Algorithm was used to create three-dimensional models from a point cloud. As a result, segmentation improves the quality of three-dimensional models by removing unnecessary noise and interference, as well as processing smaller amounts of data.