지상 LiDAR 자료처리 정확도 향상을 위한 자동 분류 기법 연구

In the midst of rising interest in building safety after the earthquake in Japan, one can assess building safety by analyzing the deformation behavior of a building. Before analyzing deformation behavior with terrestrial LiDAR data in three-dimensional coordinates based on object observations, one should classify and eliminate unnecessary data. This study set out to propose a methodology to automatically classify and eliminate vegetation, which contains unnecessary data in high frequency when measuring terrestrial LiDAR, and increase the accuracy of deformation behavior analysis.