Iterative Closest Point Method for Integrating Terrestrial Laser Scanner and Airborne Laser Scanner Data in 3D Building Modeling

The development of geospatial technology has created a need for three-dimensional (3D) spatial data to meet various requirements. 3D models are considered capable of accurately representing the real conditions of an object, making them a vital tool in the planning process. This research aims to analyse the results of integrating point cloud data from Terrestrial Laser Scanners (TLS) and Airborne Laser Scanners (ALS) in creating a 3D model of the Rectorate Building-ITS. The results of data acquisition and processing from the Terrestrial Laser Scanner yielded a mean bundle error value of 0.004 meters, demonstrating a high level of accuracy. Additionally, the results from GCPs showed RMSE_x of 0.005 meters, RMSE_y of 0.013 meters, and RMSE_z of 0.009 meters. According to the ALS data, the average altitude difference is 0.037 meters, and the RMSE is 0.048 meters. The integration of TLS and ALS point cloud data enables the representation of the object's geometry as a whole, encompassing both its exterior shape and interior structure. The registration results show an RMSE_x value of 0.012 meters, an RMSE_y value of 0.015 meters, and an RMSE_z value of 0.008 meters, further confirming the high level of accuracy. This corresponds to a high level of accuracy and is based on the three-dimensional modelling standard of the Open Geospatial Consortium at LOD 4, with a precision of 0.200 meters. The geometric accuracy test results of the 3D model length comparison with the existing building length data show an RMSE value of 0,033 meters, further demonstrating the high geometric accuracy and meeting the Level of Detail (LOD) 4 accuracy standard.