Reliability of Accuracy-Based Calibration in Quantifying Systematic Errors of Static LiDAR

The calibration of terrestrial laser scanners (TLSs) is crucial for ensuring high-quality 3D data. While system calibration often relies on precision-based methods without reference points, this study explores accuracy-based approaches incorporating reference values. TLS self-calibration was performed using point-based and line-based constraints with reference points established through close-range photogrammetry (CRP). The evaluation assessed calibration parameters (CPs), standard deviation, residuals, and correlation coefficient. Results show that the line-based approach improved accuracy by up to 60%, whereas the point-based method exhibited significant deviations. Consequently, while accuracy-based approaches can enhance TLS self-calibration, the line-based constraint is notably more effective.