A Framework Based on Reference Data with Superordinate Accuracy for the Quality Analysis of Terrestrial Laser...

Area of Science:

• Geomatics
• Geodesy
• Remote Sensing

Background:

• Terrestrial laser scanning (TLS) offers efficient large-scale data collection.
• Combining TLS with other sensors in a multi-sensor system (MSS) further enhances efficiency.
• Point uncertainty in TLS data is variable, influenced by numerous factors.

Purpose of the Study:

• To present methods, infrastructure, and results for validating TLS and TLS-based MSS suitability.
• To establish backward modeling of uncertainty using high-accuracy reference data.
• To detail the calibration process for integrating laser scanner and laser tracker data.

Main Methods:

• Backward modeling of point uncertainty based on reference data with superior accuracy (factor of 10 better).
• Development of a suitable environment and infrastructure for validation.
• Calibration of targets for high-accuracy registration of laser scanner and laser tracker data in a common coordinate system.

Main Results:

• Demonstrated methods and infrastructure for validating TLS and TLS-based MSS.
• Quantified uncertainty in scanned points considering various influencing factors.
• Achieved high-accuracy registration essential for engineering geodesy.

Conclusions:

• The presented validation approach is suitable for assessing TLS and TLS-based MSS.
• Backward uncertainty modeling with superordinate accuracy is crucial for reliable data.
• The methods support engineering geodesy applications demanding high precision (sub-millimeter).