Measuring change in underground environments is an important aspect of geological engineering. Recently, methods for using light detection and ranging (LiDAR) to measure change and convergence in tunnels and other underground environments have been demonstrated. To properly apply these new methods, it is important that an appropriate workflow is followed. The workflow proposed in this paper includes recommendations for choosing scan resolution settings and scan locations based on the level of change to be measured. The workflow follows through to the extraction of cross-section data for convergence measurement and back calculation.
The benefit of using light detection and ranging (LiDAR) for geological engineering applications has been widely demonstrated and discussed in the literature over the past ten years. For example, LiDAR can be used for rockmass characterization, discontinuity measurement, and change detection in underground spaces [1, 2]. As the number of applications of LiDAR scanning is increasing and its use is becoming more commonplace, it is important to establish best practices for both data collection and data management. More recently it has been shown that LiDAR data can be used for monitoring tunnel deformations and for change detection . To ensure LiDAR data collected from within tunnels is of high enough quality for all these applications, it is important that the appropriate amount of data is collected from the right locations at the correct resolution. Previous workflows have been suggested for different geological engineering applications of LiDAR scanning.  created a practical workflow for the scanning of large outcrops with long range time of flight laser scanners. The workflow proposed by  is very efficient for large scale feature extraction, but must be refined for application in underground environments, especially if scans are to be used for change detection.