Terrestrial Laser Scanning for underground marble quarry planning: comparison of multi-temporal 3D point clouds

Nowadays, Terrestrial Laser Scanning (TLS) is being increasingly used in the field of geology and, among the others, in the planning of quarrying activity. This technology can be useful in underground quarries where it is difficult to acquire information related to the different morphologies and to model the excavation surfaces. In this context this technique can be useful in tackling various problems and facilitating a proper planning of quarrying activities in respect to safety. By generating clouds of points, three-dimensional laser scanning overcomes most of the limitations of traditional methods, rapidly supplying accurate and detailed geometrical information. TLS, in fact, has the capability of obtaining very large amounts of geometric data (millions of points) with sub-centimetric accuracy in short working times. Furthermore, in the last few years the time needed for acquiring such a data has been significantly reduced: only three years ago it could take hours for scanning a whole underground quarry, while today within few minutes you can get a dense 3D point cloud: the speed of data acquisition has passed from thousands to millions of points per second. This work aims to make a contribution to the existing body of knowledge in mining studies, presenting a multi-temporal point clouds comparison. The general purpose of this study is to propose an innovative and efficient methodology to investigate the morphological differences of extracted material in an underground marble quarry of the Apuan Alps (Italy), over a sample time frame of three years. In total three different field surveys were carried out using terrestrial laser scanning. In addition, GPS and Total Station were utilized to georeference the point clouds in an absolute reference system in order to be able to link all the different surveys. This process, named as registration, was carried out by using targets as constraints to apply a spatial transformation (3D roto-translation). After each scan, high resolution images were taken in order to color every individual point of the cloud through a texturing process. Later, the data acquired was processed using the open source CloudCompare software and, specifically, the M3C2 plugin which enables point clouds analysis. This approach consists in performing a direct comparison of point clouds computing distances in 3D and using search cylinders to find corresponding points between the two clouds. This method delivers accurate results and it has a much more straightforward workflow respect to other existing approaches. In fact, thanks to the direct comparison of point cloud and thanks to the absence of surface meshing or DEM generation, it does not introduce an error due to interpolation process. Lastly, it enables to perform change detection analyses with point clouds related to different temporal epochs. In this work the point clouds have demonstrated to be a powerful tool for three-dimensional characterization of underground quarrying activities. Moreover, the accuracy of the involved data, together with the rapidity of acquisition, make this procedure adaptable in several contexts and promising for the future. In addition, this method allows quarry workers to gain information about the morphological differences of extracted material and possible rock fall zones. Finally, allowing reliable evaluation of productivity, this approach can be used to correctly plan future excavation activities.