Mining activities have a significant impact on the environment, and it is crucial for mining companies to restore the land after extraction and preserve the original landscape. Remote-sensing techniques, such as Structure-from-Motion and 3D laser scanners, have become widely used in mining for ground monitoring due to their accessibility and safety advantages. In this study, historical aerial optical imagery of a coal-mining site in León, Spain, was processed using SfM photogrammetry to analyze landscape changes from the beginning of the open-pit operation to the completion of land reclamation.
Two point clouds generated from open-access optical imagery were compared with a LiDAR point cloud from 2010. To ensure accurate georeferencing, ground control points were extracted from an additional LiDAR point cloud acquired in 2010. By comparing these reconstructions and conducting a comprehensive analysis of the site's evolution, the researchers identified a landfill and assessed the effectiveness of the mine reclamation works.
In recent years, remote sensing techniques have experienced a significant evolution and have become essential tools for monitoring, mapping, and understanding different environmental and man-made phenomena. These techniques enable the acquisition of information from a specific area in successive campaigns, which enables monitoring of different events and detection of movements in a study area. Among remote sensing techniques, Light Detection and Ranging (LiDAR) is the most used, providing a three-dimensional point cloud (3DPC) of the scanned surface. This geometric information can be used for characterization, evaluation, and mapping of susceptibility, as well as for monitoring and modeling of ground movements.
LiDAR system records the position, intensity, and time of the laser pulse, creating a 3D point cloud that represents the surface. This point cloud can be used to create highly accurate digital elevation models (DEM) and digital surface models (DSM) (Jaboyedoff et al., 2012).
Otherwise, Structure from Motion (SfM) technique, together with multiview-stereo (MVS) algorithms, also enables the 3D reconstruction of surfaces. This technique uses a set of overlapping images taken from different viewpoints to create a 3D model of the scene. The SfM technique uses the relative position and orientation of the camera in each image to determine the position of the 3D points. One of the main advantages of the SfM technique is that it is much more economical and manageable than LiDAR instrumentation. Additionally, SfM can be used to create 3D models of inaccessible areas or areas that are dangerous to access, making it an ideal technique for monitoring and mapping geohazards such as landslides, rockfalls, and volcanic eruptions (López-Vinielles et al., 2020; Sarro et al., 2018)
