Alignment and 3D georeferencing of tunnel coaxial hyperspectral scanning system data for mine drift exploration

Remote sensing using light detection and ranging (LiDAR) and hyperspectral imaging is widely applied in underground exploration for non-contact detection and mapping of subsurface features, particularly in mining environments. This study presents a methodology for alignment and 3D georeferencing using the tunnel coaxial hyperspectral scanning system (TCHSS), which employs a rotating sensor head integrating a hyperspectral camera, 2D LiDAR unit, and inertial measurement unit (IMU). By applying the principles of sensor-based orientation estimation in a local reference frame, exterior orientation parameters for each hyperspectral scan line were derived as a composition of IMU-based attitude data and LiDAR-based geometric data. A multi-stage protocol was implemented to correct system-induced geometric errors, including systematic lever-arm offsets and quantified boresight misalignments. The methodology was validated in an ilmenite (Fe-Ti-V) mine drift, where 20 scan sessions were registered into a continuous 3D hyperspectral point cloud, achieving a mean distance error of 86.44 mm relative to a reference 3D LiDAR model. Results demonstrate that the proposed approach generates geometrically coherent 3D models suitable for semi-quantitative applications, such as geological mapping and mine reconciliation, providing a technological foundation for fully automated underground exploration.