New mining and exploration projects have revived across Europe with an increasing demand for critical raw materials driven by the energy transition and unstable political conditions. Hyperspectral imaging proves to be an excellent tool for quick and efficient non-invasive mineral exploration. By mounting hyperspectral- and LiDAR sensors on drones and other robots, inaccessible and dangerous areas can safely be mapped for geological information. With increasingly deeper and more hazardous underground mines, a robot-aided
hyperspectral mineral exploration method in underground environments is needed. This study configures a Cubert X20P hyperspectral camera (VNIR) and VLP16 LiDAR on the versatile Boston Dynamics Spot robot, creating a multi-sensor robotic platform for data acquisition in underground mining environments. A data workflow is proposed and applied to the granite greisen rocks of the Zinnwald/Cinnovec mine (Germany). Combining hyperspectral and geometric data provides unique 3D hypercloud results interpreted for mineral
and structural features. Hyperspectral analysis successfully identifies iron and clay minerals along with multiple vein and fault structures. A remote mineral exploration method in underground mines significantly improves safety by keeping the operator away from hazardous areas. The proposed platform and workflow show potential to contribute to underground mineral exploration, especially if future improvements in data quality and autonomous capabilities are made.

The growing importance of rare earth elements (REEs) in sustainable technologies necessitates anefficient assessment of potential resource targets within the European Union. Traditional analyticaltechniques for REE determination have drawbacks like destructive and time-consuming samplepreparation, but hyperspectral imaging (HSI) and laser-induced fluorescence (LiF) offer promisingalternatives. This project aims to use a combined HSI and LiF method to qualitatively characterizeREE mineralization and alteration in drill core samples from the Storkwitz deposit, Germany. The goal is to develop a transferrable mapping approach for REEs, while enhancing our understanding of the Storkwitz deposit. It aims to check the robustness of HSI conducted across the extendedwavelength range as a tool in effectively characterizing the lithologies associated with REEmineralization in the Storkwitz breccia. It also tests if the combined HSI-LiF can provide newinsights into the presence of REEs and its associated minerals in the Storkwitz breccia.The proposed workflow involves acquiring hyperspectral data of the Storkwitz drill core and blocksections in three wavelength ranges (VNIR-SWIR, MWIR, and LWIR). Automatic and manualendmember extraction is performed on the smaller subsection of data to create spectral libraries,which are then used for spectral unmixing and mapping of the entire hyperspectral dataset toidentify lithologies. LiF is used to identify and map rare earth elements (REEs) in selected REErichzones identified from the hyperspectral data.The results indicated that the Storkwitz Breccia is primarily composed of ankerite in the matrix,along with minor amounts of white mica, clay, iron oxides, and REE-fluorcarbonates. The brecciacontains different clasts, including granitoid clasts rich in orthoclase and quartz-albite-biotite, aswell as carbonatitic clasts dominated by ankerite, dolomite, and ankerite-calcite. The breccia alsounderwent four alteration phases, including fenitization, biotite alteration, white mica-clayalteration, and ferric alteration. Laser-induced spectroscopy confirmed the presence of REEs, withapatite and REE-fluorcarbonates, particularly bastnäsite, being the main REE-bearing minerals.The specific REEs identified include Nd3+, Sm3+, Pr3+, and possibly Eu3+. The comprehensiveworkflow combining hyperspectral imaging and laser-induced fluorescence spectroscopy provedto be a successful approach for characterizing lithologies and mapping rare earth elementmineralization in the Storkwitz breccia. The study opens up new possibilities for efficient REEexploration in similar geological settings, providing valuable information for geological loggingand interpretation.

In the former lignite mine "Robertshall" near Hamburg damage to the surface was caused by the collapse of underground cavities originating from old mine workings of a lignite mine which had been in operation between 1920 and 1922. During the investigation of the subsurface by drilling it was noticed that the existing mine plans are incomplete.
If mine plans are missing or incomplete, the risk to protected assets at the surface due to mining damage can often only be reliably assessed by means of indirect methods such as geophysics in reasonable combination with drilling. Within the scope of this work the extend of room-and-pillar caving at the “Robertshall” deep lignite mine was determined by geophysical methods. Subsequent backfilling and securing of the old mine workings are the goals of this exploration.
The simultaneous application of several methods on the selected test profile is not only intended to increase the reliability of the results, but also to gain experience as to which methods are best suited for routine detection under the given geological and mining conditions. The geophysical measurements are supplemented by an evaluation of historical data.
The results of geophysics have led to the prompt and reliable discovery of many drifts that were not included in the mine plan. Compared to the conventional approach of exploration by drilling, the application of seismic measurements saves time and costs.
The securing measures could be carried out by the responsible parties and the desired securing success has been achieved so that no further movements of the ground surface are to be expected.

Measuring and analyzing the tunnel deformation through convergence measurements and cross-correlation with geological mapping is essential for understanding and controlling tunnel stability, worker safety and predicting failure zones. In order to achieve this, a new device, the so-called GroundProbe GML is tested and analyzed in this study. Currently, the deformation in the Kristineberg mine is measured through conventional techniques, such as the tape extensometer, that are labor intensive and time-consuming. On top of that, the geological mapping is done by visual inspection by experienced geologists. There is no system in place that correlates the geological setting to the deformation of the tunnels. This research aims to explore the possibility to quantify tunnel wall convergence and correlate the movement to geological circumstances. An accuracy analysis is performed, to identify the accuracy of the Light Detection and Ranging (LiDAR) technology in comparison to conventional techniques. This analysis is conducted in both a controlled (above-ground) and an uncontrolled (underground) environment and focuses on the use of different targets, i.e. prisms or reflectors, and the difference between continuous and periodic measurements. The fresh rock surfaces are also mapped by means of geological LiDAR data as well as Red-Green-Blue (RGB) image analysis and this is correlated with tunnel wall convergence. This is done to increase the understanding of the impact of the geological setting on the tunnel wall convergence.
The accuracy presented by GroundProbe of _3 mm for periodic measurements is difficult to achieve in an underground environment with mining activity. Especially the deformation of measurement points that are at a more oblique angle to the scanner prove to be difficult to assess. The geological LiDAR data can be used to distinguish different rock types and geological features with limited subjectivity. The transition zones from one rock type to the other become clearly visible from the geological LiDAR data. Additionally, geological features such as joints can be identified when combining LiDAR data with RGB image analysis. The primary promotor of tunnel wall convergence is the hanging wall that pushes down on the foot wall in combination with non-uniform waste rock areas, that are for example split into two sections by a joint. In a tunneling environment where mining activities are conducted, such as the application of shotcrete, scaling, blasting and leveling of the floor, periodic measurements with a LiDAR set-up on a tripod are difficult. One of the main limitations is the absence of stable reference points that the LiDAR scanner uses to determine its XYZ-position. The oblique angle can also be a limiting factor, measurement points closer to the LiDAR scanner provide more reliable results. For continuous measurements however, this proves to be less relevant because the repositioning error can be omitted. The LiDAR scanning technology has the potential to be used as geological mapping tool based on the varying reflectivities of different rock types. By combining LiDAR technology with RGB image analysis, a more thorough understanding of the geological setting can be obtained. By relating this understanding to the quantification of the tunnel wall convergence, this technique can be used to correlate the geology to the movement of the rock mass.

Over the last decade, interest in deep-sea mining of Polymetallic Nodules (PN) has reignited. It is driven by an increasing demand of metals that are critical for the digital economy and modern technologies such as batteries. Methods for resource estimation of PN are known and commercially available. There is however no standard method of a planning a deep-sea mining operation. This is an essential step to define mineable reserves. To address this problem, an existing concept has been applied in this thesis. This planning concept was inspired by agriculture and subdivides a mining license area into large scale mining sites, which are in turn subdivided into smaller, continuouslymineable areas calledmining fields. The subdivision is illustrated in figure 1. The contribution of this thesis is the development of a methodology for this concept. The concept was applied to a framework based upon a license area in the Clarion-Clipperton Zone (CCZ) in the Pacific Ocean. The mining will be done using a Nodule Collector (NC), which is a self-propelled machine that continuously gathers PN on the ocean floor and transports them upwards to a vessel at the ocean surface. Certain areas are deemed constrained by slopes or nodule types. Mining sites wherein the NC will operate were outlined within the license area using those constraints and Nodule Abundance (NA).Within the mining sites, a new metric was introduced for assessing the mineability for the NC: the Straight-Line Distance (SLD). The next step down from mining sites are the mining fields. The operation of the NC within them is approximated by two different driving patterns. Different field shapes are also analyzed, along with the impact of obstacles inside the field. Different methods of creating fields inside the mining sites were considered. The procedure relied upon the SLD to define the boundaries between fields. Two sets of field are created: with elongated shape and compact shape. The best set of fields was selected using the approximation of NC operation. Lastly, a method for determining the sequence of fields is developed that uses a Genetic Algorithm (GA) as optimization method. It takes into account constraints for mining rate, operational hours, nodule targets and travelling time. The methods outlined in this thesis are flexible and can be applied in a variety of circumstances. The selection of mineable areas turns out to be the must crucial step. The subsequent delineation of mining fields and sequencing does not make or break the profitability of the operation, although they are essential steps for the definition of mineable reserves.

Site-specific calibration of laser induced breakdown spectroscopy (LIBS) analysis can be achieved by presenting known geological sample data to update algorithms, therefore improving analysis of unknown samples post-calibration. The goal of this project is to optimise drill core analysis by LIBS for samples from Kittilä gold mine. In total 227 samples have been produced and analysed with a range of analytical techniques to build a comprehensive, site-specific reference library. The data from these analyses has been input into the reference library and utilised by algorithms for spectral peak identification during LIBS analysis of bulk drill core material. The semi-quantitative and quantitative data of 40 Kittilä samples has been used as a comparison to ICP-AES data used by the mine. The Kittilä powders were used to produce 39 pellets, each representative of a section of drill core of which the ICP-AES and TXRF data was known. The pellets were scanned by LIBS and the data then compared to the known data. LIBS showed strong correlations (>0.75) with ICP-AES data for As, Cr, Cu, Fe, Mn and S, poor correlations were seen for Pb and Co, however these can be explained by issues related to ICP-AES. LIBS pellet data proved strongly competitive as 5/9 elements displayed stronger correlations between LIBS and ICP-AES than TXRF. Subsequently, the successful scanning of drill core boxes directly has proven that calibration can increase the speed with which the bulk material can be effectively analysed.