## 1 Introduction
In their research, the authors used NOAA/AVHRR and MODIS satellite data (Moderate Resolution Imaging Spectroradiometer) and three models for fire detection in satellite image pixels, namely the thresholding model, the contextual model, and the fuel mask model. A similar use of UAVs for detecting underground coal fires is discussed in [42]. In this case, UAVs were equipped with gas sensors and a method was developed to evaluate the rank of a burning coal seam based on gas coefficients. The obtained characteristics allow for calculating the combustion temperature, burn rate, and theoretical oxygen demand. This, in turn, helps estimate the rate of fire progression, the energy content of the burning coal, and better planning of firefighting and evacuation operations. Another popular area of application for image processing and drones is the assessment of rock fragmentation after blasting. Ensuring an appropriate degree of rock fragmentation post-blasting directly influences the efficiency of subsequent mining and processing operations. The authors of [43] conducted laboratory-scale studies aimed at evaluating the benefits of using UAVs in this area. The results were compared to conventional methods involving manual data recording by personnel. The use of UAVs allows for significantly improved temporal and spatial resolution of data due to enhanced camera quality, better camera perspective relative to the muck pile, and the automation of data acquisition and processing. In their subsequent work [44], the authors explained several factors affecting the quality and informativeness of the collected data. In another article [45], the authors presented a method for identifying factors contributing to stability problems and extraction challenges in headings with complex geometry in a gold underground mine utilizing sublevel stoping. Since access to the heading was impossible, the use of UAVs provided an opportunity for scanning. The studies demonstrated that UAVs can be employed to make critical decisions regarding operational continuity in any excavation and to calculate pillars and support elements. UAVs have also found practical applications during procedures related to mine closure and subsequent reclamation efforts. For instance, in [46], a UAV solution was described for monitoring water quality in pit lakes during closure, a requirement frequently mandated by regulatory authorities for mining companies. Traditionally, water samples are manually collected by personnel from boats; however, many sites are inaccessible due to prior damage or pose significant health and safety risks. The authors proposed a solution wherein optimal locations and depths for sampling are determined based on conductivity-temperature-depth (CTD) measurements, along with the minimum number of samples and the physical condition of the pit lake. The proposed UAV solution is equipped with a 2 L water sampling device capable of reaching depths of up to 120 m. Another example of UAV imagery application for supporting reclamation documentation involves the creation of detailed land cover maps, as described in [47]. A limestone quarry was chosen as a case study, where a visual inspection was conducted to assess the development of vegetation, soil cover, and geomorphological features of the area. According to the authors, the inspection of a 10-hectare area took 2 h, while the total time required for data processing was 2 working days. This timeframe is significantly shorter than that of standard methods. Moreover, UAV images provide a much greater level of detail. In [48], drones were utilized to monitor areas affected by acid mine drainage (AMD), exemplified by the reclamation of the Sokolov waste dump in the Czech Republic, where significant amounts of AMD minerals are observed. Mining waste was analyzed for pH, X-ray fluorescence (XRF), and reflectance spectroscopy. The studies demonstrated that UAVs offer a fast, non-invasive, and cost-effective method for monitoring post-mining landscapes.