# Suitability of Aerial Photogrammetry for Dump Documentation and Volume Determination in Large Areas
## 1 Introduction
In recent years, digital aerial cameras and appropriate software development have provided sensors with higher resolution, allowing the Earth's surface to be captured with detail-level improvement at the same flight height, respectively reducing the necessary number of images and thus flight time and cost of imaging [23]. The minimizing of fieldwork time, rapidity of photogrammetric data collection and processing, and high detail and accuracy of the terrain models generated by modern software currently take aerial photogrammetry forward as an exciting alternative in terms of quality and efficiency in comparison with terrestrial geodetic methods [24]. Unmanned aerial systems (UAS) are preferred for smaller-scale areas today, mainly because of their ease of use and low acquisition costs. [PERSON] et al. provided a template for the application of unmanned aerial vehicles (UAV) in mapping a river landscape [25]. Its outputs can also be applied to the mapping and documentation of quarries and landfills. [PERSON] [26], [PERSON] et al. [27], and [PERSON] et al. [28] evaluated the quality and accuracy of UAV photogrammetry data using RTK GNSS methods. Without GCPs (ground control points), they achieved a positional accuracy of 1-3 cm and height accuracy of 4-6 cm. [PERSON] addressed the quality of UAV-based DEM models affected by poor lighting conditions by comparing point clouds [29]. The filtering and classification of point clouds were dealt with by [PERSON] [30] and [PERSON] et al. [31]. The analysis of spatial solids approximated by a regular solid was applied by [PERSON] et al. [32]. Speed and morphology change using cross-section processing was implemented by [PERSON] [33]. [PERSON] et al. in their works also dealt with the issue of the volume of moved material of eroded banks in Svalbard. They studied the bedload transport of material in a glacial river (see discussion) [34; 35]. The current trend in photogrammetric processing is the SfM method. It can be used to process both terrestrial and aerial photogrammetric images [36]. In addition, there are many commercial and open-source software solutions [37]. Mapping using manned aerial systems is justified, especially for larger areas such as the tasks of investigating flood events [38], soil, gullies, shore erosion [39; 40], landslides [41], and volcanological surveying [42] or of analysing the slope stability of hard-to-reach or larger units [43; 44; 45]. In practice, in addition to creating DEMs and DSMs, it is also used to create updates to orthophoto maps and large-scale maps. Other types of sensors with their economic and technological benefits, such as thermal [46], multi, and hyperspectral cameras and Lidars [47; 48; 49; 50; 51; 52], can also be placed on airborne platforms. The AP method using manned aerial vehicles is currently competing with the cheaper and more operational UAS photogrammetry, but it effectively covers a smaller area and takes measurements from a lower altitude. This study aims to demonstrate that the use of AP achieves the required accuracy and detail of outputs. After validation on a test area of 1000 m\(\times\) 350 m, it can be assumed that usage in larger areas (open-pit mines, large landfills, etc. ), i.e., where the use of conventional rotary or fixed-wing UAVs would be less economical, will meet the requirements and needs. We also see a use in obtaining data on industrial heaps and dumps as a secondary product when mapping larger parts of the territory if carried out in the required time. Given the large range of the area of interest, the terrestrial measurement would force more days of shut down, which, at a frequent periodic measurement for the company operating in the area, represents an unacceptable loss of production. Therefore, from the available methods for performing the required measurements, the method of aerial photogrammetry has been chosen as likely the most appropriate way to fulfil the purpose of measurement.