## 4 Discussion
Such conclusions are questionable because these two parameters are directly interrelated--burden represents the resistance of the rock mass to explosive energy, which in turn dictates the amount of energy (and hence explosive material) required for effective fragmentation and displacement. Ignoring this relationship leads to oversimplified and potentially misleading predictive models. Incorporating accurate burden values into predictive models remains a particularly challenging task. Figure 7 clearly illustrates the substantial variation in actual burden along the profile of a single blasthole. Traditional approaches that assume a constant burden along the entire hole length introduce significant errors in estimating the true rock resistance. Similar issues arise with the powder factor, which is typically calculated as an average across the entire blast pattern and does not account for localized variations in charge distribution, influenced by bench geometry or the presence of detached rock blocks. For blasting engineers responsible for the planning and execution of blast operations, it is essential to have access to tools that are both simple and effective--tools that allow for the rapid, high-resolution mapping of bench face geometry and the subsequent adaptation of explosive charge mass and design to actual field conditions. Only with such tailored design can flyrock throw be minimized effectively. It is also important to recognize that even the most sophisticated predictive models cannot replace the experience and local geological knowledge of a skilled blasting engineer. Such an expert, familiar with the specific characteristics of the deposit and its geological variability, can design blasting operations that are both efficient and safe. Therefore, the future of effective flyrock mitigation lies not only in the continued development of predictive tools but also in their intelligent and responsible application by trained professionals. At the same time, it should be emphasized that no tool currently offers complete assurance against the occurrence of excessive flyrock. One of the main challenges remains the lack of fast and reliable methods for detecting voids between the blasthole pattern and the face geometry. In this context, the precision of geodetic measurements and their integration with specialized blast design software become critical components in ensuring safety in mining operations. When analyzing only equipment-related costs, the use of UAV technology proves economically favorable compared to traditional surveying methods, such as laser total stations (based on average pricing in the Polish market). The purchase of a high-quality laser total station typically ranges between USD 40,000 and 55,000, with an additional software cost of approximately USD 4000-6000. In contrast, the cost of acquiring a UAV system with RTK functionality ranges from USD 5000 to 8000. Additional expenses include UAV operator training (approximately USD 500, valid for five years), annual insurance (-USD 200), and software licensing fees ranging from USD 200 to 1000 per month, depending on the software's capabilities. Considering average values, the total investment in UAV-based surveying becomes comparable to that of a total station after approximately 5-6 years of use, assuming no major equipment failures occur. Furthermore, operating a total station usually requires two personnel, while UAV data acquisition can be conducted by a single trained operator. The time required to survey the same section of a bench face is also significantly shorter with UAVs, resulting in greater operational efficiency and reduced labor costs. In summary, the integration of photogrammetric measurements, 3D modeling, and advanced blast design tools significantly enhances the reliability and safety of blasting operations. Future research should focus on hybrid approaches that combine real-time3D measurements with machine learning algorithms, especially in geologically complex environments or areas close to protected infrastructure.