@misc{Pawlik_Marcin_The,
 author={Pawlik, Marcin and Nguy, Quynh Anh and Bernsdorf, Bodo and Rudolph, Tobias and Haske, Benjamin},
 howpublished={online},
 publisher={Zielona Góra: Oficyna Wydawnicza Uniwersytetu Zielonogórskiego},
 language={eng},
 abstract={This study explores the use of advanced drone technology with multiple sensors to improve the detection and mapping of fault zones. The goal is to validate a multifaceted approach using LIDAR, multispectral cameras, and thermal imaging, providing a comprehensive analysis of the Earth`s surface. LIDAR technology plays a critical role by creating high-resolution digital elevation models (DEMs) and digital surface models (DSMs).},
 abstract={These models offer detailed depictions of terrain topography, crucial for identifying subtle variations associated with fault lines. LIDAR`s ability to see through vegetation also aids in delivering a clear terrain representation, irrespective of surface cover. Multispectral cameras capture images across various wavelengths, enabling the analysis of vegetation health through indices like GNDVI, NDVI, MSAVI, and VARI.},
 abstract={These indices indicate geological disruptions, such as fault zones, since vegetation health often correlates with underlying anomalies. Thermal imaging adds another dimension by detecting minor temperature fluctuations on the ground`s surface. These variations can signal active faults, revealing friction or geothermal activities beneath the surface. To verify the sensor data accuracy, a site visit was conducted, comparing drone findings with actual soil profile samples.},
 abstract={This ground-truthing step is vital for confirming that remote sensing data reflects real-world conditions accurately. Overall, the study shows that a multisensorial approach using drones significantly enhances fault zone detection and analysis. This integrated method serves as a potent tool for geological research, aiding in understanding fault dynamics and contributing to natural disaster preparedness.},
 title={The Use of Multisensoral Drone Monitoring to Fault's Zones in Areas Affected by Mining Activities},
 type={artykuł},
 keywords={geomatics, multisensory UAV, geomonitoring, fault zone, mining activity},
}