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		<identifier>oai:zbc.uz.zgora.pl:97276</identifier>
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<dc:title xml:lang="pl"><![CDATA[The Use of Multisensoral Drone Monitoring to Fault's Zones in Areas Affected by Mining Activities]]></dc:title>
<dc:creator><![CDATA[Pawlik, Marcin]]></dc:creator>
<dc:creator><![CDATA[Nguy, Quynh Anh]]></dc:creator>
<dc:creator><![CDATA[Bernsdorf, Bodo]]></dc:creator>
<dc:creator><![CDATA[Rudolph, Tobias]]></dc:creator>
<dc:creator><![CDATA[Haske, Benjamin]]></dc:creator>
<dc:subject xml:lang="pl"><![CDATA[geomatics]]></dc:subject>
<dc:subject xml:lang="pl"><![CDATA[multisensory UAV]]></dc:subject>
<dc:subject xml:lang="pl"><![CDATA[geomonitoring]]></dc:subject>
<dc:subject xml:lang="pl"><![CDATA[fault zone]]></dc:subject>
<dc:subject xml:lang="pl"><![CDATA[mining activity]]></dc:subject>
<dc:description xml:lang="pl"><![CDATA[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).]]></dc:description>
<dc:description xml:lang="pl"><![CDATA[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.]]></dc:description>
<dc:description xml:lang="pl"><![CDATA[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.]]></dc:description>
<dc:description xml:lang="pl"><![CDATA[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.]]></dc:description>
<dc:description xml:lang="pl"><![CDATA[tytuł dodatkowy: Prace z Inżynierii Lądowej i Środowiska]]></dc:description>
<dc:publisher><![CDATA[Zielona Góra: Oficyna Wydawnicza Uniwersytetu Zielonogórskiego]]></dc:publisher>
<dc:contributor><![CDATA[Kuczyński, Tadeusz - red.]]></dc:contributor>
<dc:date><![CDATA[2025]]></dc:date>
<dc:type xml:lang="pl"><![CDATA[artykuł]]></dc:type>
<dc:format xml:lang="pl"><![CDATA[application/pdf]]></dc:format>
<dc:identifier><![CDATA[http://www.zbc.uz.zgora.pl/repozytorium/Content/97276/ceer_2025_3_7_pawlik_the_use.pdf]]></dc:identifier>
<dc:identifier><![CDATA[https://zbc.uz.zgora.pl/repozytorium/dlibra/publication/109053/edition/97276/content]]></dc:identifier>
<dc:identifier><![CDATA[oai:zbc.uz.zgora.pl:97276]]></dc:identifier>
<dc:source xml:lang="pl"><![CDATA[Civil and Environmental Engineering Reports (CEER), no 35, vol. 3]]></dc:source>
<dc:language><![CDATA[eng]]></dc:language>
<dc:relation><![CDATA[oai:zbc.uz.zgora.pl:publication:109053]]></dc:relation>
<dc:rights xml:lang="pl"><![CDATA[Biblioteka Uniwersytetu Zielonogórskiego]]></dc:rights>
<dc:rights xml:lang="pl"><![CDATA[CC 4.0]]></dc:rights>
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