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A UAV-GPR Fusion Approach for the Characterization of a Quarry Excavation Area in Falconara Albanese, Southern Italy

The characterization of a quarry site which is suitable for railway ballast aggregate production represents a big challenge for the mining industry. The knowledge of structural discontinuities within local geological materials is fundamental to guide mining operations, optimize investments, and guar...

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Bibliographic Details
Published in:Drones (Basel) 2021-06, Vol.5 (2), p.40
Main Authors: Saponaro, Annamaria, Dipierro, Giovanni, Cannella, Emanuele, Panarese, Antonio, Galiano, Angelo Maurizio, Massaro, Alessandro
Format: Article
Language:English
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Summary:The characterization of a quarry site which is suitable for railway ballast aggregate production represents a big challenge for the mining industry. The knowledge of structural discontinuities within local geological materials is fundamental to guide mining operations, optimize investments, and guarantee quarry security. This research work presents an innovative methodology for the subsurface investigation of a quarry excavation area down to a depth of about 50 m in Falconara Albanese, Calabria, Italy. The proposed methodological approach incorporates photogrammetry, drone technology, and GPR data acquisition and processing. Photogrammetry represents the first step for obtaining a 3D topographical model reconstruction of the whole quarry, helping to detail the acquisition approach and properly plan the subsequent drone survey. In particular, two 120 MHz antennas have been mounted on the drone and two profiles have been acquired above and across the quarry. Results show the presence of fractured material and demonstrate the applicability of the method for identification of areas that are more suitable for railway ballast production. The presented method is therefore capable of detecting subsurficial fractures at a quarry site by means of a relatively fast and cost-effective procedure. Results are achieved within the framework of an industry project.
ISSN:2504-446X
2504-446X
DOI:10.3390/drones5020040