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  5. Integrated UAV-Borne GPR and LiDAR for Investigating Slope Deformation Processes: The Melizzano Case Study (Southern Italy)
 
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Integrated UAV-Borne GPR and LiDAR for Investigating Slope Deformation Processes: The Melizzano Case Study (Southern Italy)

Journal
DRONES
ISSN
2504-446X
Date Issued
2026-04-28
Author(s)
Famiglietti, Nicola Angelo  
Istituto Nazionale di Geofisica e Vulcanologia (INGV), Sezione Irpinia, Grottaminarda, Italia  
Massa, Bruno  
DST Unisannio
Memmolo, Gaetano  
DST Unisannio
Testa, Giovanni
Memmolo, Antonino  
Istituto Nazionale di Geofisica e Vulcanologia (INGV), Sezione Irpinia, Grottaminarda, Italia  
Vicari, Annamaria  
Istituto Nazionale di Geofisica e Vulcanologia (INGV), Sezione Irpinia, Grottaminarda, Italia  
DOI
10.3390/drones10050331
Abstract
Investigating slope deformation in densely vegetated or remote areas is a major challenge for slope stability assessment. This study introduces and validates an integrated UAV-borne low-frequency Ground Penetrating Radar (UAV-GPR) and LiDAR methodology to characterize an unstable slope in Melizzano, Southern Italy. Radar data were acquired along an east–west transect at ~1 m above ground level, while high-resolution LiDAR were used to generate a detailed Digital Terrain Model for topographic correction and geomorphological analysis. The processed radargram images subsurface features down to ~15 m, revealing a laterally continuous high-amplitude reflector at ~10 m, interpreted as a key main sliding surface. Chaotic reflections above this interface indicate heterogeneous deposits associated with gravitational deformation, while more homogeneous reflections below correspond to stable geological units. The geometry of the reflector suggests a compound landslide mechanism. Borehole data validate the geophysical interpretation, showing depth discrepancies lower than 2 m. The integration of UAV-GPR and LiDAR enables a reliable correlation between surface morphology and subsurface structures. This non-invasive, spatially continuous approach provides an effective framework for subsurface characterization and for improving the interpretation of landslide geometry and internal structure in challenging environments. This study demonstrates the capability of low-frequency UAV-borne GPR to detect deep-seated sliding surfaces (>10 m) in vegetated environments when integrated with high-resolution LiDAR topography.
Subjects

UAV-GPR

UAV-LiDAR

slope deformation

drone geophysics

sliding surface detec...

subsurface imaging

File(s)
Main Article: drones-10-00331 (1).pdf (2.24 MB)
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