The increasing availability of laser scanning sensors across various platforms is revolutionizing multiple research fields, particularly archaeological surveys in densely vegetated areas. This is largely due to the sensors' ability to penetrate vegetation effectively. Notably, drone-based laser scanning has become more prevalent for this specific application with the miniaturization of sensors, offering higher resolution and point density, although at the cost of reduced endurance. A recent study focused on a coastal area near Rome, Italy, where dense vegetation hindered ground surveys. The area showed morphologies suggesting anthropic modifications, prompting a more detailed investigation using a DJI Matrice 300 drone equipped with a Zenmuse L1 LiDAR and GNSS/RTK positioning. The goal was to leverage the LiDAR sensor's high resolution and its capability to record multiple returns per pulse to better define these morphologies. However, the high density of vegetation posed challenges in filtering intermediate echoes to identify ground points. Despite testing various algorithms, the limited number of echoes often made it difficult to accurately classify the 'last echoes' as ground points. The ongoing study aims to develop the optimal combination of filters to produce a clean dataset of ground points without eliminating valid data. Preliminary results indicate that even in areas with shrub vegetation, the strength and number of laser echoes play a crucial role in detecting ground points effectively.

Drone-based laser scanning for improved archaeological surveys in heavily vegetated zones: A Roman coastline case study / Alessandri, L.; Baiocchi, V.; Guarnieri, A.; Ciardulli, A. M.. - (2025), pp. 838-842. ( MetroAeroSpace 2025 Naples (Italy) ) [10.1109/MetroAeroSpace64938.2025.11114655].

Drone-based laser scanning for improved archaeological surveys in heavily vegetated zones: A Roman coastline case study

Alessandri L.
;
Baiocchi V.
;
Ciardulli A. M.
2025

Abstract

The increasing availability of laser scanning sensors across various platforms is revolutionizing multiple research fields, particularly archaeological surveys in densely vegetated areas. This is largely due to the sensors' ability to penetrate vegetation effectively. Notably, drone-based laser scanning has become more prevalent for this specific application with the miniaturization of sensors, offering higher resolution and point density, although at the cost of reduced endurance. A recent study focused on a coastal area near Rome, Italy, where dense vegetation hindered ground surveys. The area showed morphologies suggesting anthropic modifications, prompting a more detailed investigation using a DJI Matrice 300 drone equipped with a Zenmuse L1 LiDAR and GNSS/RTK positioning. The goal was to leverage the LiDAR sensor's high resolution and its capability to record multiple returns per pulse to better define these morphologies. However, the high density of vegetation posed challenges in filtering intermediate echoes to identify ground points. Despite testing various algorithms, the limited number of echoes often made it difficult to accurately classify the 'last echoes' as ground points. The ongoing study aims to develop the optimal combination of filters to produce a clean dataset of ground points without eliminating valid data. Preliminary results indicate that even in areas with shrub vegetation, the strength and number of laser echoes play a crucial role in detecting ground points effectively.
2025
MetroAeroSpace 2025
3D point data; laser scanning; Remote sensing; Roman coastal areas; vegetation mapping
04 Pubblicazione in atti di convegno::04b Atto di convegno in volume
Drone-based laser scanning for improved archaeological surveys in heavily vegetated zones: A Roman coastline case study / Alessandri, L.; Baiocchi, V.; Guarnieri, A.; Ciardulli, A. M.. - (2025), pp. 838-842. ( MetroAeroSpace 2025 Naples (Italy) ) [10.1109/MetroAeroSpace64938.2025.11114655].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1757109
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