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Article

Exploiting a Semi-Automatic Point Cloud Segmentation Method to Improve the Quality of Rock-Mass Characterization. The Cima Grappa Conservative Restoration Case Study

1
Department of Civil and Environmental Engineering, University of Florence, Via di S. Marta 3, 50139 Firenze, Italy
2
Geoapp s.r.l., Viale Spartaco Lavagnini 70/72, 50129 Firenze, Italy
*
Author to whom correspondence should be addressed.
Academic Editors: Wolfgang Kainz, Claudio Vanneschi and Matthew Eyre
ISPRS Int. J. Geo-Inf. 2021, 10(5), 276; https://doi.org/10.3390/ijgi10050276
Received: 10 February 2021 / Revised: 13 April 2021 / Accepted: 26 April 2021 / Published: 28 April 2021
(This article belongs to the Special Issue Advancements in Remote Sensing Derived Point Cloud Processing)
This paper presents results from applying semi-automatic point cloud segmentation methods in the underground tunnels within the Military Shrine’s conservative restoration project in Cima Grappa (Italy). The studied area, which has a predominant underground development distributed in a network of tunnels, is characterized by diffuse rock collapsing. In such a context, carrying out surveys and other technical operations are dangerous activities. Considering safety restrictions and unreachable impervious tunnels, having approached the study area with the scan-line survey technique resulted in only partial rock mass characterization. Hence, the geo-mechanical dataset was integrated, applying a semi-automatic segmentation method to the point clouds acquired through terrestrial laser scanning (TLS). The combined approach allowed for remote performance of detailed rock mass characterization, even remotely, in a short time and with a limited operators presence on site. Moreover, it permitted extending assessing tunnels’ stability and state of conservation to the inaccessible areas. View Full-Text
Keywords: laser scanning; conservative restoration, geometrical reconstruction; point clouds segmentation laser scanning; conservative restoration, geometrical reconstruction; point clouds segmentation
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MDPI and ACS Style

Mugnai, F.; Farina, P.; Tucci, G. Exploiting a Semi-Automatic Point Cloud Segmentation Method to Improve the Quality of Rock-Mass Characterization. The Cima Grappa Conservative Restoration Case Study. ISPRS Int. J. Geo-Inf. 2021, 10, 276. https://doi.org/10.3390/ijgi10050276

AMA Style

Mugnai F, Farina P, Tucci G. Exploiting a Semi-Automatic Point Cloud Segmentation Method to Improve the Quality of Rock-Mass Characterization. The Cima Grappa Conservative Restoration Case Study. ISPRS International Journal of Geo-Information. 2021; 10(5):276. https://doi.org/10.3390/ijgi10050276

Chicago/Turabian Style

Mugnai, Francesco, Paolo Farina, and Grazia Tucci. 2021. "Exploiting a Semi-Automatic Point Cloud Segmentation Method to Improve the Quality of Rock-Mass Characterization. The Cima Grappa Conservative Restoration Case Study" ISPRS International Journal of Geo-Information 10, no. 5: 276. https://doi.org/10.3390/ijgi10050276

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