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EXTENDING 3D QUALITY MODELLING FOR EARTHQUAKE-DAMAGED STONE MASONRY WALL: COMBINED DIGITAL MODELS FOR BUILDING ARCHAEOLOGY

Authors :
Mattia Previtali
Fabrizio Banfi
Angelo Giuseppe Landi
Raffaella Brumana
Chiara Stanga
Source :
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XLVI-M-1-2021, Pp 721-728 (2021)
Publication Year :
2021
Publisher :
Copernicus Publications, 2021.

Abstract

The paper proposes an approach for defining a generative modelling process of complex objects and their sharing. The case study is the Stronghold of Arquata del Tronto, a monument of extraordinary historical, cultural and landscape value, damaged by the earthquake in 2016. The first step has been data acquisition on a geometrical level, through laser scanner and UAV photogrammetry, and on a historical level, through archival research to understand construction phases and transformations. The Stronghold was probably built between the 11 and the 12th century on a hill to control the territory. It underwent several transformations and neglection phases over the centuries. The second phase has been the generative modelling following the scan-to-BIM approach. The three-dimensional model is intended to support the design phases, from preliminary analysis to the construction site.For this reason, the Stronghold has been modelled with different Grade of Generation (GOG). The study of the eastern curtain wall, where the signs suffered by the structure due to the earthquake are most evident, was deepened through a Building Archaeology preliminary analysis. The third phase aimed at orienting the HBIM towards three digital information-sharing solutions such as Common Data Environment (CDE), and Virtual Reality (VR) to enhance the cultural and historical values, supporting the reopening of the Stronghold as a venue for conferences and exhibitions.

Details

Language :
English
ISSN :
21949034 and 16821750
Database :
OpenAIRE
Journal :
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Accession number :
edsair.doi.dedup.....64f679bdafb02f2cb19b7cbee74ca9b7