The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Download
Publications Copernicus
Download
Citation
Articles | Volume XLII-4/W12
https://doi.org/10.5194/isprs-archives-XLII-4-W12-25-2019
https://doi.org/10.5194/isprs-archives-XLII-4-W12-25-2019
21 Feb 2019
 | 21 Feb 2019

DIGITAL SURVEY AND ALGORITHMIC MODELING IN HBIM. TOWARDS A LIBRARY OF COMPLEX CONSTRUCTION ELEMENTS

V. Bagnolo, R. Argiolas, and A. Cuccu

Keywords: Algorithmic modeling, Documentation, HBIM, Surveying, 3D modeling

Abstract. In the study of built heritage, the introduction of BIM models provides the advantage of a set of data that can be shared between different platforms. Despite the continuous progress in research, the modeling processes of complex construction elements, typical of historical architectures, always require a certain attention and care that involve considerable investments in terms of both resources and time. In this paper we present the first results of an ongoing research aimed at considering possible methods that can allow a simplification of the modeling processes of elements of historical architectures in the BIM environment. In particular, the research aims to explore the possibilities offered by the algorithmic modeling of complex construction elements. In the study of historical architecture, an enough recurring theme concerns those elements that can be traced back to the principles of architectural orders. In the survey of historical architecture, a quite recurring case study concerns those elements or parts of building ruled by the principles of architectural orders. One of the first elements taken into consideration was that of the column that, in its articulation in base, shaft and capital, offers three different levels of complexity of the modeling process very suitable for the research path. Starting with a collection of data acquired from digital photogrammetric modeling, we considered a initial set of different case studies that allowed us to conduct a first working hypothesis by embracing a quite wide range of possible variations starting from a basic column.