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Special Session Proposal for ISMLG 2023
Data-driven solutions for underground built heritage modeling, preservation and valorization
Special Session Organizers
Alfonso Bahillo Martinez, University of Valladolid, Spain
Pinar Karagoz, Middle East Technical University, Turkey
Giuseppe Pace, ISMed-CNR Istituto di Studi Sul Mediterraneo, Italy
The Underground Built Heritage (UBH) is a unique cultural resource, which might contribute to individual and collective identity, social cohesion and inclusion, being laid at the heart of community’s sense of place. The UBH includes several typologies, such as natural and anthropic caves, underground burial/rites structures, mines and quarries, other man-made caves for exploitation and dwelling, underground infrastructures (cisterns, ancient drainage systems, tunnels, etc.), ancient structures and settlements currently buried. Although success stories in the field of UBH have captured the attention of the world, this resource’s description, modeling, preservation and valorisation finds relevant constraints. Among them, UBH results largely not or not well documented, and indeed under-utilized, or they deliver a perception that the underground space is a high-risk and costly area of intervention, and indeed under-exploited. Therefore, in the era of big data, UBH demands for data-driven solutions and technologies to better understand, promote, preserve, and celebrate, realizing its full potential as catalyzer for community valorization. For these reasons, the focus of this special session is to discuss the numerous data-driven solutions and technologies related to understanding, description, modeling, preservation and valorization of UBH.
This special session invites authors to submit the latest studies on data-driven solution applied to UBH that include (but are not limited to) the following topics:
UBH non-invasive diagnosis and monitoring.
Three-dimensional computer modelling.
Simulation of underground failures.
High-resolution visualization and reconstruction of UBH.
UBH data modelling and categorization
UBH related data analysis