Towards Intelligent Digital Heritage: From Latest Digital Survey Techniques to Advanced 3D Data Analytics and Use

A special issue of Heritage (ISSN 2571-9408).

Deadline for manuscript submissions: 31 December 2024 | Viewed by 3180

Special Issue Editors


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Guest Editor
Department of Architecture, Built Environment and Construction Engineering, Politecnico di Milano, 20133 Milano, Italy
Interests: photogrammetry; laser scanning; topography; mobile mapping; CH digitalization; 3D
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Guest Editor
Department of History and Cultural Heritage, University of Siena, 53100 Siena, Italy
Interests: archeology

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Guest Editor
3D Optical Metrology (3DOM) Unit, Bruno Kessler Foundation (FBK), 38123 Trento, Italy
Interests: geomatics; mapping; UAV
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Special Issue Information

Dear Colleagues,

The development of smart tools has led to a new age of digital cultural heritage preservation and understanding. From advanced 3D surveys to sophisticated data analytics, these technologies are revolutionizing the way in which cultural artifacts and heritage sites are documented, analyzed, and shared. This evolution is also vital for generations to come as it helps to preserve vulnerable and endangered sites and makes cultural knowledge more accessible to more people.

Three-dimensional surveying technologies, including photogrammetry and laser scanning, are becoming more and more essential instruments for digitally documenting cultural heritage. These technologies offer a digital archive that can be utilized for research, education, and conservation. These days, tools like mobile mapping and Artificial Intelligence (AI) are available to overcome operational challenges that were not previously addressed or to create precise and detailed digital replicas of artefacts, buildings, and landscapes—even in real time. Beyond creating digital models, intelligent tools are also enhancing our ability to interpret and interact with these digital assets allowing analyses of patterns, structures, materials, and state of conservation in ways that were previously impossible.

Furthermore, the way in which the public interacts with cultural heritage is being revolutionized by advanced data use through interactive web platforms, virtual reality (VR), and augmented reality (AR). With the help of these technologies, people can now explore historical sites from the comfort of their own homes, engage with digital models in immersive settings, and even contribute to the restoration process through crowdsourcing projects.

The goal of this Special Issue is to collect papers (original research articles and review papers) to give insights about these trends, exploring one of the three main aspects (survey, data analytics, and data fruition) or all of them, describing exceptional case studies, and presenting issues, possible solutions, and future developments.

This Special Issue will welcome manuscripts that link the following themes:

  • Low-cost sensors and open-source algorithms for terrestrial 3D modelling;
  • Fusion of multi-source and multi-sensors data;
  • Research in 3D/4D survey and modelling;
  • Automation in data processing;
  • Image matching, Multi-View Stereo (MVS) and 3D reconstruction;
  • Point cloud processing, semantic enrichment, and analysis;
  • NeRF and Gaussian splatting 3D reconstruction and modelling;
  • Semantic and AI methods in terrestrial 3D reconstruction problems;
  • Accuracy requirement and assessment;
  • Virtual and augmented reality for complex architectures and heritage;
  • Investigations in BIM for cultural heritage (HBIM);
  • Data sharing platform for architectural 3D models.

We look forward to receiving your original research articles and reviews.

Dr. Francesco Fassi
Dr. Stefano Campana
Dr. Fabio Remondino
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Heritage is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • 3D survey
  • photogrammetry
  • laser scanning
  • cultural heritage
  • AI 
  • 3D data analytics

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Published Papers (2 papers)

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Research

26 pages, 19393 KiB  
Article
ML Approaches for the Study of Significant Heritage Contexts: An Application on Coastal Landscapes in Sardinia
by Marco Cappellazzo, Giacomo Patrucco and Antonia Spanò
Heritage 2024, 7(10), 5521-5546; https://doi.org/10.3390/heritage7100261 - 5 Oct 2024
Viewed by 905
Abstract
Remote Sensing (RS) and Geographic Information Science (GIS) techniques are powerful tools for spatial data collection, analysis, management, and digitization within cultural heritage frameworks. Despite their capabilities, challenges remain in automating data semantic classification for conservation purposes. To address this, leveraging airborne Light [...] Read more.
Remote Sensing (RS) and Geographic Information Science (GIS) techniques are powerful tools for spatial data collection, analysis, management, and digitization within cultural heritage frameworks. Despite their capabilities, challenges remain in automating data semantic classification for conservation purposes. To address this, leveraging airborne Light Detection And Ranging (LiDAR) point clouds, complex spatial analyses, and automated data structuring is crucial for supporting heritage preservation and knowledge processes. In this context, the present contribution investigates the latest Artificial Intelligence (AI) technologies for automating existing LiDAR data structuring, focusing on the case study of Sardinia coastlines. Moreover, the study preliminary addresses automation challenges in the perspective of historical defensive landscapes mapping. Since historical defensive architectures and landscapes are characterized by several challenging complexities—including their association with dark periods in recent history and chronological stratification—their digitization and preservation are highly multidisciplinary issues. This research aims to improve data structuring automation in these large heritage contexts with a multiscale approach by applying Machine Learning (ML) techniques to low-scale 3D Airborne Laser Scanning (ALS) point clouds. The study thus develops a predictive Deep Learning Model (DLM) for the semantic segmentation of sparse point clouds (<10 pts/m2), adaptable to large landscape heritage contexts and heterogeneous data scales. Additionally, a preliminary investigation into object-detection methods has been conducted to map specific fortification artifacts efficiently. Full article
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10 pages, 3383 KiB  
Article
Virtually Reconstructing Bernhard Heine’s Osteotome
by John LaRocco and Eric Zachariah
Heritage 2024, 7(7), 3756-3765; https://doi.org/10.3390/heritage7070178 - 15 Jul 2024
Viewed by 930
Abstract
The osteotome was a hand-cranked medical chainsaw designed in 1830 by the German surgeon Bernhard Heine. Before Heine, surgeons used crude, manual tools, such as hammers, chisels, and handsaws. The osteotome was among the first mechanical tools used in orthopedic surgery, and it [...] Read more.
The osteotome was a hand-cranked medical chainsaw designed in 1830 by the German surgeon Bernhard Heine. Before Heine, surgeons used crude, manual tools, such as hammers, chisels, and handsaws. The osteotome was among the first mechanical tools used in orthopedic surgery, and it preceded the later use of the motorized chainsaw for woodcutting. Due to the small number of units manufactured, questions remain about the osteotome’s usage. To facilitate conservation and assist with investigation, Heine’s osteotome was digitally reconstructed. As with other digital reconstruction attempts in cultural heritage, assumptions were made to facilitate reproduction. To highlight the functional similarities and contrasts between early and contemporary tools, its parts were compared with contemporary chainsaws and surgical tools. Contemporary orthopedic surgeons have largely shifted away from medical chainsaws, such as the osteotome, in favor of reciprocating saws. Due to its small size and medical purpose, the osteotome was designed for greater precision than a modern industrial chainsaw. Based on the reproduction and comparative analysis, the device was likely used in a manner more similar to modern medical reciprocating saws than to its direct descendant, the industrial chainsaw. The Heine osteotome mechanized surgery and its descendants are still used in medicine and the industry. The osteotome model enabled an analysis of its function and use. Full article
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