{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,2]],"date-time":"2026-04-02T15:55:02Z","timestamp":1775145302938,"version":"3.50.1"},"reference-count":50,"publisher":"MDPI AG","issue":"23","license":[{"start":{"date-parts":[[2024,12,4]],"date-time":"2024-12-04T00:00:00Z","timestamp":1733270400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The work developed aims to present an innovative methodology to execute the heritage conservation processes in a collaborative and interdisciplinary Building Information Modeling (BIM) project, with an effective management of the deterioration suffered over time, emphasizing the structures and coatings. The research begins with an architectural survey using terrestrial laser scanning (TLS) and terrestrial photogrammetry software, Structure from Motion (SfM), studying study the Duomo of Molfetta (Italy), a unique Romanesque architecture of Puglia (Italy). The methodological process is mainly aided by the precise semantic segmentation of global point clouds, a semi-automatic process assisted by classification algorithms implemented in the Cyclone 3DR post-processing software, which has allowed the classification of the unstructured information provided by the remote sensing equipment when identifying the architectural-structural systems of a building with high historical values. Subsequently, it was possible to develop an efficient Scan-to-HBIM workflow, where the Heritage BIM (HBIM) project has fulfilled the function of a database by incorporating and organizing all the information (graphic and non-graphic) to optimize the tasks of auscultation, identification, classification, and quantification and, in turn, facilitating the parametric modeling of unique structures and architectural elements. The results have shown great effectiveness in the processes of characterization of architectural heritage, focusing on the deformations and deterioration of the masonry in columns and pilasters. To make multidisciplinary conservation work more flexible, specific properties have been created for the identification and analysis of the degradation detected in the structures, with the HBIM project constituting a manager of the control and inspection activities. The restoration technician interacts with the determined 3D element to mark the \u201ctype decay\u201d, managing the properties in the element\u2019s own definition window. Interactive schemes have been defined that incorporate the items for the mapping of the elements, as well as particular properties of a conservation process (intervention, control, and maintenance). All listed parametric elements have links to be viewed in 2D and 3D views. Therefore, the procedure has facilitated the auscultation of the scanned element as it is semantically delimited, the parametric modeling of it, the analytical study of its materials and deterioration, and the association of intrinsic parameters so that they can be evaluated by all the intervening agents. But there are still some difficulties for the automatic interpretation of 3D point cloud data, related to specific systems of the historical architecture. In conclusion, human action and interpretation continues to be a fundamental pillar to achieve precise results in a heritage environment.<\/jats:p>","DOI":"10.3390\/rs16234542","type":"journal-article","created":{"date-parts":[[2024,12,4]],"date-time":"2024-12-04T04:47:22Z","timestamp":1733287642000},"page":"4542","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["An Efficient Process for the Management of the Deterioration and Conservation of Architectural Heritage: The HBIM Project of the Duomo of Molfetta (Italy)"],"prefix":"10.3390","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1413-3811","authenticated-orcid":false,"given":"Enrique","family":"Nieto-Juli\u00e1n","sequence":"first","affiliation":[{"name":"TEP970 Group Technological Innovation, 3D Modelling and Diagnosis Systems in Heritage and Building, Department of Graphic Expression and Building Engineering, Universidad de Sevilla, 41004 Seville, Spain"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7633-9989","authenticated-orcid":false,"given":"Silvana","family":"Bruno","sequence":"additional","affiliation":[{"name":"Department of Civil, Environmental, Land, Construction and Chemistry, University Polytechnic of Bari, 70126 Bari, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2186-6159","authenticated-orcid":false,"given":"Juan","family":"Moyano","sequence":"additional","affiliation":[{"name":"TEP970 Group Technological Innovation, 3D Modelling and Diagnosis Systems in Heritage and Building, Department of Graphic Expression and Building Engineering, Universidad de Sevilla, 41004 Seville, Spain"}]}],"member":"1968","published-online":{"date-parts":[[2024,12,4]]},"reference":[{"key":"ref_1","first-page":"65","article-title":"3D survey and semantic analysis for the documentation of built heritage. The case study of Palazzo Centrale of Pavia University","volume":"5","author":"Miceli","year":"2020","journal-title":"VITRUVIO-Int. J. Archit. Technol. Sustain."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Moyano, J., Nieto-Juli\u00e1n, J.E., Bienvenido-Huertas, D., and Mar\u00edn-Garc\u00eda, D. (2020). Validation of Close-Range Photogrammetry for Architectural and Archaeological Heritage: Analysis of Point Density and 3D Mesh Geometry. Remote Sens., 12.","DOI":"10.3390\/rs12213571"},{"key":"ref_3","unstructured":"Spina, S., Debattista, K., Bugeja, K., and Chalmers, A. (2011, January 18\u201321). Point Cloud Segmentation for Cultural Heritage Sites. Proceedings of the VAST\u201911: Proceedings of the 12th International Conference on Virtual Reality, Archaeology and Cultural Heritage, Prato, Italy."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"607","DOI":"10.1007\/s12518-021-00359-2","article-title":"Scan-to-HBIM for conservation and preservation of Cultural Heritage building: The case study of San Nicola in Montedoro church (Italy)","volume":"15","author":"Costantino","year":"2023","journal-title":"Appl. Geomat."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"47","DOI":"10.3390\/heritage3010004","article-title":"A Scan-to-BIM Methodology Applied to Heritage Buildings","volume":"3","author":"Rocha","year":"2020","journal-title":"Heritage"},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"de la Plata, A.R.M., Franco, P.A.C., Franco, J.C., and Bravo, V.G. (2021). Protocol Development for Point Clouds, Triangulated Meshes and Parametric Model Acquisition and Integration in an HBIM Workflow for Change Control and Management in a UNESCO\u2019s World Heritage Site. Sensors, 21.","DOI":"10.3390\/s21041083"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"25","DOI":"10.5194\/isprs-archives-XLII-2-W9-25-2019","article-title":"Photogrammetric survey with fisheye lens for the characterization of the La Sassa cave","volume":"XLII-2\/W9","author":"Alessandri","year":"2019","journal-title":"Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"429","DOI":"10.5194\/isprs-archives-XLII-2-W15-429-2019","article-title":"HBIM implementation for an ottoman mosque. Case of study: Sultan mehmet fatih II mosque in Kosovo","volume":"XLII-2\/W15","author":"Malinverni","year":"2019","journal-title":"Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"105190","DOI":"10.1016\/j.jobe.2022.105190","article-title":"Evaluation of records using terrestrial laser scanner in architectural heritage for information modeling in HBIM construction: The case study of the La Anunciaci\u00f3n church (Seville)","volume":"62","author":"Moyano","year":"2022","journal-title":"J. Build. Eng."},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Klapa, P., and Gawronek, P. (2022). Synergy of Geospatial Data from TLS and UAV for Heritage Building Information Modeling (HBIM). Remote. Sens., 15.","DOI":"10.3390\/rs15010128"},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Mat\u00e9-Gonz\u00e1lez, M.\u00c1., Di Pietra, V., and Piras, M. (2022). Evaluation of Different LiDAR Technologies for the Documentation of Forgotten Cultural Heritage under Forest Environments. Sensors, 22.","DOI":"10.3390\/s22166314"},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"P\u00e9rez, J.J., Senderos, M., Casado, A., and Leon, I. (2022). Field Work\u2019s Optimization for the Digital Capture of Large University Campuses, Combining Various Techniques of Massive Point Capture. Buildings, 12.","DOI":"10.3390\/buildings12030380"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"176","DOI":"10.1016\/j.jas.2012.07.024","article-title":"Integrating radar and laser-based remote sensing techniques for monitoring structural deformation of archaeological monuments","volume":"40","author":"Tapete","year":"2013","journal-title":"J. Archaeol. Sci."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"1712","DOI":"10.3390\/su7021712","article-title":"Differential Radar Interferometry for Structural and Ground Deformation Monitoring: A New Tool for the Conservation and Sustainability of Cultural Heritage Sites","volume":"7","author":"Zhou","year":"2015","journal-title":"Sustainability"},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Tang, P., Chen, F., Zhu, X., and Zhou, W. (2016). Monitoring Cultural Heritage Sites with Advanced Multi-Temporal InSAR Technique: The Case Study of the Summer Palace. Remote Sens., 8.","DOI":"10.3390\/rs8050432"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"2317","DOI":"10.1177\/1475921720942120","article-title":"Country-scale InSAR monitoring for settlement and uplift damage calculation in architectural heritage structures","volume":"20","author":"Drougkas","year":"2021","journal-title":"Struct. Health Monit."},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Su, R., and Ma, J. (2023). Research on the Protection of Architectural Heritage Based on SBAS and LSTM Technologies. 2023 IEEE International Conference on Image Processing and Computer Applications (ICIPCA), IEEE.","DOI":"10.1109\/ICIPCA59209.2023.10257768"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"253","DOI":"10.1016\/j.culher.2010.12.004","article-title":"Photogrammetric survey of complex geometries with low-cost software: Application to the \u2018G1\u2032 temple in Myson, Vietnam","volume":"12","author":"Barazzetti","year":"2011","journal-title":"J. Cult. Herit."},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Herban, S., Costantino, D., Alfio, V.S., and Pepe, M. (2022). Use of Low-Cost Spherical Cameras for the Digitisation of Cultural Heritage Structures into 3D Point Clouds. J. Imaging, 8.","DOI":"10.3390\/jimaging8010013"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"553","DOI":"10.5194\/isprsarchives-XXXIX-B5-553-2012","article-title":"Recording approach of heritage sites based on merging point clouds from high resolution photogrammetry and terrestrial laser scanning","volume":"XXXIX-B5","author":"Grussenmeyer","year":"2012","journal-title":"Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"95","DOI":"10.1016\/j.culher.2018.04.003","article-title":"A no-reference method of geometric content quality analysis of 3D models generated from laser scanning point clouds for hBIM","volume":"34","author":"Fryskowska","year":"2018","journal-title":"J. Cult. Herit."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"765","DOI":"10.5194\/isprs-archives-XLII-4-W18-765-2019","article-title":"Photogrammetric solutions for 3d modeling of cultural heritage sites in remote areas","volume":"XLII-4\/W18","author":"Mostafavi","year":"2019","journal-title":"Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"423","DOI":"10.1016\/j.culher.2007.06.003","article-title":"Documentation of cultural heritage using digital photogrammetry and laser scanning","volume":"8","author":"Yastikli","year":"2007","journal-title":"J. Cult. Herit."},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Jaradat, M., Al Majali, H., Bendea, C., Bungau, C.C., and Bungau, T. (2023). Enhancing Energy Efficiency in Buildings through PCM Integration: A Study across Different Climatic Regions. Buildings, 14.","DOI":"10.3390\/buildings14010040"},{"key":"ref_25","unstructured":"Galantucci, R.A., Musicco, A., Bruno, S., and Fatiguso, F. (2020, January 24\u201327). Automatic detection of dampness phenomena on architectural elements by point cloud segmentation. Proceedings of the Rehabend 2020 Euro-American Congress-Construction Pathology, Rehabilitation Technology and Heritage Management, Granada, Spain."},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Rodrigues, F., Cotella, V., Rodrigues, H., Rocha, E., Freitas, F., and Matos, R. (2022). Application of Deep Learning Approach for the Classification of Buildings\u2019 Degradation State in a BIM Methodology. Appl. Sci., 12.","DOI":"10.3390\/app12157403"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"73","DOI":"10.4995\/var.2021.15318","article-title":"Transfer learning and performance enhancement techniques for deep semantic segmentation of built heritage point clouds","volume":"12","author":"Matrone","year":"2021","journal-title":"Virtual Archaeol. Rev."},{"key":"ref_28","unstructured":"Mu\u00f1oz-Pandiella, I., Akoglu, K., Bosch, C., and Rushmeier, H. (2017, January 27\u201329). Towards Semi-Automatic Scaling Detection on Flat Stones. Proceedings of the EUROGRAPHICS Workshop on Graphics and Cultural Heritage, Graz, Austria."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"1035","DOI":"10.5370\/JEET.2016.11.4.1035","article-title":"A Robust Crack Filter Based on Local Gray Level Variation and Multiscale Analysis for Automatic Crack Detection in X-ray Images","volume":"11","author":"Peng","year":"2016","journal-title":"J. Electr. Eng. Technol."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"21","DOI":"10.1016\/j.culher.2016.11.017","article-title":"Semiautomatic detection and classification of materials in historic buildings with low-cost photogrammetric equipment","volume":"25","year":"2017","journal-title":"J. Cult. Herit."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"104928","DOI":"10.1016\/j.autcon.2023.104928","article-title":"Preserving our heritage: A photogrammetry-based digital twin framework for monitoring deteriorations of historic structures","volume":"152","author":"Kong","year":"2023","journal-title":"Autom. Constr."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1080\/01431161.2020.1788742","article-title":"Deep learning-based multi-feature semantic segmentation in building extraction from images of UAV photogrammetry","volume":"42","author":"Boonpook","year":"2021","journal-title":"Int. J. Remote. Sens."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"381","DOI":"10.1145\/358669.358692","article-title":"Random sample consensus","volume":"24","author":"Fischler","year":"1981","journal-title":"Commun. ACM"},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Raguram, R., Frahm, J.-M., and Pollefeys, M. (2008). A comparative analysis of RANSAC techniques leading to adaptive real-time random sample consensus. Computer Vision\u2014ECCV 2008: 10th European Conference on Computer Vision, Marseille, France, 12\u201318 October 2008, Springer. Proceedings, Part II.","DOI":"10.1007\/978-3-540-88688-4_37"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"112","DOI":"10.1016\/j.isprsjprs.2018.01.013","article-title":"An efficient global energy optimization approach for robust 3D plane segmentation of point clouds","volume":"137","author":"Dong","year":"2018","journal-title":"ISPRS J. Photogramm. Remote. Sens."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"88","DOI":"10.1016\/j.isprsjprs.2015.01.011","article-title":"Octree-based region growing for point cloud segmentation","volume":"104","author":"Vo","year":"2015","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_37","doi-asserted-by":"crossref","unstructured":"Kim, C., Habib, A., Pyeon, M., Kwon, G.-R., Jung, J., and Heo, J. (2016). Segmentation of Planar Surfaces from Laser Scanning Data Using the Magnitude of Normal Position Vector for Adaptive Neighborhoods. Sensors, 16.","DOI":"10.3390\/s16020140"},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"103856","DOI":"10.1016\/j.autcon.2021.103856","article-title":"Semantic interpretation of architectural and archaeological geometries: Point cloud segmentation for HBIM parameterisation","volume":"130","author":"Moyano","year":"2021","journal-title":"Autom. Constr."},{"key":"ref_39","doi-asserted-by":"crossref","unstructured":"Croce, V., Caroti, G., De Luca, L., Jacquot, K., Piemonte, A., and V\u00e9ron, P. (2021). From the Semantic Point Cloud to Heritage-Building Information Modeling: A Semiautomatic Approach Exploiting Machine Learning. Remote Sens., 13.","DOI":"10.3390\/rs13030461"},{"key":"ref_40","unstructured":"(2024, August 03). Leica Cyclone 3DR (leica-geosystems.com). Available online: https:\/\/shop.leica-geosystems.com\/it\/es-ES\/leica-blk\/software\/leica-cyclone-3dr\/buy."},{"key":"ref_41","doi-asserted-by":"crossref","unstructured":"Tzedaki, V., and Kamara, J.M. (2013, January 3\u20135). Capturing As-Built Information for a BIM Environment Using 3D Laser Scanner: A Process Model. Proceedings of the Architectural Engineering Conference AEI 2013, State College, PA, USA.","DOI":"10.1061\/9780784412909.047"},{"key":"ref_42","first-page":"e00166","article-title":"Geometric accuracy and semantic richness in heritage BIM: A review","volume":"19","author":"Radanovic","year":"2020","journal-title":"Digit. Appl. Archaeol. Cult. Herit."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"5627","DOI":"10.1109\/JSTARS.2021.3068796","article-title":"A Survey of Applications With Combined BIM and 3D Laser Scanning in the Life Cycle of Buildings","volume":"14","author":"Liu","year":"2021","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"103274","DOI":"10.1016\/j.jobe.2021.103274","article-title":"Analysis and management of structural deformations through parametric models and HBIM workflow in architectural heritage","volume":"45","author":"Moyano","year":"2022","journal-title":"J. Build. Eng."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"104551","DOI":"10.1016\/j.autcon.2022.104551","article-title":"Systematic approach to generate Historical Building Information Modelling (HBIM) in architectural restoration project","volume":"143","author":"Moyano","year":"2022","journal-title":"Autom. Constr."},{"key":"ref_46","doi-asserted-by":"crossref","unstructured":"Nieto-Juli\u00e1n, J.E., Lara, L., and Moyano, J. (2021). Implementation of a TeamWork-HBIM for the Management and Sustainability of Architectural Heritage. Sustainability, 13.","DOI":"10.3390\/su13042161"},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"107965","DOI":"10.1016\/j.jobe.2023.107965","article-title":"Semantic interoperability for cultural heritage conservation: Workflow from ontologies to a tool for managing and sharing data","volume":"80","author":"Moyano","year":"2023","journal-title":"J. Build. Eng."},{"key":"ref_48","unstructured":"Railway Innovation Hub, AEI (2024, February 16). Agrupaciones Empresariales Innovadoras, M. y A. U. Ministerio de Transportes, and Adif. Administrador de Infraestructuras Ferroviarias. BIM Railway Classification System SCFclass. Available online: https:\/\/www.railwayinnovationhub.com\/bim\/."},{"key":"ref_49","unstructured":"NBS Enterprises Ltd (2024, February 16). Uniclass\u2014Unified Classification for the Construction Industry. Available online: https:\/\/uniclass.thenbs.com\/."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"105728","DOI":"10.1016\/j.autcon.2024.105728","article-title":"Geometric characterization and segmentation of historic buildings using classification algorithms and convolutional networks in HBIM","volume":"167","author":"Moyano","year":"2024","journal-title":"Autom. Constr."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/16\/23\/4542\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T16:46:33Z","timestamp":1760114793000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/16\/23\/4542"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,12,4]]},"references-count":50,"journal-issue":{"issue":"23","published-online":{"date-parts":[[2024,12]]}},"alternative-id":["rs16234542"],"URL":"https:\/\/doi.org\/10.3390\/rs16234542","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,12,4]]}}}