{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,13]],"date-time":"2026-02-13T10:46:24Z","timestamp":1770979584165,"version":"3.50.1"},"reference-count":76,"publisher":"MDPI AG","issue":"16","license":[{"start":{"date-parts":[[2024,8,20]],"date-time":"2024-08-20T00:00:00Z","timestamp":1724112000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Deanship of Scientific Research, Vice Presidency for Graduate Studies and Scientific Research, King Faisal University, Saudi Arabia","award":["KFU241319"],"award-info":[{"award-number":["KFU241319"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The analysis and preservation of the cultural heritage sites are critical for maintaining their historical and architectural integrity, as they can be damaged by various factors, including climatic, geological, geomorphological, and human actions. Based on this, the present study proposes a semi-automatic and non-learning-based method for detecting degraded surfaces within cultural heritage sites by integrating UAV, photogrammetry, and 3D data analysis. A 20th-century fortification from Romania was chosen as the case study due to its physical characteristics and state of degradation, making it ideal for testing the methodology. Images were collected using UAV and terrestrial sensors and processed to create a detailed 3D point cloud of the site. The developed pipeline effectively identified degraded areas, including cracks and material loss, with high accuracy. The classification and segmentation algorithms, including K-means clustering, geometrical features, RANSAC, and FACETS, improved the detection of destructured areas. The combined use of these algorithms facilitated a detailed assessment of the structural condition. This integrated approach demonstrated that the algorithms have the potential to support each other in minimizing individual limitations and accurately identifying degraded surfaces. Even though some limitations were observed, such as the potential for the overestimation of false negatives and positives areas, the damaged surfaces were extracted with high precision. The methodology proved to be a practical and economical solution for cultural heritage monitoring and conservation, offering high accuracy and flexibility. One of the greatest advantages of the method is its ease of implementation, its execution speed, and the potential of using entirely open-source software. This approach can be easily adapted to various heritage sites, significantly contributing to their protection and valorization.<\/jats:p>","DOI":"10.3390\/rs16163061","type":"journal-article","created":{"date-parts":[[2024,8,20]],"date-time":"2024-08-20T09:13:48Z","timestamp":1724145228000},"page":"3061","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["Advanced Semi-Automatic Approach for Identifying Damaged Surfaces in Cultural Heritage Sites: Integrating UAVs, Photogrammetry, and 3D Data Analysis"],"prefix":"10.3390","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1046-3776","authenticated-orcid":false,"given":"Tudor","family":"Caciora","sequence":"first","affiliation":[{"name":"Department of Geography, Tourism and Territorial Planning, Faculty of Geography, Tourism and Sport, University of Oradea, 1 Universitatii Street, 410087 Oradea, Romania"}]},{"given":"Alexandru","family":"Ilie\u0219","sequence":"additional","affiliation":[{"name":"Department of Geography, Tourism and Territorial Planning, Faculty of Geography, Tourism and Sport, University of Oradea, 1 Universitatii Street, 410087 Oradea, Romania"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7586-6226","authenticated-orcid":false,"given":"Grigore Vasile","family":"Herman","sequence":"additional","affiliation":[{"name":"Department of Geography, Tourism and Territorial Planning, Faculty of Geography, Tourism and Sport, University of Oradea, 1 Universitatii Street, 410087 Oradea, Romania"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2898-8212","authenticated-orcid":false,"given":"Zharas","family":"Berdenov","sequence":"additional","affiliation":[{"name":"Faculty of Science, L.N. Gumilyov Eurasian National University, 2 Satpayev Street, Nur-Sultan 010008, Kazakhstan"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2736-7000","authenticated-orcid":false,"given":"Bahodirhon","family":"Safarov","sequence":"additional","affiliation":[{"name":"Department of Digital Economy, Samarkand State University, Samarkand 140105, Uzbekistan"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-8085-853X","authenticated-orcid":false,"given":"Bahadur","family":"Bilalov","sequence":"additional","affiliation":[{"name":"Department of Tourism Business, Azerbaijan University of Tourism and Management, Baku 1172, Azerbaijan"}]},{"given":"Dorina Camelia","family":"Ilie\u0219","sequence":"additional","affiliation":[{"name":"Department of Geography, Tourism and Territorial Planning, Faculty of Geography, Tourism and Sport, University of Oradea, 1 Universitatii Street, 410087 Oradea, Romania"}]},{"given":"\u0218tefan","family":"Baias","sequence":"additional","affiliation":[{"name":"Department of Geography, Tourism and Territorial Planning, Faculty of Geography, Tourism and Sport, University of Oradea, 1 Universitatii Street, 410087 Oradea, Romania"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0510-3730","authenticated-orcid":false,"given":"Thowayeb H.","family":"Hassan","sequence":"additional","affiliation":[{"name":"Social Studies Department, College of Arts, King Faisal University, Al Ahsa 31982, Saudi Arabia"},{"name":"Tourism Studies Department, Faculty of Tourism and Hotel Management, Helwan University, Cairo 12612, Egypt"}]}],"member":"1968","published-online":{"date-parts":[[2024,8,20]]},"reference":[{"key":"ref_1","first-page":"1103","article-title":"Geohazards affecting cultural heritage monuments. 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