3D Point Cloud for Cultural Heritage: A Scientometric Survey
Three-dimensional point cloud has been widely used in the cultural heritage field in the last two decades, gaining attention from both academic and industry communities. A large number of scientific papers have been published concerning this topic, which covers a wide range of journals, countries, a...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-11-01
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| Series: | Remote Sensing |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2072-4292/14/21/5542 |
| _version_ | 1797466633869983744 |
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| author | Su Yang Shishuo Xu Wei Huang |
| author_facet | Su Yang Shishuo Xu Wei Huang |
| author_sort | Su Yang |
| collection | DOAJ |
| description | Three-dimensional point cloud has been widely used in the cultural heritage field in the last two decades, gaining attention from both academic and industry communities. A large number of scientific papers have been published concerning this topic, which covers a wide range of journals, countries, and disciplines. There has been no comprehensive and systematic survey of recent literature performed in a scientometric way based on the complex network analysis methods. In this work, we extracted the terms (i.e., noun phrases included in the title, abstract and keywords), the documents, the countries that the research institutions are located in, and the categories that the literature belongs to from the Web of Science database to compose a term co-occurrence network, document co-citation network, collaborative country network and category co-occurrence network using CiteSpace software. Through visualizing and analyzing those networks, we identified the research hotspots, landmark literature, national collaboration, interdisciplinary patterns as well as the emerging trends through assessing the central nodes and the nodes with strong citation bursts. This work not only provides a structured view on state-of-art literature, but also reveals the future trends of employing 3D point cloud data for cultural heritage, aiding researchers carry out further research in this area. |
| first_indexed | 2024-03-09T18:41:28Z |
| format | Article |
| id | doaj.art-d15d41507c1545289a1afd7b5ae173a2 |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-09T18:41:28Z |
| publishDate | 2022-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-d15d41507c1545289a1afd7b5ae173a22023-11-24T06:40:42ZengMDPI AGRemote Sensing2072-42922022-11-011421554210.3390/rs142155423D Point Cloud for Cultural Heritage: A Scientometric SurveySu Yang0Shishuo Xu1Wei Huang2College of Geosciences and Surveying Engineering, China University of Mining and Technology, Beijing 100083, ChinaSchool of Geomatics and Urban Spatial Informatics, Beijing University of Civil Engineering and Architecture, Beijing 100044, ChinaCollege of Surveying and Geo-informatics, Tongji University, Shanghai 200092, ChinaThree-dimensional point cloud has been widely used in the cultural heritage field in the last two decades, gaining attention from both academic and industry communities. A large number of scientific papers have been published concerning this topic, which covers a wide range of journals, countries, and disciplines. There has been no comprehensive and systematic survey of recent literature performed in a scientometric way based on the complex network analysis methods. In this work, we extracted the terms (i.e., noun phrases included in the title, abstract and keywords), the documents, the countries that the research institutions are located in, and the categories that the literature belongs to from the Web of Science database to compose a term co-occurrence network, document co-citation network, collaborative country network and category co-occurrence network using CiteSpace software. Through visualizing and analyzing those networks, we identified the research hotspots, landmark literature, national collaboration, interdisciplinary patterns as well as the emerging trends through assessing the central nodes and the nodes with strong citation bursts. This work not only provides a structured view on state-of-art literature, but also reveals the future trends of employing 3D point cloud data for cultural heritage, aiding researchers carry out further research in this area.https://www.mdpi.com/2072-4292/14/21/5542point cloudcultural heritageCiteSpacescientometricvisual analysis |
| spellingShingle | Su Yang Shishuo Xu Wei Huang 3D Point Cloud for Cultural Heritage: A Scientometric Survey Remote Sensing point cloud cultural heritage CiteSpace scientometric visual analysis |
| title | 3D Point Cloud for Cultural Heritage: A Scientometric Survey |
| title_full | 3D Point Cloud for Cultural Heritage: A Scientometric Survey |
| title_fullStr | 3D Point Cloud for Cultural Heritage: A Scientometric Survey |
| title_full_unstemmed | 3D Point Cloud for Cultural Heritage: A Scientometric Survey |
| title_short | 3D Point Cloud for Cultural Heritage: A Scientometric Survey |
| title_sort | 3d point cloud for cultural heritage a scientometric survey |
| topic | point cloud cultural heritage CiteSpace scientometric visual analysis |
| url | https://www.mdpi.com/2072-4292/14/21/5542 |
| work_keys_str_mv | AT suyang 3dpointcloudforculturalheritageascientometricsurvey AT shishuoxu 3dpointcloudforculturalheritageascientometricsurvey AT weihuang 3dpointcloudforculturalheritageascientometricsurvey |