Scientometric review and visualisation of City Information Modeling (CIM) trends and future directions

被引:0
|
作者
Ebere Donatus Okonta [1 ]
Godspower Chukwudi Israel [2 ]
Francis Ogochukwu Okeke [3 ]
机构
[1] Teesside University,School of Computing, Engineering and Digital Technologies
[2] University of Jos,Department of Architecture
[3] Canterbury Christ Church University,School of Engineering, Technology and Design
来源
Discover Cities | / 2卷 / 1期
关键词
City Information Modelling (CIM); Scientometric analysis; Smart city; Digital twin; Building Information Modelling (BIM); Geographic information system (GIS); Research trends; Sustainability;
D O I
10.1007/s44327-025-00072-4
中图分类号
学科分类号
摘要
City Information Modelling (CIM) has emerged as a promising approach for developing smart and sustainable cities. The study conducted a scientometric review and visualisation of global CIM research from 1996 to 2023 through a co-author, co-word, and co-citation analysis on 303 bibliographic records from the Scopus core collection database using VOSviewer and Gephi software. Prominent research domains encompass areas such as Smart City, Digital Twin, CIM, 3D City Models, Geographic Information Systems (GIS), Building Information Modelling (BIM), Big Data, and the Internet of Things (IoT). Leading institutions contributing significantly to CIM research include NEC Laboratories Europe in Germany, the University of Florence in Italy, Loughborough University in the United Kingdom, South China University of Technology in China, the Georgia Institute of Technology in the United States, and the National University of Singapore in Singapore. These institutions have emerged as influential contributors to the field of CIM research. The United States, China, Germany, the Netherlands, South Korea, and the United Kingdom have emerged as leaders in citations for CIM research. Additionally, the study identified key publication outlets such as Sustainable Cities and Society, ISPRS journals, and Lecture Notes in Computer Science, emphasizing their pivotal role in disseminating CIM research. The study further identified some of the practical applications of CIM in Urban developments, such as Energy-Efficient Urban Planning, Urban Digital Twins for Participatory Planning, Geographical Digital Twins for Renewable Energy, Crisis Management Information Systems, Innovative Land Acquisition, Building Energy Consumption Optimization, and so on. Areas such as Artificial Intelligence, Blockchain, Human Factors, Design, Linked Data Benchmark, Photogrammetry, Photorealistic Texture, Virtual Reality, Ontology, and Semantic Web require considerable attention and warrant further studies. The study provides insights into CIM's status, trends, and collaboration networks, guiding policies and fostering research collaboration to enhance cities’ sustainability and technology.
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