ABSTRACT. We draw on a substantial body of theoretical and empirical research on 3D virtual simulation technology, digital twin modeling, and geospatial data mining in smart sustainable city governance and management. With increasing evidence of spatial computing technology, digital twin modeling, multi-sensor environmental data fusion, there is an essential demand for comprehending whether digital twin modeling integrate geospatial data mining and urban cloud data. In this research, prior findings were cumulated indicating that virtual simulation tools, urban sensing technologies, and digital twin networks enable smart city environments. We carried out a quantitative literature review of ProQuest, Scopus, and the Web of Science throughout March 2022, with search terms including “smart sustainable city governance and management” + “3D virtual simulation technology,” “digital twin modeling,” and “geospatial data mining.” As we analyzed research published in 2022, only 186 papers met the eligibility criteria. By removing controversial or unclear findings (scanty/unimportant data), results unsupported by replication, undetailed content, or papers having quite similar titles, we decided on 34, chiefly empirical, sources. Data visualization tools: Dimensions (bibliometric mapping) and VOSviewer (layout algorithms). Reporting quality assessment tool: PRISMA. Methodological quality assessment tools include: AMSTAR, Distiller SR, ROBIS, and SRDR.

Keywords: digital twin; geospatial data; smart sustainable city; governance; simulation

How to cite: Kovacova, M., Novak, A., Machova, V., and Carey, B. (2022). “3D Virtual Simulation Technology, Digital Twin Modeling, and Geospatial Data Mining in Smart Sustainable City Governance and Management,” Geopolitics, History, and International Relations 14(1): 43–58. doi: 10.22381/GHIR14120223.

Received 21 March 2022 • Received in revised form 25 June 2022
Accepted 27 June 2022 • Available online 30 June 2022