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• Analyzes 2062 papers on LUCC using bibliometric methods. • Tracks rising global interest in LUCC through detailed publication and collaboration trends from 1990 to 2023. • Outlines a systematic five-step LUCC simulation process enhancing result accuracy and reliability. • Identifies key research areas in LUCC simulation, including spatiotemporal patterns, driving mechanisms, simulation models, and comprehensive applications. • Categorizes LUCC models into quantitative, spatial, and hybrid types, tailored to diverse research objectives and methodologies. Land use/cover change (LUCC) simulation is a critical tool for monitoring and predicting LUCC, which is essential for sustainable development and land resource management. This paper employs bibliometric methods to systematically analyze the 2062 papers published in the Web of Science from 1990 to 2023, focusing areas including publication trends, overall focus thematic, keyword analysis, and national collaboration network analysis. Key developments encompass spatiotemporal pattern analysis, driving mechanism analysis, simulation model analysis, and comprehensive application analysis. The review identified three categories of models: quantitative prediction models, spatial simulation models, and hybrid models. Despite significant progress, challenges remain in data reliability, the selection and quantification of driving factors, and issues related to spatial and temporal scales. Future research should focus on establishing high spatiotemporal resolution big data systems, multi-scenario theoretical frameworks, multi-scale multi-level spatiotemporal dynamic models, and AI and machine learning. Enhancing the coupling of models improves understanding and prediction of complex LUCC processes, supporting global environmental research, resource management, and policymaking. This approach aligns with the objectives of the 28th Conference of the Parties to the United Nations Framework Convention on Climate Change (COP28) and advances the Sustainable Development Goals (SDGs) by addressing environmental challenges and informing sustainable climate policies.
Samat et al. (Fri,) studied this question.