Land use/cover change simulation research: A system literature review based on bibliometric analyses

Land use/cover change simulation research: A system literature review based on bibliometric analyses

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 2...

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Bibliographic Details
Main Authors: Meili Chen, Narimah Samat, Mohammad Javad Maghsoodi Tilaki, Liyuan Duan
Format: Article
Language:English
Published: Elsevier 2025-01-01
Series:Ecological Indicators
Subjects:
Land use change
Land cover change
Simulation research
Spatiotemporal patterns
Driving mechanisms
Simulation models
Online Access:http://www.sciencedirect.com/science/article/pii/S1470160X24014481
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Summary: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.
ISSN:1470-160X

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