SYSTEMATIC REVIEW article
Front. Sustain. Food Syst.
Sec. Land, Livelihoods and Food Security
Volume 9 - 2025 | doi: 10.3389/fsufs.2025.1548565
This article is part of the Research TopicGlobal Land Use Intensity Change and Its Impact on Food SecurityView all 15 articles
Review of Simulations on Land Use Change: A Methodology Based on Bibliometric Analysis
Provisionally accepted
- Agricultural Information Institute, Chinese Academy of Agricultural Sciences, Haidian, China
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Land use change simulation is crucial for understanding global environmental changes and guiding sustainable land management. This study conducts a bibliometric analysis of 2,147 Web of Science articles from 1988 to 2023 to summarize research trends, thematic evolutions, and future directions in land use change modeling. Using Biblioshiny tools, the study applies quantitative analytics, cocitation network mapping, and keyword clustering. The research reveals three developmental phases. From 1988From -2000 (62 articles) (62 articles), foundational models like CLUE and CA were developed. During 2001-2016 (1,039 articles), there were advancements in coupled models and multi-scenario simulations. From 2017-2023 (1,046 articles), the focus shifted to integrative frameworks linking land dynamics, ecosystem services, and climate feedbacks. Annual publication outputs increased from 5 to 149, showing exponential growth. Key research themes involve computational modeling, spatiotemporal dynamics analysis, and environmental impact assessment. Recent trends highlight "river-basin", "multi-source data fusion", and "geographically weighted models", indicating a move towards basin-scale simulations, machine learning integration, and policy-oriented scenarios. China, the U.S., and Germany lead in research output, with top institutions including Beijing Normal University and the Chinese Academy of Sciences. China and the U.S. have strong domestic collaborations, while European countries have higher international collaboration ratios. The analysis points out research gaps, such as limited integration of socio-economic drivers and insufficient crossscale modeling. Future research should focus on developing hybrid frameworks combining processbased and data-driven models, leveraging multi-source data for accuracy, and designing scenariobased models for sustainable development goals, especially in river basins and urbanizing regions.
Keywords: Land use change1, bibliometrics2, prediction3, Simulation4, Models5 Methodology, Software, Data curation, Writing-original draft. L.H.: Data curation
Received: 19 Dec 2024; Accepted: 15 May 2025.
Copyright: © 2025 Sun, Huang, Meng, Chi, Wu and Zhou. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Xiangyang Zhou, Agricultural Information Institute, Chinese Academy of Agricultural Sciences, Haidian, China
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