Review article

https://doi.org/10.67252/gl.2026.80.2.1

The Application Progress of Big Data in Land System Research: Based on the Web of Science Database

Huiqing Han ; School of Architecture and Urban Planning, Guizhou Institute of Technology, Guiyang, PR China *
Yingjia Zhang ; School of Architecture and Urban Planning, Guizhou Institute of Technology, Guiyang, PR China
Changying Yin ; School of Architecture and Urban Planning, Guizhou Institute of Technology, Guiyang, PR China

* Corresponding author.

Abstract

With the rapid development of information technology, big data has become a vital driving force in land system research. Based on the Web of Science Core Collection database, this study adopts bibliometric methods combined with visualization tools such as CiteSpace and VOSviewer to systematically review the application evolution, research hotspots, and collaboration networks of big data technology in land system studies. A total of 317 relevant articles published between 2013 and 2024 were selected and analyzed from the perspectives of annual publication trends, keyword co-occurrence, author-institution collaboration networks, and thematic clustering. The results reveal that big data applications in land system research have undergone a transition from initial exploration to rapid growth and are now entering a mature stage. Research themes have expanded from early land use change detection to broader areas including ecosystem service evaluation, urban expansion simulation, agricultural monitoring, and carbon emission analysis. Practical applications frequently utilize remote sensing data, geographic information systems, machine learning, and artificial intelligence to support spatial modeling, predictive analysis, and land planning tasks. The study also finds that the Chinese Academy of Sciences ranks among the global leaders in terms of research output and collaborative influence, with research institutions displaying a "core–periphery" structure. Keyword evolution indicates an increasing trend toward intelligent technological methods and interdisciplinary integration. This study contributes to a better understanding of the co-evolution of big data and land system research and provides systematic references and theoretical support for future academic research, policy-making, and spatial governance.

Keywords

Big data; Land system; Bibliometric analysis; CiteSpace/VOSviewer; Research hotspots; Evolution pathways

Hrčak ID:

348609

URI

https://hrcak.srce.hr/348609

Publication date:

30.6.2026.

Article data in other languages: croatian

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