文献类型：期刊文献

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

作者：Han, Huiqing Zhang, Yingjia Yin, Changying

通信作者：Han, HQ[1]

机构：[1]Guizhou Inst Technol, Sch Architecture & Urban Planning, Guiyang, Peoples R China

第一机构：贵州理工学院

通信机构：corresponding author), Guizhou Inst Technol, Sch Architecture & Urban Planning, Guiyang, Peoples R China.|贵州理工学院;

年份：2026

卷号：80

期号：2

起止页码：101-136

外文期刊名：GEODETSKI LIST

收录：WOS:【ESCI(收录号:WOS:001818840000002)】；

基金：This work was supported by the Ministry of Education Humanities and Social Sciences Research Project (25XJAZH003) and Guizhou Basic Research Program (MS [2026] 243) .

语种：英文

外文关键词：Big data; Land system; Bibliometric analysis; CiteSpace/VOSviewer; Research hotspots; Evolution pathways

摘要：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.