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To explore the research hotspots and development trends in the field of mine ecological restoration, based on the literature data retrieved from Web of Science (WOS) and China National Knowledge Infrastructure (CNKI), 692 English literatures and 298 Chinese literatures were visually analyzed using software including VOSviewer, CiteSpace and SCImago Graphica. The differences among various mine ecological restoration philosophies and key restoration technologies were also discussed. The results show that the number of publications in the field of mine ecological restoration shows an overall upward trend. Cooperation among countries is frequent, and a research network has been formed with China as the primary core and European and American countries such as the United States, Australia and Spain as the secondary cores. Cooperation among international high-yield institutions is close, while connections among domestic high-yield institutions are lacking. Research hotspots focus on coal mine restoration, phytoremediation technology, soil heavy metal remediation, microbial mechanism research, restoration effect evaluation, and carbon neutrality target practice. In the future, it is necessary to further study the restoration technologies of basic mine ecological units dominated by soil, microorganisms and plants, promote the application of emerging technologies such as UAV aerial mapping and machine learning in model construction and effect evaluation, and explore the path of mine ecological restoration under the carbon neutrality goal. Mine ecological restoration research is currently in a period of explosive development. China should combine macro-monitoring with micro-research, apply cutting-edge technologies, promote interdisciplinary integration and cross-field cooperation, and continuously improve the research system of mine ecological restoration in China.
, authors=Yang LIU
1, 2, Liangbin ZHOU
3, 4, Xuetao YUAN
5, Zhihui CHANG
1, authorsList=Yang LIU, Liangbin ZHOU, Xuetao YUAN, Zhihui CHANG, authorCompany=null, correspAuthors=Zhihui CHANG, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=null), CN=ArticleExt(id=1322559930222101253, articleId=1322559929735561987, tenantId=1146029695717560320, journalId=1225396423026438145, language=CN, title=基于知识图谱分析的矿山生态修复研究进展, columnId=1226462295417598973, journalTitle=矿业研究与开发, columnName=矿山安全与环保, runingTitle=null, highlight=null, articleAbstract=
为探究矿山生态修复领域的研究热点和发展趋势,基于Web of Science(WOS)和中国知网(CNKI)检索的文献数据,采用VOSviewer、CiteSpace、SCImago Graphica等软件,对692篇英文文献和298篇中文文献进行可视化分析,并探讨了不同矿山生态修复理念及关键修复技术的差异。结果表明:矿山生态修复研究领域的发文量总体呈上升趋势;国家之间合作频繁,已形成以中国为主要核心,以美国、澳大利亚、西班牙等欧美国家为次要核心的研究网络;国际高产机构间合作紧密,国内高产机构间缺乏联系;研究热点聚焦于煤矿修复、植物修复技术、土壤重金属修复、微生物作用研究、修复效果评价、碳中和目标实践等。未来需要深入以土壤、微生物、植物为主的矿山生态基本单元的修复技术,推动无人机航测、机器学习等新兴技术在模型搭建和效果评价中的应用,并探索碳中和目标下的矿山生态修复路径。矿山生态修复研究目前处于发展爆发期,我国应将宏观监测与微观研究相结合,运用前沿技术,促进跨学科融合与跨领域合作,持续完善我国矿山生态修复的研究体系。
, authors=刘洋
1, 2, 周良彬
3, 4, 袁雪涛
5, 常智慧
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1.School of Grassland Science, Beijing Forestry University, Beijing 100083, China
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1.北京林业大学 草业与草原学院,北京 100083
2.华北理工大学 电气工程学院,河北 唐山市 063210, bio={"content":"
刘洋(1988—),男,河北邢台人,硕士,讲师,主要从事矿山生态修复研究。E-mail: hlliuyang@ncst.edu.cn
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刘洋(1988—),男,河北邢台人,硕士,讲师,主要从事矿山生态修复研究。E-mail: hlliuyang@ncst.edu.cn
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3.成都获得感科技有限公司,四川 成都 610200
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5.College of Mining Engineering, North China University of Science and Technology, Tangshan, Hebei 063210, China, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null), CN=AuthorExt(id=1322559933225222951, tenantId=1146029695717560320, journalId=1225396423026438145, articleId=1322559929735561987, authorId=1322559933053256484, language=CN, stringName=袁雪涛, firstName=null, middleName=null, lastName=null, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=
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