<p>Mineral prospectivity mapping (MPM) is becoming a cutting edge and hotspot of geoscientific research in the context of artificial intelligence era, accumulating substantial publications over the past two decades. The analysis of research dynamics on these publications helps to trace the trajectory of development and to provide insights into future foci in the MPM field. We conducted a bibliometric analysis of publications closely related to the field of MPM from January 1, 2006, to December 31, 2024, based on the Web of Science Core Collection database. We analyzed 727 publications, involving 55 countries, 1974 authors, 671 institutions, and 95 publication sources. The analyses included statistics on the annual number of MPM-related publications, top and highly cited papers, research authors and institutions, scientific cooperation between countries, sources statistic, co-occurrence of keywords, and newly emerging high-frequency keywords in the latest publications. The analytic results are presented herein using information visualization tools, including CiteSpace, VOSviewer, R bibliometrix, and Scimago Graphica. The results highlight a thriving development trend of MPM research that can be subdivided into three distinct periods including budding, expansion and boom period. Carranza, E. J. M. is the author who has participated in the authorship of the most number of MPM papers with the maximum accumulated citations. Zuo, R. stands out as the leading author in number of publications and total citations as either the first or corresponding author in the MPM field. Yousefi, M. is noted for achieving the highest average citation count per article among authors with significant publication volumes. Rodriguez-Galiano, V. also shows his great impact through his top cited paper that achieved 816 citations in the past 10 years. China has the largest volume of MPM-related publications in global, and the collaboration analysis among countries indicates that Chinese scholars engaged in the most frequent research collaborations with researchers from various countries. Australia had collaborated with the largest number of countries. China University of Geosciences leads in the institution ranking in terms of publication volume and total citations and holds three researchers that position within the top 10 globally cited authors. “Ore Geology Reviews” and “Natural Resources Research” are the most concentrated sources for MPM-related publications, accounting for 37.0% published articles and 43.3% accumulated citations. The analysis of author keywords indicates that “GIS” and “machine learning” are the two most frequently occurring keywords in MPM-related publications. Deep learning, few-shot learning and explainable artificial intelligence are currently the hottest research topics.</p>

Bibliometric Analysis of Mineral Prospectivity Mapping Research from 2006 to 2024

期刊论文
发表日期：

2025年10月17日

查看全文

Hongwei Zhang,
Tao Sun

摘要

Mineral prospectivity mapping (MPM) is becoming a cutting edge and hotspot of geoscientific research in the context of artificial intelligence era, accumulating substantial publications over the past two decades. The analysis of research dynamics on these publications helps to trace the trajectory of development and to provide insights into future foci in the MPM field. We conducted a bibliometric analysis of publications closely related to the field of MPM from January 1, 2006, to December 31, 2024, based on the Web of Science Core Collection database. We analyzed 727 publications, involving 55 countries, 1974 authors, 671 institutions, and 95 publication sources. The analyses included statistics on the annual number of MPM-related publications, top and highly cited papers, research authors and institutions, scientific cooperation between countries, sources statistic, co-occurrence of keywords, and newly emerging high-frequency keywords in the latest publications. The analytic results are presented herein using information visualization tools, including CiteSpace, VOSviewer, R bibliometrix, and Scimago Graphica. The results highlight a thriving development trend of MPM research that can be subdivided into three distinct periods including budding, expansion and boom period. Carranza, E. J. M. is the author who has participated in the authorship of the most number of MPM papers with the maximum accumulated citations. Zuo, R. stands out as the leading author in number of publications and total citations as either the first or corresponding author in the MPM field. Yousefi, M. is noted for achieving the highest average citation count per article among authors with significant publication volumes. Rodriguez-Galiano, V. also shows his great impact through his top cited paper that achieved 816 citations in the past 10 years. China has the largest volume of MPM-related publications in global, and the collaboration analysis among countries indicates that Chinese scholars engaged in the most frequent research collaborations with researchers from various countries. Australia had collaborated with the largest number of countries. China University of Geosciences leads in the institution ranking in terms of publication volume and total citations and holds three researchers that position within the top 10 globally cited authors. “Ore Geology Reviews” and “Natural Resources Research” are the most concentrated sources for MPM-related publications, accounting for 37.0% published articles and 43.3% accumulated citations. The analysis of author keywords indicates that “GIS” and “machine learning” are the two most frequently occurring keywords in MPM-related publications. Deep learning, few-shot learning and explainable artificial intelligence are currently the hottest research topics.