Geodata Science-Based Mineral Prospectivity Mapping: A Review

被引:0
作者
Renguang Zuo
机构
[1] China University of Geosciences,State Key Laboratory of Geological Processes and Mineral Resources
来源
Natural Resources Research | 2020年 / 29卷
关键词
Mineral prospectivity mapping; Geodata science; Geological prospecting big data; Geoinformation; Geo-knowledge; GIS;
D O I
暂无
中图分类号
学科分类号
摘要
This paper introduces the concept of geodata science-based mineral prospectivity mapping (GSMPM), which is based on analyzing the spatial associations between geological prospecting big data (GPBD) and locations of known mineralization. Geodata science reveals the inter-correlations between GPBD and mineralization, converts GPBD into mappable criteria, and combines multiple mappable criteria into a mineral potential map. A workflow of the GSMPM is proposed and compared with the traditional workflow of mineral prospectivity mapping. More specifically, each component in such a workflow is explained in detail to demonstrate how geodata science serves mineral prospectivity mapping by deriving geoinformation from geoscience data, generating geo-knowledge from geoinformation, and allowing spatial decision-making by integrating geoinformation and geo-knowledge on the formation of mineral deposits. This review also presents several research directions for GSMPM in the future.
引用
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页码:3415 / 3424
页数:9
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