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Geodata Science-Based Mineral Prospectivity Mapping: A Review

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Abstract

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.

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Acknowledgments

I thank two reviewers’ comments and suggestions which help me improve this review. This study was supported by the National Natural Science Foundation of China (Nos. 41972303 and 41772344).

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  1. State Key Laboratory of Geological Processes and Mineral Resources, China University of Geosciences, Wuhan, 430074, China

    Renguang Zuo

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Zuo, R. Geodata Science-Based Mineral Prospectivity Mapping: A Review. Nat Resour Res 29, 3415–3424 (2020). https://doi.org/10.1007/s11053-020-09700-9

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