Sustainability in Mineral Potential Mapping of Key Mineral Resources
A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Sustainability in Geographic Science".
Deadline for manuscript submissions: 18 October 2024 | Viewed by 257
Special Issue Editor
Special Issue Information
Dear Colleagues,
Mineral resources are a significant material basis for ensuring the sustainable development of the national economy and society. Sustainable management of mineral resources requires consideration of resource quality, location, and utilization. The issue of strategic key mineral resources such as lithium, cobalt, and nickel has risen to a national strategic level and received a lot of attention from relevant departments, with significant practical significance. In the era of big data, establishing a coupled model of sustainable geology environment mineral resources and utilizing machine learning and deep learning methods to tap into their resource potential is of great practical significance for the sustainable development of strategic mineral resources.
In this Special Issue, original research articles and reviews are welcome. Research areas may include (but are not limited to) the following:
- Mineral potential mapping of key mineral resource sustainability;
- Coupling model of geological environment and mineral resources;
- Sustainable development and utilization of key metal resources;
- Big data and artificial intelligence for mineral exploration.
I look forward to receiving your contributions.
Dr. Li Sun
Guest Editor
Manuscript Submission Information
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Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- sustainable geology
- environment sustainability
- key metal resources
- mineral potential mapping
- artificial intelligence
- machine learning
- data mining
