Smart Exploration of Critical Minerals: Integrating Multi-Source Data for Enhanced Mineral Prospectivity Mapping
A special issue of Minerals (ISSN 2075-163X). This special issue belongs to the section "Mineral Exploration Methods and Applications".
Deadline for manuscript submissions: 30 April 2025 | Viewed by 1141
Special Issue Editors
Interests: 2D & 3D mineral prospectivity mapping; geophysical and geochemical anomaly mapping; AI-aided mineral exploration; ore deposit modelling; ore-forming magmatic systems
Interests: mineral prospectivity mapping; remote predictive mapping; remote sensing applications to geological mapping
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The global demand for critical minerals, driven by technological advances and the shift to renewable energy, necessitates innovative exploration techniques. Traditional methods often fall short in addressing the complexities of locating these essential resources. Smart mineral exploration, utilizing cutting-edge technologies, offers a solution by integrating multi-source data to enhance mineral prospectivity mapping.
This Special Issue explores the transformative potential of smart mineral exploration for critical minerals. In recent years, advances in artificial intelligence (AI) and machine learning (ML) have revolutionized mineral exploration by enabling the integration of diverse datasets from geophysical, geochemical, remote sensing, and geological sources. These innovations have not only enhanced the accuracy and efficiency of mineral prospectivity mapping (MPM), but have also opened new avenues for discovering previously overlooked mineral deposits. This Special Issue explores the transformative impact of these technologies on MPM, emphasizing both knowledge-driven and data-driven approaches.
We welcome specific contributions related to the following:
- Smart mineral exploration, highlighting innovative tools and techniques that enhance the exploration process.
- AI- and ML-aided mineral exploration, showcasing case studies and applications that leverage these technologies for improved predictive capabilities.
- Advanced 2D and 3D knowledge-driven and data-driven MPM, focusing on integrating traditional geological knowledge with modern data analytics.
- Numerical simulation and big data analytics for mineral exploration, presenting methodologies that handle large datasets to uncover hidden patterns and insights.
- Geochemical and geophysical anomaly mapping, detailing methods that identify and analyze anomalies indicative of mineral deposits.
- Remote sensing- and GIS-based MPM, discussing the use of remote sensing data and GIS technologies to map and predict mineral occurrences.
This issue provides an overview of smart mineral exploration, highlighting the synergy between various data sources and technologies. By showcasing the latest research and applications, we aim to inspire innovation and collaboration, contributing to the sustainable exploration of critical minerals.
Dr. Amirabbas Karbalaeiramezanali
Dr. Jeff Harris
Guest Editors
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Minerals is an international peer-reviewed open access monthly journal published by MDPI.
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
- critical minerals
- artificial intelligence (AI)
- machine learning (ML)
- mineral exploration
- mineral prospectivity mapping (MPM)
- geophysical data
- geochemical data
- remote sensing
- knowledge-driven approaches
- data-driven approaches
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