Global Mineral Resource Exploration Using Multi-Sensor Satellite Data and Machine Learning Algorithms
A special issue of Minerals (ISSN 2075-163X). This special issue belongs to the section "Mineral Exploration Methods and Applications".
Deadline for manuscript submissions: 31 July 2025 | Viewed by 1
Special Issue Editors
Interests: geoinformatics; spatial data analysis; data sciences and modelling; cyber-physical systems integration; remote sensing and machine learning applications in mineral resource exploration
Special Issue Information
Dear Colleagues,
In recent years, global mineral resource exploration has seen significant advancements, driven by the fusion of multi-sensor satellite data and the rise in machine learning algorithms. These technological breakthroughs have transformed how we identify and assess mineral deposits, enabling more efficient, cost-effective, and accurate exploration processes. This Special Issue, titled "Global Mineral Resource Exploration Using Multi-Sensor Satellite Data and Machine Learning Algorithms", brings together cutting-edge research that addresses the challenges and opportunities in this rapidly evolving field.
The issue will highlight innovative applications of remote sensing technologies such as hyperspectral, multispectral, and radar imaging, combined with artificial intelligence techniques like neural networks, random forests, and deep learning. These tools are being used to process large datasets and reveal new mineral prospects in previously inaccessible or underexplored regions, from mountainous terrains to deeply buried deposits.
Key topics include the integration of satellite data with geochemical, geological, and geophysical datasets, the development of novel machine learning models for mineral prospectivity mapping, and case studies demonstrating successful applications of these technologies in the field. The contributions in this issue aim to provide a comprehensive overview of the current state of mineral exploration, while also setting the stage for future research and technological advancements.
We invite scholars, researchers, and practitioners to engage with this Special Issue and contribute to the ongoing discourse in this exciting intersection of geoscience and technology.
Dr. Muhammad Mahboob
Dr. Iqra Atif
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
- mineral resource exploration
- multi-sensor satellite data
- machine learning algorithms
- remote sensing
- geospatial data
- hyperspectral imaging
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