Remote Sensing for Mineral Exploration: Current Progress and Future Vision
A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Remote Sensing in Geology, Geomorphology and Hydrology".
Deadline for manuscript submissions: 31 January 2026 | Viewed by 1215
Special Issue Editors
Interests: hyperspectral remote sensing; mineral exploration; spectral analysis
Interests: remote sensing geology
Interests: remote sensing; machine learning algorithms; geological exploration; mineral deposits; Li mineralizations; geochemistry
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Remote sensing technology can rapidly, accurately, and non-destructively obtain information regarding the mineralization of surface and underground mineral deposits, becoming an efficient and economical detection method in mineral exploration. In recent years, due to the rapid development of sensor technology, aerospace technology, and computer technology, the spatial resolution, spectral resolution, and time resolution of remote sensing data have been enhanced continuously. Meanwhile, observation platforms are developing towards multi-platforms, including ground, aviation, and aerospace platforms. The successful application of remote sensing technology has been achieved in the field of mineral exploration, covering the identification of lithology, alteration extraction, the identification of fine minerals, and prospective prediction. In particular, hyperspectral remote sensing technology has shown significant advantages in the fine identification of rocks and minerals. With the application of advanced methods such as artificial intelligence and machine learning, the capabilities of remote sensing technology in mineral exploration have been significantly enhanced.
This Special Issue will outline the latest advances and trends in remote sensing-based mineral exploration, and contribute to the sustainable development of the global mining industry. We welcome the submission of articles related to this topic, including research based on new advances in laboratory hyperspectral reflectance and research performed using recent and emerging technologies such as hyperspectral imaging and deep learning.
Dr. Hengqian Zhao
Prof. Dr. Zhifang Zhao
Dr. Joana Cardoso-Fernandes
Dr. Deshuai Yuan
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. Remote Sensing is an international peer-reviewed open access semimonthly 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 2700 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
- remote sensing
- mineral exploration
- multispectral and hyperspectral
- lithology
- mineralization
- deep learning
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