Cutting-edge Techniques for Sustainable Exploration of Critical Minerals

AI Algorithms for Multidisciplinary Geoscientific Data Processing and Fusion
Erscheinungsjahr 2027
ISBN: 978-0-443-45250-5
Verlag: Elsevier Science & Technology

Buch, Englisch, Format (B × H): 191 mm x 235 mm, Gewicht: 450 g

Cutting-edge Techniques for Sustainable Exploration of Critical Minerals: AI Algorithms for Multidisciplinary Geoscientific Data Processing and Fusion presents a comprehensive overview of the evolving landscape of critical minerals exploration, emphasizing the role of artificial intelligence (AI) in enhancing efficiency and sustainability. The book begins by defining critical minerals, outlining their geological occurrences, and discussing their essential applications in modern technology and renewable energy. It highlights the importance of integrating multidisciplinary geoscientific datasets, which form the foundation for effective exploration strategies. The text explores various AI techniques and their applications in processing and fusing diverse data sources, enabling more informed decision-making in mineral exploration. Real-world case studies demonstrate the successful implementation of AI and machine learning in identifying and assessing critical mineral deposits globally, showcasing the transformative potential of these technologies. Additionally, the book addresses future trends in sustainable exploration practices, emphasizing the need for innovative approaches that minimize environmental impact while maximizing resource recovery. Ultimately, this book underscores the critical intersection of AI and geoscience in driving sustainable practices for the exploration of vital mineral resources essential for the future of technology and environmental stewardship.

Autoren/Hrsg.

Pour, Amin Beiranvand

Zoheir, Basem

Hashim, Mazlan

Fachgebiete

• Geowissenschaften Geologie Geologie
• Wirtschaftswissenschaften Wirtschaftssektoren & Branchen Primärer Sektor
• Wirtschaftswissenschaften Betriebswirtschaft Unternehmensforschung
• Mathematik | Informatik EDV | Informatik Business Application Unternehmenssoftware

Inhaltsverzeichnis

1. Introduction to Critical Minerals Exploration
2. Geology, Occurrences and Uses of Critical Minerals
3. Multidisciplinary Geoscience Datasets for Exploration of Critical Minerals
4. Artificial Intelligence (AI) techniques
5. Datasets Processing and Fusion Using Artificial Intelligence (AI) Techniques
6. Real-World Examples of AI and Machine Learning in the Exploration of Critical Minerals in a Global Perspective
7. Future Trends in Sustainable Exploration of Critical Minerals

Über Autor(innen)

Zoheir, Basem
Basem Zoheir is a distinguished professor in the Department of Geosciences at King Fahd University of Petroleum and Minerals (KFUPM), Dhahran, Saudi Arabia. He holds a Ph.D. in Mineralogy and Economic Geology and has extensive experience in mineral exploration, ore deposit modeling, structural geology, geochronology, and geochemistry. His research focuses on the genesis of precious and critical metal deposits, particularly in relation to tectonics, magmatism, and hydrothermal processes. He has been listed among the World’s Top 2% Scientists by Stanford University for the years 2020-2026, with over 100 peer-reviewed published articles and book chapters and has presented his work at numerous international conferences. He is actively involved in the application of remote sensing, GIS, and machine learning to mineral exploration, with a particular emphasis on sustainable development. He collaborates with academic and industrial partners globally and contributes to advancing the understanding of metallogenic processes in diverse geological settings.

Hashim, Mazlan
Mazlan Hashim is a distinguished professor of Remote Sensing at the Faculty of Built Environment & Surveying and is a senior fellow at the Geoscience Science & Digital Earth Centre (INSTeG), University Technology Malaysia (UTM). Professor Hashim is an expert in satellite remote sensing data processing, mapping and modelling for environmental applications including geological and mineral-related prospecting mapping. He has published his research works in more than 200 high impact articles, and more than 120 proceedings indexed in SCOPUS and Web-of-Science. He was listed among the World’s Top 2% Scientists by Stanford University for the years 2019-2026. Professor Hashim has successfully graduated 27 PhD students and 31 Master by research. In addition, he has also contributed to various applied satellite remote sensing fields by providing consultancies, conducting professional training and offering contract research services at both national and international levels. He is a Fellow of the Academy Sciences Malaysia, and the Institution of Geospatial and Remote Sensing Malaysia.

Pour, Amin Beiranvand
Amin Beiranvand Pour is an internationally recognized academic and research leader in remote sensing, geospatial science, and data-driven mineral systems analysis, with a sustained record of high-impact research at the interface of Earth observation, artificial intelligence, and sustainable resource exploration. He is currently a professor and has held senior research appointments at institutions across the Asia-Pacific and in mineral exploration research, reflecting a strong global research footprint. He has been consistently ranked among the World’s Top 2% Scientists (Stanford University, 2018–2026). He is one of the most highly cited researchers worldwide in geological remote sensing and mineral exploration. He is ranked as the #1 national scientist in Earth Sciences in Malaysia for the years 2023 to 2026. His work is widely recognized for advancing multispectral, hyperspectral, and synthetic aperture radar Earth observation analytics, including the integration of machine learning and deep learning approaches to map lithological units, structural features, and hydrothermal alteration minerals associated with diverse ore mineralization systems in complex, data-limited environments. His work has contributed directly to improved critical mineral targeting, sustainable exploration strategies, and environmental monitoring, aligning strongly with sustainability, climate, and resources.