Topic Editors

Prof. Dr. Yongzhang Zhou
School of Earth Science and Engineering, Sun Yat-sen University, Guangzhou 510275, China
School of Resources and Geosciences, China University of Mining and Technology, Xuzhou 221116, China
School of Information Engineering, China University of Geosciences, Beijing 100083, China

Big Data and AI for Geoscience

Abstract submission deadline
31 October 2026
Manuscript submission deadline
31 December 2026
Viewed by
18

Topic Information

Dear Colleagues,

Big data thinking and artificial intelligence (AI) are rapidly reshaping how geoscientists think, analyze, model, and understand the Earth. This Topic explores both the theoretical foundations and practical applications of big data mining algorithms and AI in geoscience. It focuses on new methodological advances, such as knowledge graphs, machine learning, generative models, and foundation models, and their ability to capture spatial, temporal, and multi-scale and multi-modal patterns in geoscientific data. It also highlights data integration, anomaly detection, simulation acceleration and decision-support tools for mineral resource and geo-environmental challenges. This Topic aims to bridge theory and practice. From a theoretical perspective, this Topic will explore the role of big data paradigms in guiding model development, the integration of domain knowledge into AI systems, and the validation of AI methods against physical constraints and geoscientific understanding. On the practical side, this Topic showcases contributions from diverse fields, covering geology, geochemistry, geophysics, mineral exploration, remote sensing, natural hazard prediction, and hydrological forecasting. This Topic also sparks discussions on rigorous, interpretable, and impactful AI, setting the stage for its future in geoscience research.

Prof. Dr. Yongzhang Zhou
Prof. Dr. Hui Yang
Dr. Xiaohui Ji
Topic Editors

Keywords

  • big data mining algorithms
  • machine learning
  • knowledge graph
  • LLM
  • multi-modal data fusion
  • explainable AI
  • computer vision
  • probabilistic forecasting
  • geological modeling
  • geophysical inversion
  • geochemical exploration
  • mineral targeting
  • remote sensing
  • natural hazard prediction
  • hydrological forecasting

Participating Journals

Journal Name Impact Factor CiteScore Launched Year First Decision (median) APC
Remote Sensing
remotesensing
4.1 8.6 2009 24.9 Days CHF 2700 Submit
Minerals
minerals
2.2 4.4 2011 18.2 Days CHF 2400 Submit
Geosciences
geosciences
2.1 5.1 2011 23.4 Days CHF 1800 Submit
GeoHazards
geohazards
1.6 2.2 2020 17.2 Days CHF 1400 Submit
Applied Sciences
applsci
2.5 5.5 2011 19.8 Days CHF 2400 Submit

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Published Papers

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