Big Data and AI for Geoscience

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